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    -
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    -
    -

    Return str(self).

    -
    - Source code in hydrolib/core/basemodel.py - 
    def __str__(self) -> str:
-    return str(self.filepath if self.filepath else "")
-
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Known issues and requested features: via GitHub issues .","title":"More information"},{"location":"changelog/","text":"0.6.0 (2023-11-16) \u00b6 Feat \u00b6 Add filetype 10 (polyfile) to class ExtOldFileType (#565) Add missing oldext quantities (#557) Fix \u00b6 Rainfall Runoff .bui file with multiple stations gives parse error 0.5.2 (2023-04-19) \u00b6 Fix \u00b6 failing unittest + SonarCloud security issue (#541) 0.5.1 (2023-04-17) \u00b6 Feat \u00b6 Add the quantity nudge_salinity_temperature to ext old file header. Support the old style external forcings file Add support for several coastal MDU keywords Add support for .tim files and .bc files in the structure file Support meteo blocks in external forcings file (#477) Remove indentation from MDU file Add 4 missing 1D2D settings to FMModel Support *.tim files Add XYN classes to public API (#492) Include old and new observation crossections into MDU FMModel.output class (#470) Support observation crosssection .pli via existing PolyFile class (#464) Add support for 3D Z-sigma settings in MDU Support loading+saving models with configurable OS path style formats (#361) Add support for observation point xyn files (#472) Support filepath as str besides Path for all model classes under FileBasedModel (#469) Add validation for NaN values in datablocks Fix \u00b6 Fixed issues with the new release script Special characters should be parsed correctly from file MDU keywords such as 1d2dLinkFile are written to file without comments (#528) UGRID network files without faces should be accepted correct handling of whitespace and comments in observation point .xyn files (#508) Fix resolving of relative paths containing .. when not using the resolve_casing option. ignore trailing values or text on polyline data lines to better support boundary polyfiles (#482) Reading invalid formatted plifile should raise error instead of warning polyline serializer should print empty trailing comment lines Refactor \u00b6 Make sure of the new Pydantic 1.10 functionality 0.4.1 (2023-01-26) \u00b6 Fix \u00b6 _add_nodes_to_segments fixed ( #440 ) 0.4.0 (2023-01-23) \u00b6 Feat \u00b6 Remove io namespace and add convenient imports/API at several directory levels ( #438 ) Added the option for all supported files to customize the float formatting when saving ( #406 ) Suppress warning in polyfile parser that the white space at the start of the line is ignored ( #409 ) Change data block default spacing from 4 to 2 ( #407 ) Add support for non-recursively loading models ( #401 ) Fix \u00b6 Fixed polylinefile validation for Structure and its subclasses ( #416 ) Rename variable in generate_nodes function ( #437 ) Ensure that QuantityUnitPairs that are not part of a vector are correctly parsed ( #420 ) Enum values are incorrectly written to files ( #403 ) Refactor \u00b6 Small refactoring of the VectorQuantityUnitPairs and VectorForcingBase ( #422 ) Move the base module in XYZ back to IO ( #418 ) Refactored support for vectors in .bc files ( #394 ) 0.3.1 (2022-10-25) \u00b6 Feat \u00b6 option resolve_casing to fix filepath casing between different OS's. Added support for the use of vectors within forcing models with a t3d or timeseries function type. Added possibility to take structure positions into account when discretizing 1d mesh Add support for branches.gui file ( #333 ) Drop extra fields for INIBasedModels if they are not in file format definition Support crs file for observation cross sections ( #289 ) implement mesh generation for pipes ( #294 ) and fix support different reference system ( #298 ) ( #299 ) removed the writeBalanceFile keyword from the mdu support copying generic files/models ( #281 ) Support extra MDU sections ( #284 ) add binder support with a dockerfile ( #264 ) Fix \u00b6 Add backwards compatibility for the old \"percentage from bed\" vertical position type. Fix freeze when printing a ForcingModel with multiple [forcing] blocks by omitting the datablocks. T3D header is not correct ( #356 ) Change AutoStart type from bool to int ( #349 ) Skip serialization of empty INI properties when configured ( #336 ) Net writer should not produce NaN as fill values ( #363 ) Change type of xcoordinates and ycoordinates in Lateral class from int to float ( #351 ) Fix that single structure in StructureModel class is correctly converted to a list ( #352 ) Ensure poly files can be saved ( #344 ) write correct branchorder to net file ( #335 ) add zdatum vertical position type ( #324 ) parse vertical positions to list ( #325 ) make has_z_values parameter optional in polyfile.parser.read_polyfile ( #312 ) Remove unnessary indent in .bc datablocks ( #304 ) Fix the types of 4 fields in the MDU file ( #283 ) Refactor \u00b6 Location specification root validator ( #347 ) 0.3.0 (2022-07-11) \u00b6 Fix \u00b6 Add water level location validation DamBreaks allow empty file paths in the .fnm file Add modeltype 21 to RR node for open water precipitation/evaporation ( #261 ) filemodel : ResolveRelativeMode is incorrectly set when reading a model with 'pathsRelativeToParent' set to false ( #259 ) Feat \u00b6 network : additional mesh funcs dhydamo support .bc files and more in lateral discharge ( #244 ) add support for observation point ini file ( #236 ) support .bc files and more in lateral discharge Refactor \u00b6 rr : place all RR-related code+tests in own rr subpackage ( #235 ) remove dead code of _process_edges_for_branch 0.2.1 (2022-03-15) \u00b6 Fix \u00b6 parser : correctly parse model input fields with leading digits, such as 1D2DLinkFile. parser : allow empty friction specification in all crossdef types. ( #206 ). 0.2.0 (2021-12-17) \u00b6 Added \u00b6 RainfallRunoff files: NodeFile ( #138 ) and LinkFile ( #140 ) D-Flow FM files: Initial field files: IniFieldModel , also added 1D Field INI format: OneDFieldModel ( #119 ). 1D Roughness INI files: FrictionModel ( #118 ). Storage node files: StorageNodeModel ( #131 ). General structure: GeneralStructure ( #79 ). Many additions to the API documentation . Changed \u00b6 All classes that have fields with \"keyword values\" (such as frictionType = WhiteColebrook ) now use Enum classes for those values. See for example FrictionType and FlowDirection ( #98 ) All crosssection definition type now supported as subclasses of CrossSection ( #117 ) Cross section definition and location classes have been moved from hydrolib.core.io.ini.models to hydrolib.core.io.crosssection.models . ( #149 ) Changed behavior for file paths in saved files ( #96 ). More information about: technical background and a tutorial . Fixed \u00b6 Too strict validation of optional fields in culvert ( #75 ), pump ( #76 ), weir ( #77 ), orifice ( #78 ). 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( #206 ).","title":"Fix"},{"location":"changelog/#020-2021-12-17","text":"","title":"0.2.0 (2021-12-17)"},{"location":"changelog/#added","text":"RainfallRunoff files: NodeFile ( #138 ) and LinkFile ( #140 ) D-Flow FM files: Initial field files: IniFieldModel , also added 1D Field INI format: OneDFieldModel ( #119 ). 1D Roughness INI files: FrictionModel ( #118 ). Storage node files: StorageNodeModel ( #131 ). General structure: GeneralStructure ( #79 ). Many additions to the API documentation .","title":"Added"},{"location":"changelog/#changed","text":"All classes that have fields with \"keyword values\" (such as frictionType = WhiteColebrook ) now use Enum classes for those values. See for example FrictionType and FlowDirection ( #98 ) All crosssection definition type now supported as subclasses of CrossSection ( #117 ) Cross section definition and location classes have been moved from hydrolib.core.io.ini.models to hydrolib.core.io.crosssection.models . ( #149 ) Changed behavior for file paths in saved files ( #96 ). More information about: technical background and a tutorial .","title":"Changed"},{"location":"changelog/#fixed","text":"Too strict validation of optional fields in culvert ( #75 ), pump ( #76 ), weir ( #77 ), orifice ( #78 ). 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See 0.5.1 release notes for the main 0.5 release notes. HYDROLIB-core 0.5.1 Release Notes \u00b6 HYDROLIB-core 0.5.1 mainly adds more support for D-Flow FM 2D3D models in coastal applications. Compatibility Notes \u00b6 Support for MacOS is temporarily dropped, due to an upgrade to MeshKernel 2.0.2, which has no MacOS version at the moment. We aim to re-enable this support in future releases. New Features \u00b6 Support for cross-platform path style ( #361 ), more info in the loading and saving tutorial . Support for more MDU keywords (1D2D: see #489 , 2D/3D: see #474 , #486 ). Support for [Meteo] blocks in external forcings files ( #446 ) Support for various legacy file formats, to facilitate future model conversions: Observation point *.xyn files ( #459 ). Observation crosssection *.pli files ( #364 , #461 ). Old external forcings file *.ext ( #369 ). Support for timeseries in *.tim files ( #348 ), also included in structure files ( #497 ) and external meteo forcings ( #446 ). Improvements \u00b6 All file-based model class constructors now accept file path as a str , in addition to the already existing pathlib.Path ( #365 ). MeshKernel dependency was updated to version 2.0.2, which has more functionality in its API ( #450 ). Bugfixes \u00b6 See the detailed ChangeLog on GitHub . Archive \u00b6 Pre-0.5.0 release notes are available via the ChangeLog on GitHub .","title":"Release notes"},{"location":"releasenotes/#hydrolib-core-052-release-notes","text":"HYDROLIB-core 0.5.2 only contains 'cosmetic' changes, and is otherwise equal to 0.5.1. See 0.5.1 release notes for the main 0.5 release notes.","title":"HYDROLIB-core 0.5.2 Release Notes"},{"location":"releasenotes/#hydrolib-core-051-release-notes","text":"HYDROLIB-core 0.5.1 mainly adds more support for D-Flow FM 2D3D models in coastal applications.","title":"HYDROLIB-core 0.5.1 Release Notes"},{"location":"releasenotes/#compatibility-notes","text":"Support for MacOS is temporarily dropped, due to an upgrade to MeshKernel 2.0.2, which has no MacOS version at the moment. We aim to re-enable this support in future releases.","title":"Compatibility Notes"},{"location":"releasenotes/#new-features","text":"Support for cross-platform path style ( #361 ), more info in the loading and saving tutorial . Support for more MDU keywords (1D2D: see #489 , 2D/3D: see #474 , #486 ). Support for [Meteo] blocks in external forcings files ( #446 ) Support for various legacy file formats, to facilitate future model conversions: Observation point *.xyn files ( #459 ). Observation crosssection *.pli files ( #364 , #461 ). Old external forcings file *.ext ( #369 ). Support for timeseries in *.tim files ( #348 ), also included in structure files ( #497 ) and external meteo forcings ( #446 ).","title":"New Features"},{"location":"releasenotes/#improvements","text":"All file-based model class constructors now accept file path as a str , in addition to the already existing pathlib.Path ( #365 ). MeshKernel dependency was updated to version 2.0.2, which has more functionality in its API ( #450 ).","title":"Improvements"},{"location":"releasenotes/#bugfixes","text":"See the detailed ChangeLog on GitHub .","title":"Bugfixes"},{"location":"releasenotes/#archive","text":"Pre-0.5.0 release notes are available via the ChangeLog on GitHub .","title":"Archive"},{"location":"guides/contributing/","text":"Contributing \u00b6 Tooling \u00b6 Poetry \u00b6 We use poetry to manage our package and its dependencies. More information on the separate Poetry page. Pytest \u00b6 We use pytest to test our package. Run it with poetry run pytest to test your code changes locally. Black \u00b6 We use black as an autoformatter. It is also run during CI and will fail if it's not formatted beforehand. Isort \u00b6 We use isort as an autoformatter. Commitizen \u00b6 We use commitizen to automatically bump the version number. If you use conventional commit messages , the changelog.md is generated automatically. More details below under \"Merging\" . Development \u00b6 Branches \u00b6 For each issue or feature, a separate branch should be created from the main. To keep the branches organized each branch should be created with a prefix in the name: * feat/ for new features and feature improvements; * fix/ for bugfixes; * docs/ for documentation; * chore/ for tasks, tool changes, configuration work, everything not relevant for external users. After this prefix, preferrably add the issue number, followed by a brief title using underscores. For example: feat/160_obsfile or, fix/197_validation_pump_stages . Pull requests \u00b6 When starting development on a branch, a pull request should be created for reviews and continous integration. In the description text area on GitHub, use a closing keyword such that this PR will be automatically linked to the issue. For example: Fixes #160 . During continuous integration, the checks will be run with python 3.8 and 3.9 on Windows, Ubuntu and MacOS. The checks consist of running the tests, checking the code formatting and running SonarCloud. We advise to use a draft pull request, to prevent the branch to be merged back before developement is finished. When the branch is ready for review, you can update the status of the pull request to \"ready for review\". Reviews \u00b6 When an issue is ready for review, it should be moved to the \"Ready for review\" column on the GitHub board for visibility. Merging \u00b6 Merging a branch can only happen when a pull request is accepted through review. When a pull request is accepted the changes should be merged back with the \"squash and merge\" option. The merge commit message should adhere to the conventional commit guidelines . * In the first textfield of the GitHub commit form, use for example: feat: Support 3D timeseries in .bc file , without any PR/issue references. * In the text area of the GitHub commit form, optionally add some more description details on the commit. * In the same text area, add footer line Refs: # , and if needed an extra line BREAKING CHANGE: explanation . Don't forget a blank line between footer lines and the preceding description lines (if present). Coding guidelines \u00b6 If there is code that needs to be tested, there should be tests written for it. If there are any additions or changes to the public API, the documentation should be updated. Files should be added to the appropriate folder to keep modules and objects within the correct scope. Releasing \u00b6 Making a release on GitHub and PyPi \u00b6 When we are releasing hydrolib-core, we want to create a release on GitHub and PyPi. This should only be done by one of the hydrolib-core maintainers. To prepare for releasing, please make sure you have a clean checkout of the latest main branch and follow these steps: Go to the root level your hydrolib-core checkout location Open your command line in this location Perform the following commands: If commitizen is not installed yet: pip install commitizen Prepare the Changelog before bumping the release version: cz changelog --unreleased-version=\"0.3.1\" --incremental In the above command, use the version tag instead of the raw version number (so without \"v\" in our case). If you don't know the version tag yet, you can do a dry-run of the next step, for example via: cz bump --dry-run --increment PATCH In the updated docs/changelog.md , manually add links to GitHub PR numbers (or issue numbers) at the end of each line, if appropriate. It is recommended to use the macros [#123](https://github.com/Deltares/HYDROLIB-core/pull/123) , resp. [#345](https://github.com/Deltares/HYDROLIB-core/issues/345) to get automatic hyperlinks (where 123 and 345 are GitHub's PR and issue numbers, respectively). Use MAJOR, MINOR or PATCH to increment the version cz bump --increment {MAJOR,MINOR,PATCH} Or let commitizen detect the increment automatically cz bump Push the tags and changes to git git push --tags git push Build the wheels and publish the package to PyPi poetry build poetry publish You will need a PyPI account and permissions for this publish step. Ask a maintainer for help if you need this. Go to the hydrolib-core GitHub page. Go to Releases and click on Draft a new release . Fill in the Release title field with Release v , with in the full format .. , for example Release v0.3.0 . Choose the appropriate version tag in the Choose a tag dropdown box (typically without \"v\" prefix). Click on Generate release notes . Click on Publish release . Celebrate","title":"Contributing"},{"location":"guides/contributing/#contributing","text":"","title":"Contributing"},{"location":"guides/contributing/#tooling","text":"","title":"Tooling"},{"location":"guides/contributing/#poetry","text":"We use poetry to manage our package and its dependencies. More information on the separate Poetry page.","title":"Poetry"},{"location":"guides/contributing/#pytest","text":"We use pytest to test our package. Run it with poetry run pytest to test your code changes locally.","title":"Pytest"},{"location":"guides/contributing/#black","text":"We use black as an autoformatter. It is also run during CI and will fail if it's not formatted beforehand.","title":"Black"},{"location":"guides/contributing/#isort","text":"We use isort as an autoformatter.","title":"Isort"},{"location":"guides/contributing/#commitizen","text":"We use commitizen to automatically bump the version number. If you use conventional commit messages , the changelog.md is generated automatically. More details below under \"Merging\" .","title":"Commitizen"},{"location":"guides/contributing/#development","text":"","title":"Development"},{"location":"guides/contributing/#branches","text":"For each issue or feature, a separate branch should be created from the main. To keep the branches organized each branch should be created with a prefix in the name: * feat/ for new features and feature improvements; * fix/ for bugfixes; * docs/ for documentation; * chore/ for tasks, tool changes, configuration work, everything not relevant for external users. After this prefix, preferrably add the issue number, followed by a brief title using underscores. For example: feat/160_obsfile or, fix/197_validation_pump_stages .","title":"Branches"},{"location":"guides/contributing/#pull-requests","text":"When starting development on a branch, a pull request should be created for reviews and continous integration. In the description text area on GitHub, use a closing keyword such that this PR will be automatically linked to the issue. For example: Fixes #160 . During continuous integration, the checks will be run with python 3.8 and 3.9 on Windows, Ubuntu and MacOS. The checks consist of running the tests, checking the code formatting and running SonarCloud. We advise to use a draft pull request, to prevent the branch to be merged back before developement is finished. When the branch is ready for review, you can update the status of the pull request to \"ready for review\".","title":"Pull requests"},{"location":"guides/contributing/#reviews","text":"When an issue is ready for review, it should be moved to the \"Ready for review\" column on the GitHub board for visibility.","title":"Reviews"},{"location":"guides/contributing/#merging","text":"Merging a branch can only happen when a pull request is accepted through review. When a pull request is accepted the changes should be merged back with the \"squash and merge\" option. The merge commit message should adhere to the conventional commit guidelines . * In the first textfield of the GitHub commit form, use for example: feat: Support 3D timeseries in .bc file , without any PR/issue references. * In the text area of the GitHub commit form, optionally add some more description details on the commit. * In the same text area, add footer line Refs: # , and if needed an extra line BREAKING CHANGE: explanation . Don't forget a blank line between footer lines and the preceding description lines (if present).","title":"Merging"},{"location":"guides/contributing/#coding-guidelines","text":"If there is code that needs to be tested, there should be tests written for it. If there are any additions or changes to the public API, the documentation should be updated. Files should be added to the appropriate folder to keep modules and objects within the correct scope.","title":"Coding guidelines"},{"location":"guides/contributing/#releasing","text":"","title":"Releasing"},{"location":"guides/contributing/#making-a-release-on-github-and-pypi","text":"When we are releasing hydrolib-core, we want to create a release on GitHub and PyPi. This should only be done by one of the hydrolib-core maintainers. To prepare for releasing, please make sure you have a clean checkout of the latest main branch and follow these steps: Go to the root level your hydrolib-core checkout location Open your command line in this location Perform the following commands: If commitizen is not installed yet: pip install commitizen Prepare the Changelog before bumping the release version: cz changelog --unreleased-version=\"0.3.1\" --incremental In the above command, use the version tag instead of the raw version number (so without \"v\" in our case). If you don't know the version tag yet, you can do a dry-run of the next step, for example via: cz bump --dry-run --increment PATCH In the updated docs/changelog.md , manually add links to GitHub PR numbers (or issue numbers) at the end of each line, if appropriate. It is recommended to use the macros [#123](https://github.com/Deltares/HYDROLIB-core/pull/123) , resp. [#345](https://github.com/Deltares/HYDROLIB-core/issues/345) to get automatic hyperlinks (where 123 and 345 are GitHub's PR and issue numbers, respectively). Use MAJOR, MINOR or PATCH to increment the version cz bump --increment {MAJOR,MINOR,PATCH} Or let commitizen detect the increment automatically cz bump Push the tags and changes to git git push --tags git push Build the wheels and publish the package to PyPi poetry build poetry publish You will need a PyPI account and permissions for this publish step. Ask a maintainer for help if you need this. Go to the hydrolib-core GitHub page. Go to Releases and click on Draft a new release . Fill in the Release title field with Release v , with in the full format .. , for example Release v0.3.0 . Choose the appropriate version tag in the Choose a tag dropdown box (typically without \"v\" prefix). Click on Generate release notes . Click on Publish release . Celebrate","title":"Making a release on GitHub and PyPi"},{"location":"guides/devcontainers/","text":"Devcontainers: Developing HYDROLIB in an isolated environment \u00b6 A common struggle while working on any software project, is to ensure all of your dependencies are available and you can actually build the software, run the tests etc. While any developer is free to choose their own toolchain, environment etc, HYDROLIB-Core includes the necessary files to run the project within a so called devcontainer within Visual Studio Code. With the help of Docker, we can spin up an independent development environment, ensuring that HYDROLIB-Core works out of the box and you are insulated from any specific local configurations on your machines. This should allow you to start working on HYDROLIB-Core quickly. The following sub sections will walk you through the necessary dependencies, and how to use it, and modify it, to fit your own needs. This will be done in the following order: Requirements: Docker and Visual Studio Code Remote - Containers extension Dockerfile configures python, poetry and other dependencies devcontainer.json specifies how visual studio code should be configured External references Requirements: Docker and Visual Studio Code Remote - Containers extension \u00b6 In order to run HYDROLIB in a dev container we need the following dependencies Docker Visual Studio Code Visual Studio Code Remote - Containers extension Docker will ensure we can spin up an isolated container. A full tutorial on how to use Docker is outside the scope of this tutorial, however the Getting Started guide of Docker should provide you with the steps to install Docker on your machine. Visual Studio Code is the editor we will use. The website should provide you with the necessary steps to install it. Lastly, we need to install the Visual Studio Code Remote - Containers extension . The install button on the marketplace should walk you through the steps to install it. Run HYDROLIB in a devcontainer by executing \"Reopen in container\" command \u00b6 With all of the dependencies set up, we should be able to run HYDROLIB within our devcontainer. When opening the HYDROLIB-Core repository in Visual Studio Code, we should either get a pop-up asking us to reopen the project within a remote container, or we can select the \"Open a Remote Window\" button, the green button in the bottom left corner of your visual studio code window, after which we can select \"Reopen in container\". Both will then spin up a new container in which we can work. Note that if it is the first time starting our repository, or if we have made changes to the Docker Images we might need to build the container, which could take a few moments. Once opened in a separate container, we can start a terminal to verify everything is working correctly. First, we need to ensure the correct python interpreter is used. We want to use the virtual environment created by poetry, which default resides in ./.venv/ . Visual Studio Code might prompt you to select an interpreter. If it does press the 'Select Python Interpreter', and select the virtual environment residing in ./.venv/ . If it does not explicitly prompt you (or if you want to change it later on), press ctrl + shift + p , and select 'Python: Select Interpreter'. If it currently is not set to the virtual environment, change it to the correct interpreter. It should now be possible to run the HYDROLIB-Core tests within our container by opening the 'Testing' tab. If the 'Testing' is not already configured in the ./.vscode/settings.json , we will need to configure the Python tests: click the 'Configure Python Tests' button in the 'Testing' tab Select 'pytest' in the pop-up window Select 'tests', this will ensure tests are located in our 'tests' directory Once this is done all tests should pass as they would normally. Dockerfile configures python, poetry and other dependencies \u00b6 The Dockerfile which specifies our specific devcontainer can be found here in the repository . Currently, it extends the python 3.9 buster image provided by the Python foundation. It then does the following: Installs Poetry 1.1.11 and configure the necessary paths Copies the poetry.lock and pyproject.toml and installs the project Installs git within the container This should provide us with a ready to go environment to run HYDROLIB-Core with. devcontainer.json specifies how visual studio code should be configured \u00b6 We can further customise our environment by editing the devcontainer.json located here in the repository . In particular, you can add any Visual Studio Code extensions you require for your work to the extensions field. Currently it is populated with several common Python extensions which we use to develop HYDROLIB. For a full overview how to customise this file, you can find the documentation here External references: \u00b6 Developing inside a Container - VS Code docs Develop with containers - VS Code docs (guide specific for python) Document docker poetry best practices - Poetry issue","title":"Developer container"},{"location":"guides/devcontainers/#devcontainers-developing-hydrolib-in-an-isolated-environment","text":"A common struggle while working on any software project, is to ensure all of your dependencies are available and you can actually build the software, run the tests etc. While any developer is free to choose their own toolchain, environment etc, HYDROLIB-Core includes the necessary files to run the project within a so called devcontainer within Visual Studio Code. With the help of Docker, we can spin up an independent development environment, ensuring that HYDROLIB-Core works out of the box and you are insulated from any specific local configurations on your machines. This should allow you to start working on HYDROLIB-Core quickly. The following sub sections will walk you through the necessary dependencies, and how to use it, and modify it, to fit your own needs. This will be done in the following order: Requirements: Docker and Visual Studio Code Remote - Containers extension Dockerfile configures python, poetry and other dependencies devcontainer.json specifies how visual studio code should be configured External references","title":"Devcontainers: Developing HYDROLIB in an isolated environment"},{"location":"guides/devcontainers/#requirements-docker-and-visual-studio-code-remote-containers-extension","text":"In order to run HYDROLIB in a dev container we need the following dependencies Docker Visual Studio Code Visual Studio Code Remote - Containers extension Docker will ensure we can spin up an isolated container. A full tutorial on how to use Docker is outside the scope of this tutorial, however the Getting Started guide of Docker should provide you with the steps to install Docker on your machine. Visual Studio Code is the editor we will use. The website should provide you with the necessary steps to install it. Lastly, we need to install the Visual Studio Code Remote - Containers extension . The install button on the marketplace should walk you through the steps to install it.","title":"Requirements: Docker and Visual Studio Code Remote - Containers extension"},{"location":"guides/devcontainers/#run-hydrolib-in-a-devcontainer-by-executing-reopen-in-container-command","text":"With all of the dependencies set up, we should be able to run HYDROLIB within our devcontainer. When opening the HYDROLIB-Core repository in Visual Studio Code, we should either get a pop-up asking us to reopen the project within a remote container, or we can select the \"Open a Remote Window\" button, the green button in the bottom left corner of your visual studio code window, after which we can select \"Reopen in container\". Both will then spin up a new container in which we can work. Note that if it is the first time starting our repository, or if we have made changes to the Docker Images we might need to build the container, which could take a few moments. Once opened in a separate container, we can start a terminal to verify everything is working correctly. First, we need to ensure the correct python interpreter is used. We want to use the virtual environment created by poetry, which default resides in ./.venv/ . Visual Studio Code might prompt you to select an interpreter. If it does press the 'Select Python Interpreter', and select the virtual environment residing in ./.venv/ . If it does not explicitly prompt you (or if you want to change it later on), press ctrl + shift + p , and select 'Python: Select Interpreter'. If it currently is not set to the virtual environment, change it to the correct interpreter. It should now be possible to run the HYDROLIB-Core tests within our container by opening the 'Testing' tab. If the 'Testing' is not already configured in the ./.vscode/settings.json , we will need to configure the Python tests: click the 'Configure Python Tests' button in the 'Testing' tab Select 'pytest' in the pop-up window Select 'tests', this will ensure tests are located in our 'tests' directory Once this is done all tests should pass as they would normally.","title":"Run HYDROLIB in a devcontainer by executing \"Reopen in container\" command"},{"location":"guides/devcontainers/#dockerfile-configures-python-poetry-and-other-dependencies","text":"The Dockerfile which specifies our specific devcontainer can be found here in the repository . Currently, it extends the python 3.9 buster image provided by the Python foundation. It then does the following: Installs Poetry 1.1.11 and configure the necessary paths Copies the poetry.lock and pyproject.toml and installs the project Installs git within the container This should provide us with a ready to go environment to run HYDROLIB-Core with.","title":"Dockerfile configures python, poetry and other dependencies"},{"location":"guides/devcontainers/#devcontainerjson-specifies-how-visual-studio-code-should-be-configured","text":"We can further customise our environment by editing the devcontainer.json located here in the repository . In particular, you can add any Visual Studio Code extensions you require for your work to the extensions field. Currently it is populated with several common Python extensions which we use to develop HYDROLIB. For a full overview how to customise this file, you can find the documentation here","title":"devcontainer.json specifies how visual studio code should be configured"},{"location":"guides/devcontainers/#external-references","text":"Developing inside a Container - VS Code docs Develop with containers - VS Code docs (guide specific for python) Document docker poetry best practices - Poetry issue","title":"External references:"},{"location":"guides/developers/","text":"Developer guide \u00b6 This guide contains some more in-depth guidelines, tasks and examples that developers should adhere to when working on hydrolib-core. In addition to being a useful resource for developing, this documentation can also be helpful for code reviews. Explicitly exposing the public API \u00b6 Whenever you add new functionality that should (or could) be used by the users, make sure you explicitly expose them in the correct __init__.py files. For example, you have developed a new TimModel class that represents a .tim file. The TimModel makes use of the TimParser class and TimSerializer class. While the TimModel class should be publicly exposed to the users, because it is part of the public API, the parser and serializer classes are implementation details that users should not be concerned with. The parser and serializer should therefore not be publicly exposed to the users. To expose the TimModel explicitly to our users, you have to update both the hydrolib/core/dflowfm/tim/__init__.py (assuming you created a new tim folder for this new functionality) and the hydrolib/core/dflowfm/__init__.py : # hydrolib/core/dflowfm/tim/__init__.py from .models import TimModel __all__ = [ \"TimModel\" , ] # hydrolib/core/dflowfm/__init__.py ... ... from .tim import * Updating the documentation \u00b6 In the hydrolib-core repository there are several reference files that are used to automatically generate the API reference . If you add or make changes to the existing API, always make sure the API reference is still up to date. Let's use the example mentioned before, where the TimModel was introduced in hydrolib-core. Since this is new functionality that affects the API, we have to update the reference files. The API reference files are located at docs\\reference . Since the TimModel was newly introduced, we should create a new file named tim.md . The contents of this file include a short description about what the '.tim' file is and what it is used for, followed by the actual API. You do not have to manually write the API, that is done for us by mkdocs. Since the newly introduced TimParser and TimSerializer are not part of the public API, they should not be added to the reference file. An example of such an .md can be found below: # Timeseries .tim files Timeseries .tim files are timeseries input files for a [ D-Flow FM ]( glossary.md#d-flow-fm ) model. The support of .tim files is discontinued and are replaced by the [ .bc file ]( #bc-file ). They are represented by the class below. ## Model ::: hydrolib.core.dflowfm.tim.models Updating the functionalities sheet \u00b6 To generate a list of D-HYDRO functionalities, grouped by kernel, and the current status of support inside hydrolib-core, we use an Excel sheet. This Excel sheet can be found at docs\\topics\\dhydro_support_hydrolib-core.xlsx . Each time you add support for new D-HYDRO functionalities, this Excel file has to be updated. Detailed information on how to update the Excel file correctly can be found inside the Excel file itself.","title":"Developer guide"},{"location":"guides/developers/#developer-guide","text":"This guide contains some more in-depth guidelines, tasks and examples that developers should adhere to when working on hydrolib-core. In addition to being a useful resource for developing, this documentation can also be helpful for code reviews.","title":"Developer guide"},{"location":"guides/developers/#explicitly-exposing-the-public-api","text":"Whenever you add new functionality that should (or could) be used by the users, make sure you explicitly expose them in the correct __init__.py files. For example, you have developed a new TimModel class that represents a .tim file. The TimModel makes use of the TimParser class and TimSerializer class. While the TimModel class should be publicly exposed to the users, because it is part of the public API, the parser and serializer classes are implementation details that users should not be concerned with. The parser and serializer should therefore not be publicly exposed to the users. To expose the TimModel explicitly to our users, you have to update both the hydrolib/core/dflowfm/tim/__init__.py (assuming you created a new tim folder for this new functionality) and the hydrolib/core/dflowfm/__init__.py : # hydrolib/core/dflowfm/tim/__init__.py from .models import TimModel __all__ = [ \"TimModel\" , ] # hydrolib/core/dflowfm/__init__.py ... ... from .tim import *","title":"Explicitly exposing the public API"},{"location":"guides/developers/#updating-the-documentation","text":"In the hydrolib-core repository there are several reference files that are used to automatically generate the API reference . If you add or make changes to the existing API, always make sure the API reference is still up to date. Let's use the example mentioned before, where the TimModel was introduced in hydrolib-core. Since this is new functionality that affects the API, we have to update the reference files. The API reference files are located at docs\\reference . Since the TimModel was newly introduced, we should create a new file named tim.md . The contents of this file include a short description about what the '.tim' file is and what it is used for, followed by the actual API. You do not have to manually write the API, that is done for us by mkdocs. Since the newly introduced TimParser and TimSerializer are not part of the public API, they should not be added to the reference file. An example of such an .md can be found below: # Timeseries .tim files Timeseries .tim files are timeseries input files for a [ D-Flow FM ]( glossary.md#d-flow-fm ) model. The support of .tim files is discontinued and are replaced by the [ .bc file ]( #bc-file ). They are represented by the class below. ## Model ::: hydrolib.core.dflowfm.tim.models","title":"Updating the documentation"},{"location":"guides/developers/#updating-the-functionalities-sheet","text":"To generate a list of D-HYDRO functionalities, grouped by kernel, and the current status of support inside hydrolib-core, we use an Excel sheet. This Excel sheet can be found at docs\\topics\\dhydro_support_hydrolib-core.xlsx . Each time you add support for new D-HYDRO functionalities, this Excel file has to be updated. Detailed information on how to update the Excel file correctly can be found inside the Excel file itself.","title":"Updating the functionalities sheet"},{"location":"guides/documentation/","text":"Documentation \u00b6 We use MKdocs for documentation. For full documentation visit mkdocs.org . The documentation itself is written with https://documentation.divio.com/ structure in mind, creating different categories: - Guides - Tutorials - Reference - Topics Commands \u00b6 mkdocs new [dir-name] - Create a new project. mkdocs serve - Start the live-reloading docs server. mkdocs build - Build the documentation site. mkdocs -h - Print help message and exit. Project layout \u00b6 mkdocs.yml # The configuration file. docs/ index.md # The documentation homepage. ... # Other markdown pages, images and other files.","title":"Documentation"},{"location":"guides/documentation/#documentation","text":"We use MKdocs for documentation. For full documentation visit mkdocs.org . The documentation itself is written with https://documentation.divio.com/ structure in mind, creating different categories: - Guides - Tutorials - Reference - Topics","title":"Documentation"},{"location":"guides/documentation/#commands","text":"mkdocs new [dir-name] - Create a new project. mkdocs serve - Start the live-reloading docs server. mkdocs build - Build the documentation site. mkdocs -h - Print help message and exit.","title":"Commands"},{"location":"guides/documentation/#project-layout","text":"mkdocs.yml # The configuration file. docs/ index.md # The documentation homepage. ... # Other markdown pages, images and other files.","title":"Project layout"},{"location":"guides/gettinghelp/","text":"Getting help \u00b6 See the How-to's and Tutorials to get started using hydrolib-core. For building you own tools upon hydrolib-core, see the API reference for more complete documentation of all current features. If you are missing functionality, please check the list of supported functionalities first. If you think you've encountered a bug, please check the open GitHub issues . Feel free to open a new issue if your issue is not yet known. You can contact the package maintainers about any remaining questions you have.","title":"Getting help"},{"location":"guides/gettinghelp/#getting-help","text":"See the How-to's and Tutorials to get started using hydrolib-core. For building you own tools upon hydrolib-core, see the API reference for more complete documentation of all current features. If you are missing functionality, please check the list of supported functionalities first. If you think you've encountered a bug, please check the open GitHub issues . Feel free to open a new issue if your issue is not yet known. You can contact the package maintainers about any remaining questions you have.","title":"Getting help"},{"location":"guides/poetry/","text":"Installation using Poetry \u00b6 You can use a Poetry-based installation if you are using hydrolib-core from a local clone of the Github repository, for example if you intend to contribute to the code. Clone the GitHub repo \u00b6 Use your own preferred way of cloning the GitHub repository of hydrolib-core. In the examples below it is placed in C:\\checkouts\\HYDROLIB-core_git . Use Poetry to install hydrolib-core \u00b6 We use poetry to manage our package and its dependencies. Note If you use conda , do not combine conda virtual environments with the poetry virtual environment. In other words, run the poetry install command from the base conda environment. Download + installation instructions for Poetry are here . After installation of Poetry itself, now use it to install your local clone of the hydrolib-core package, as follows. Make sure Poetry is available on your PATH and run poetry install in the hydrolib-core directory in your shell of choice. This will create a virtual environment in which hydrolib-core is installed and made available for use in your own scripts. For example in an Anaconda PowerShell: (base) PS C:\\checkouts\\HYDROLIB-core_git> poetry install Creating virtualenv hydrolib-core-kHkQBdtS-py3.8 in C:\\Users\\dam_ar\\AppData\\Local\\pypoetry\\Cache\\virtualenvs Installing dependencies from lock file Package operations: 67 installs, 0 updates, 0 removals * Installing six (1.16.0) [..] Installing the current project: hydrolib-core (0.1.5) (base) PS C:\\checkouts\\HYDROLIB-core_git> If you need to use an already existing Python installation, you can activate it and run poetry env use system before poetry install . Test your installation, by running the hydrolib-core pytest suite via poetry: (base) PS C:\\checkouts\\HYDROLIB-core_git> poetry run pytest ===================================== test session starts ====================================== platform win32 -- Python 3.8.8, pytest-6.2.5, py-1.10.0, pluggy-1.0.0 rootdir: C:\\checkouts\\HYDROLIB-core_git, configfile: pyproject.toml plugins: cov-2.12.1 collected 473 items / 2 deselected / 471 selected tests\\io\\dflowfm\\ini\\test_ini.py ........................................................ [ 3%] tests\\io\\dflowfm\\test_bc.py .... [ 4%] tests\\io\\dflowfm\\test_ext.py ........................................................ [ 5%] tests\\io\\dflowfm\\test_fnm.py .................. [ 11%] tests\\io\\dflowfm\\test_net.py ............ [ 11%] tests\\io\\dflowfm\\test_parser.py . [ 12%] tests\\io\\dflowfm\\test_polyfile.py ........................................................[ 23%] .................................... [ 27%] tests\\io\\dflowfm\\test_structure.py .......................................................[ 42%] ......................................................... [ 54%] tests\\io\\dimr\\test_dimr.py ... [ 56%] tests\\io\\rr\\meteo\\test_bui.py ........................... [ 57%] tests\\io\\test_docker.py . [ 70%] tests\\test_model.py ............... [ 78%] tests\\test_utils.py ....... [ 91%] ......................................... [100%] ============================== 471 passed, 2 deselected in 3.50s =============================== (base) PS C:\\checkouts\\HYDROLIB-core_git> Start using hydrolib-core. You can launch your favourite editor (for example VS Code) by first starting a poetry shell with the virtual hydrolib-core environment: (base) PS C:\\checkouts\\HYDROLIB-core_git> poetry shell (base) PS C:\\checkouts\\HYDROLIB-core_git> code Frequently asked questions \u00b6 How to fix \"File ... does not exist\" errors during poetry install as in the example below? * Installing six (1.16.0) ValueError File \\C:\\Users\\dam_ar\\AppData\\Local\\pypoetry\\Cache\\artifacts\\48\\e6\\04\\8118155ae3ec3a16dd2a213bbf7a7d8a62c596b2e90f73a22c896269f1\\six-1.16.0-py2.py3-none-any.whl does not exist This may occur when a conda environment was activated. Delete the AppData\\Local\\pypoetry\\Cache directory. Then run conda deactivate to return to the base environment. Finally, rerun poetry install .","title":"Local clone + Poetry"},{"location":"guides/poetry/#installation-using-poetry","text":"You can use a Poetry-based installation if you are using hydrolib-core from a local clone of the Github repository, for example if you intend to contribute to the code.","title":"Installation using Poetry"},{"location":"guides/poetry/#clone-the-github-repo","text":"Use your own preferred way of cloning the GitHub repository of hydrolib-core. In the examples below it is placed in C:\\checkouts\\HYDROLIB-core_git .","title":"Clone the GitHub repo"},{"location":"guides/poetry/#use-poetry-to-install-hydrolib-core","text":"We use poetry to manage our package and its dependencies. Note If you use conda , do not combine conda virtual environments with the poetry virtual environment. In other words, run the poetry install command from the base conda environment. Download + installation instructions for Poetry are here . After installation of Poetry itself, now use it to install your local clone of the hydrolib-core package, as follows. Make sure Poetry is available on your PATH and run poetry install in the hydrolib-core directory in your shell of choice. This will create a virtual environment in which hydrolib-core is installed and made available for use in your own scripts. For example in an Anaconda PowerShell: (base) PS C:\\checkouts\\HYDROLIB-core_git> poetry install Creating virtualenv hydrolib-core-kHkQBdtS-py3.8 in C:\\Users\\dam_ar\\AppData\\Local\\pypoetry\\Cache\\virtualenvs Installing dependencies from lock file Package operations: 67 installs, 0 updates, 0 removals * Installing six (1.16.0) [..] Installing the current project: hydrolib-core (0.1.5) (base) PS C:\\checkouts\\HYDROLIB-core_git> If you need to use an already existing Python installation, you can activate it and run poetry env use system before poetry install . Test your installation, by running the hydrolib-core pytest suite via poetry: (base) PS C:\\checkouts\\HYDROLIB-core_git> poetry run pytest ===================================== test session starts ====================================== platform win32 -- Python 3.8.8, pytest-6.2.5, py-1.10.0, pluggy-1.0.0 rootdir: C:\\checkouts\\HYDROLIB-core_git, configfile: pyproject.toml plugins: cov-2.12.1 collected 473 items / 2 deselected / 471 selected tests\\io\\dflowfm\\ini\\test_ini.py ........................................................ [ 3%] tests\\io\\dflowfm\\test_bc.py .... [ 4%] tests\\io\\dflowfm\\test_ext.py ........................................................ [ 5%] tests\\io\\dflowfm\\test_fnm.py .................. [ 11%] tests\\io\\dflowfm\\test_net.py ............ [ 11%] tests\\io\\dflowfm\\test_parser.py . [ 12%] tests\\io\\dflowfm\\test_polyfile.py ........................................................[ 23%] .................................... [ 27%] tests\\io\\dflowfm\\test_structure.py .......................................................[ 42%] ......................................................... [ 54%] tests\\io\\dimr\\test_dimr.py ... [ 56%] tests\\io\\rr\\meteo\\test_bui.py ........................... [ 57%] tests\\io\\test_docker.py . [ 70%] tests\\test_model.py ............... [ 78%] tests\\test_utils.py ....... [ 91%] ......................................... [100%] ============================== 471 passed, 2 deselected in 3.50s =============================== (base) PS C:\\checkouts\\HYDROLIB-core_git> Start using hydrolib-core. You can launch your favourite editor (for example VS Code) by first starting a poetry shell with the virtual hydrolib-core environment: (base) PS C:\\checkouts\\HYDROLIB-core_git> poetry shell (base) PS C:\\checkouts\\HYDROLIB-core_git> code","title":"Use Poetry to install hydrolib-core"},{"location":"guides/poetry/#frequently-asked-questions","text":"How to fix \"File ... does not exist\" errors during poetry install as in the example below? * Installing six (1.16.0) ValueError File \\C:\\Users\\dam_ar\\AppData\\Local\\pypoetry\\Cache\\artifacts\\48\\e6\\04\\8118155ae3ec3a16dd2a213bbf7a7d8a62c596b2e90f73a22c896269f1\\six-1.16.0-py2.py3-none-any.whl does not exist This may occur when a conda environment was activated. Delete the AppData\\Local\\pypoetry\\Cache directory. Then run conda deactivate to return to the base environment. Finally, rerun poetry install .","title":"Frequently asked questions"},{"location":"guides/setup/","text":"Installation using pip \u00b6 You can use a pip-based installation if you simply want to use hydrolib-core, without making contributions to the package yourself. You should be able to install hydrolib-core with: pip install hydrolib-core Conda specifics \u00b6 Note If you use conda , it is advisable to install hydrolib-core within a new environment with only conda-forge as channel. If you want to create a fresh test environment for hydrolib-core, you could use the following command (only once): conda create -n hydrolib python = 3 .8 -c conda-forge Prior to the pip install , first activate the desired environment: conda activate hydrolib After successful installation, you should be able to do the \"Basic Model\" tutorial .","title":"pip install"},{"location":"guides/setup/#installation-using-pip","text":"You can use a pip-based installation if you simply want to use hydrolib-core, without making contributions to the package yourself. You should be able to install hydrolib-core with: pip install hydrolib-core","title":"Installation using pip"},{"location":"guides/setup/#conda-specifics","text":"Note If you use conda , it is advisable to install hydrolib-core within a new environment with only conda-forge as channel. If you want to create a fresh test environment for hydrolib-core, you could use the following command (only once): conda create -n hydrolib python = 3 .8 -c conda-forge Prior to the pip install , first activate the desired environment: conda activate hydrolib After successful installation, you should be able to do the \"Basic Model\" tutorial .","title":"Conda specifics"},{"location":"include/mkdocs-macros/main/","text":"(function (global, factory) { typeof exports === 'object' && typeof module !== 'undefined' ? module.exports = factory() : typeof define === 'function' && define.amd ? define(factory) : (global = global || self, global.ClipboardCopyElement = factory()); }(this, function () { 'use strict'; function createNode(text) { const node = document.createElement('pre'); node.style.width = '1px'; node.style.height = '1px'; node.style.position = 'fixed'; node.style.top = '5px'; node.textContent = text; return node; } function copyNode(node) { if ('clipboard' in navigator) { // eslint-disable-next-line flowtype/no-flow-fix-me-comments // $FlowFixMe Clipboard is not defined in Flow yet. return navigator.clipboard.writeText(node.textContent); } const selection = getSelection(); if (selection == null) { return Promise.reject(new Error()); } selection.removeAllRanges(); const range = document.createRange(); range.selectNodeContents(node); selection.addRange(range); document.execCommand('copy'); selection.removeAllRanges(); return Promise.resolve(); } function copyText(text) { if ('clipboard' in navigator) { // eslint-disable-next-line flowtype/no-flow-fix-me-comments // $FlowFixMe Clipboard is not defined in Flow yet. return navigator.clipboard.writeText(text); } const body = document.body; if (!body) { return Promise.reject(new Error()); } const node = createNode(text); body.appendChild(node); copyNode(node); body.removeChild(node); return Promise.resolve(); } function copy(button) { const id = button.getAttribute('for'); const text = button.getAttribute('value'); function trigger() { button.dispatchEvent(new CustomEvent('clipboard-copy', { bubbles: true })); } if (text) { copyText(text).then(trigger); } else if (id) { const root = 'getRootNode' in Element.prototype ? button.getRootNode() : button.ownerDocument; if (!(root instanceof Document || 'ShadowRoot' in window && root instanceof ShadowRoot)) return; const node = root.getElementById(id); if (node) copyTarget(node).then(trigger); } } function copyTarget(content) { if (content instanceof HTMLInputElement || content instanceof HTMLTextAreaElement) { return copyText(content.value); } else if (content instanceof HTMLAnchorElement && content.hasAttribute('href')) { return copyText(content.href); } else { return copyNode(content); } } function clicked(event) { const button = event.currentTarget; if (button instanceof HTMLElement) { copy(button); } } function keydown(event) { if (event.key === ' ' || event.key === 'Enter') { const button = event.currentTarget; if (button instanceof HTMLElement) { event.preventDefault(); copy(button); } } } function focused(event) { event.currentTarget.addEventListener('keydown', keydown); } function blurred(event) { event.currentTarget.removeEventListener('keydown', keydown); } class ClipboardCopyElement extends HTMLElement { constructor() { super(); this.addEventListener('click', clicked); this.addEventListener('focus', focused); this.addEventListener('blur', blurred); } connectedCallback() { if (!this.hasAttribute('tabindex')) { this.setAttribute('tabindex', '0'); } if (!this.hasAttribute('role')) { this.setAttribute('role', 'button'); } } get value() { return this.getAttribute('value') || ''; } set value(text) { this.setAttribute('value', text); } } if (!window.customElements.get('clipboard-copy')) { window.ClipboardCopyElement = ClipboardCopyElement; window.customElements.define('clipboard-copy', ClipboardCopyElement); } return ClipboardCopyElement; })); document.addEventListener('clipboard-copy', function(event) { const notice = event.target.querySelector('.notice') notice.hidden = false setTimeout(function() { notice.hidden = true }, 1000) }) pre { line-height: 125%; } td.linenos .normal { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; } span.linenos { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; } td.linenos .special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; } span.linenos.special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; } .highlight-ipynb .hll { background-color: var(--jp-cell-editor-active-background) } .highlight-ipynb { background: var(--jp-cell-editor-background); color: var(--jp-mirror-editor-variable-color) } .highlight-ipynb .c { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment */ .highlight-ipynb .err { color: var(--jp-mirror-editor-error-color) } /* Error */ .highlight-ipynb .k { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword */ .highlight-ipynb .o { color: var(--jp-mirror-editor-operator-color); font-weight: bold } /* Operator */ .highlight-ipynb .p { color: var(--jp-mirror-editor-punctuation-color) } /* Punctuation */ .highlight-ipynb .ch { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Hashbang */ .highlight-ipynb .cm { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Multiline */ .highlight-ipynb .cp { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Preproc */ .highlight-ipynb .cpf { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.PreprocFile */ .highlight-ipynb .c1 { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Single */ .highlight-ipynb .cs { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Special */ .highlight-ipynb .kc { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Constant */ .highlight-ipynb .kd { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Declaration */ .highlight-ipynb .kn { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Namespace */ .highlight-ipynb .kp { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Pseudo */ .highlight-ipynb .kr { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Reserved */ .highlight-ipynb .kt { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Type */ .highlight-ipynb .m { color: var(--jp-mirror-editor-number-color) } /* Literal.Number */ .highlight-ipynb .s { color: var(--jp-mirror-editor-string-color) } /* Literal.String */ .highlight-ipynb .ow { color: var(--jp-mirror-editor-operator-color); font-weight: bold } /* Operator.Word */ .highlight-ipynb .pm { color: var(--jp-mirror-editor-punctuation-color) } /* Punctuation.Marker */ .highlight-ipynb .w { color: var(--jp-mirror-editor-variable-color) } /* Text.Whitespace */ .highlight-ipynb .mb { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Bin */ .highlight-ipynb .mf { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Float */ .highlight-ipynb .mh { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Hex */ .highlight-ipynb .mi { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Integer */ .highlight-ipynb .mo { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Oct */ .highlight-ipynb .sa { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Affix */ .highlight-ipynb .sb { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Backtick */ .highlight-ipynb .sc { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Char */ .highlight-ipynb .dl { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Delimiter */ .highlight-ipynb .sd { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Doc */ .highlight-ipynb .s2 { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Double */ .highlight-ipynb .se { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Escape */ .highlight-ipynb .sh { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Heredoc */ .highlight-ipynb .si { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Interpol */ .highlight-ipynb .sx { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Other */ .highlight-ipynb .sr { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Regex */ .highlight-ipynb .s1 { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Single */ .highlight-ipynb .ss { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Symbol */ .highlight-ipynb .il { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Integer.Long */ /* This file is taken from the built JupyterLab theme.css Found on share/nbconvert/templates/lab/static Some changes have been made and marked with CHANGE */ .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ --jp-shadow-base-lightness: 0; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-400); --jp-border-color1: var(--md-grey-400); --jp-border-color2: var(--md-grey-300); --jp-border-color3: var(--md-grey-200); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(0, 0, 0, 1); --jp-ui-font-color1: rgba(0, 0, 0, 0.87); --jp-ui-font-color2: rgba(0, 0, 0, 0.54); --jp-ui-font-color3: rgba(0, 0, 0, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color1: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color2: rgba(255, 255, 255, 0.7); --jp-ui-inverse-font-color3: rgba(255, 255, 255, 0.5); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(0, 0, 0, 1); --jp-content-font-color1: rgba(0, 0, 0, 0.87); --jp-content-font-color2: rgba(0, 0, 0, 0.54); --jp-content-font-color3: rgba(0, 0, 0, 0.38); --jp-content-link-color: var(--md-blue-700); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: white; --jp-layout-color1: white; --jp-layout-color2: var(--md-grey-200); --jp-layout-color3: var(--md-grey-400); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: #111111; --jp-inverse-layout-color1: var(--md-grey-900); --jp-inverse-layout-color2: var(--md-grey-800); --jp-inverse-layout-color3: var(--md-grey-700); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-900); --jp-brand-color1: var(--md-blue-700); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-900); --jp-accent-color1: var(--md-green-700); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-900); --jp-warn-color1: var(--md-orange-700); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-900); --jp-error-color1: var(--md-red-700); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-900); --jp-success-color1: var(--md-green-700); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-900); --jp-info-color1: var(--md-cyan-700); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--md-grey-100); --jp-cell-editor-border-color: var(--md-grey-300); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 0.5; --jp-cell-prompt-not-active-font-color: var(--md-grey-700); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: var(--md-blue-50); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: #fdd; --jp-rendermime-table-row-background: var(--md-grey-100); --jp-rendermime-table-row-hover-background: var(--md-light-blue-50); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.25); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color1); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.24); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--md-grey-300); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color1); --jp-input-hover-background: var(--jp-layout-color1); --jp-input-background: var(--md-grey-100); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: #d9d9d9; --jp-editor-selected-focused-background: #d7d4f0; --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: #008000; --jp-mirror-editor-atom-color: #88f; --jp-mirror-editor-number-color: #080; --jp-mirror-editor-def-color: #00f; --jp-mirror-editor-variable-color: var(--md-grey-900); --jp-mirror-editor-variable-2-color: #05a; --jp-mirror-editor-variable-3-color: #085; --jp-mirror-editor-punctuation-color: #05a; --jp-mirror-editor-property-color: #05a; --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ba2121; --jp-mirror-editor-string-2-color: #708; --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: #008000; --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: #170; --jp-mirror-editor-attribute-color: #00c; --jp-mirror-editor-header-color: blue; --jp-mirror-editor-quote-color: #090; --jp-mirror-editor-link-color: #00c; --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: white; /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.5; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(245, 200, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } [data-md-color-scheme=\"slate\"] .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ /* The dark theme shadows need a bit of work, but this will probably also require work on the core layout * colors used in the theme as well. */ --jp-shadow-base-lightness: 32; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-700); --jp-border-color1: var(--md-grey-700); --jp-border-color2: var(--md-grey-800); --jp-border-color3: var(--md-grey-900); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(255, 255, 255, 1); --jp-ui-font-color1: rgba(255, 255, 255, 0.87); --jp-ui-font-color2: rgba(255, 255, 255, 0.54); --jp-ui-font-color3: rgba(255, 255, 255, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(0, 0, 0, 1); --jp-ui-inverse-font-color1: rgba(0, 0, 0, 0.8); --jp-ui-inverse-font-color2: rgba(0, 0, 0, 0.5); --jp-ui-inverse-font-color3: rgba(0, 0, 0, 0.3); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(255, 255, 255, 1); --jp-content-font-color1: rgba(255, 255, 255, 1); --jp-content-font-color2: rgba(255, 255, 255, 0.7); --jp-content-font-color3: rgba(255, 255, 255, 0.5); --jp-content-link-color: var(--md-blue-300); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: #111111; --jp-layout-color1: var(--md-grey-900); --jp-layout-color2: var(--md-grey-800); --jp-layout-color3: var(--md-grey-700); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: white; --jp-inverse-layout-color1: white; --jp-inverse-layout-color2: var(--md-grey-200); --jp-inverse-layout-color3: var(--md-grey-400); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-700); --jp-brand-color1: var(--md-blue-500); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-700); --jp-accent-color1: var(--md-green-500); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-700); --jp-warn-color1: var(--md-orange-500); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-700); --jp-error-color1: var(--md-red-500); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-700); --jp-success-color1: var(--md-green-500); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-700); --jp-info-color1: var(--md-cyan-500); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--jp-layout-color1); --jp-cell-editor-border-color: var(--md-grey-700); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 1; --jp-cell-prompt-not-active-font-color: var(--md-grey-300); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: rgba(33, 150, 243, 0.24); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: rgba(244, 67, 54, 0.28); --jp-rendermime-table-row-background: var(--md-grey-900); --jp-rendermime-table-row-hover-background: rgba(3, 169, 244, 0.2); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.6); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color2); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.8); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--jp-layout-color0); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color0); --jp-input-hover-background: var(--jp-layout-color2); --jp-input-background: var(--md-grey-800); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: var(--jp-layout-color2); --jp-editor-selected-focused-background: rgba(33, 150, 243, 0.24); --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: var(--md-green-500); --jp-mirror-editor-atom-color: var(--md-blue-300); --jp-mirror-editor-number-color: var(--md-green-400); --jp-mirror-editor-def-color: var(--md-blue-600); --jp-mirror-editor-variable-color: var(--md-grey-300); --jp-mirror-editor-variable-2-color: var(--md-blue-400); --jp-mirror-editor-variable-3-color: var(--md-green-600); --jp-mirror-editor-punctuation-color: var(--md-blue-400); --jp-mirror-editor-property-color: var(--md-blue-400); --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ff7070; --jp-mirror-editor-string-2-color: var(--md-purple-300); --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: var(--md-green-600); --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: var(--md-green-700); --jp-mirror-editor-attribute-color: var(--md-blue-700); --jp-mirror-editor-header-color: var(--md-blue-500); --jp-mirror-editor-quote-color: var(--md-green-300); --jp-mirror-editor-link-color: var(--md-blue-700); --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: var(--md-grey-400); /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.6; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(255, 225, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* scrollbar related styles. Supports every browser except Edge. */ /* colors based on JetBrain's Darcula theme */ --jp-scrollbar-background-color: #3f4244; --jp-scrollbar-thumb-color: 88, 96, 97; /* need to specify thumb color as an RGB triplet */ --jp-scrollbar-endpad: 3px; /* the minimum gap between the thumb and the ends of a scrollbar */ /* hacks for setting the thumb shape. These do nothing in Firefox */ --jp-scrollbar-thumb-margin: 3.5px; /* the space in between the sides of the thumb and the track */ --jp-scrollbar-thumb-radius: 9px; /* set to a large-ish value for rounded endcaps on the thumb */ /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } :root{--md-red-50: #ffebee;--md-red-100: #ffcdd2;--md-red-200: #ef9a9a;--md-red-300: #e57373;--md-red-400: #ef5350;--md-red-500: #f44336;--md-red-600: #e53935;--md-red-700: #d32f2f;--md-red-800: #c62828;--md-red-900: #b71c1c;--md-red-A100: #ff8a80;--md-red-A200: #ff5252;--md-red-A400: #ff1744;--md-red-A700: #d50000;--md-pink-50: #fce4ec;--md-pink-100: #f8bbd0;--md-pink-200: #f48fb1;--md-pink-300: #f06292;--md-pink-400: #ec407a;--md-pink-500: #e91e63;--md-pink-600: #d81b60;--md-pink-700: #c2185b;--md-pink-800: #ad1457;--md-pink-900: #880e4f;--md-pink-A100: #ff80ab;--md-pink-A200: #ff4081;--md-pink-A400: #f50057;--md-pink-A700: #c51162;--md-purple-50: #f3e5f5;--md-purple-100: #e1bee7;--md-purple-200: #ce93d8;--md-purple-300: #ba68c8;--md-purple-400: #ab47bc;--md-purple-500: #9c27b0;--md-purple-600: #8e24aa;--md-purple-700: #7b1fa2;--md-purple-800: #6a1b9a;--md-purple-900: #4a148c;--md-purple-A100: #ea80fc;--md-purple-A200: #e040fb;--md-purple-A400: #d500f9;--md-purple-A700: #aa00ff;--md-deep-purple-50: #ede7f6;--md-deep-purple-100: #d1c4e9;--md-deep-purple-200: #b39ddb;--md-deep-purple-300: #9575cd;--md-deep-purple-400: #7e57c2;--md-deep-purple-500: #673ab7;--md-deep-purple-600: #5e35b1;--md-deep-purple-700: #512da8;--md-deep-purple-800: #4527a0;--md-deep-purple-900: #311b92;--md-deep-purple-A100: #b388ff;--md-deep-purple-A200: #7c4dff;--md-deep-purple-A400: #651fff;--md-deep-purple-A700: #6200ea;--md-indigo-50: #e8eaf6;--md-indigo-100: #c5cae9;--md-indigo-200: #9fa8da;--md-indigo-300: #7986cb;--md-indigo-400: #5c6bc0;--md-indigo-500: #3f51b5;--md-indigo-600: #3949ab;--md-indigo-700: #303f9f;--md-indigo-800: #283593;--md-indigo-900: #1a237e;--md-indigo-A100: #8c9eff;--md-indigo-A200: #536dfe;--md-indigo-A400: #3d5afe;--md-indigo-A700: #304ffe;--md-blue-50: #e3f2fd;--md-blue-100: #bbdefb;--md-blue-200: #90caf9;--md-blue-300: #64b5f6;--md-blue-400: #42a5f5;--md-blue-500: #2196f3;--md-blue-600: #1e88e5;--md-blue-700: #1976d2;--md-blue-800: #1565c0;--md-blue-900: #0d47a1;--md-blue-A100: #82b1ff;--md-blue-A200: #448aff;--md-blue-A400: #2979ff;--md-blue-A700: #2962ff;--md-light-blue-50: #e1f5fe;--md-light-blue-100: #b3e5fc;--md-light-blue-200: #81d4fa;--md-light-blue-300: #4fc3f7;--md-light-blue-400: #29b6f6;--md-light-blue-500: #03a9f4;--md-light-blue-600: #039be5;--md-light-blue-700: #0288d1;--md-light-blue-800: #0277bd;--md-light-blue-900: #01579b;--md-light-blue-A100: #80d8ff;--md-light-blue-A200: #40c4ff;--md-light-blue-A400: #00b0ff;--md-light-blue-A700: #0091ea;--md-cyan-50: #e0f7fa;--md-cyan-100: #b2ebf2;--md-cyan-200: #80deea;--md-cyan-300: #4dd0e1;--md-cyan-400: #26c6da;--md-cyan-500: #00bcd4;--md-cyan-600: #00acc1;--md-cyan-700: #0097a7;--md-cyan-800: #00838f;--md-cyan-900: #006064;--md-cyan-A100: #84ffff;--md-cyan-A200: #18ffff;--md-cyan-A400: #00e5ff;--md-cyan-A700: #00b8d4;--md-teal-50: #e0f2f1;--md-teal-100: #b2dfdb;--md-teal-200: #80cbc4;--md-teal-300: #4db6ac;--md-teal-400: #26a69a;--md-teal-500: #009688;--md-teal-600: #00897b;--md-teal-700: #00796b;--md-teal-800: #00695c;--md-teal-900: #004d40;--md-teal-A100: #a7ffeb;--md-teal-A200: #64ffda;--md-teal-A400: #1de9b6;--md-teal-A700: #00bfa5;--md-green-50: #e8f5e9;--md-green-100: #c8e6c9;--md-green-200: #a5d6a7;--md-green-300: #81c784;--md-green-400: #66bb6a;--md-green-500: #4caf50;--md-green-600: #43a047;--md-green-700: #388e3c;--md-green-800: #2e7d32;--md-green-900: #1b5e20;--md-green-A100: #b9f6ca;--md-green-A200: #69f0ae;--md-green-A400: #00e676;--md-green-A700: 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sourceMappingURL=mkdocs-jupyter.css.map*/ init_mathjax = function() { if (window.MathJax) { // MathJax loaded MathJax.Hub.Config({ TeX: { equationNumbers: { autoNumber: \"AMS\", useLabelIds: true } }, tex2jax: { inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ], displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ], processEscapes: true, processEnvironments: true }, displayAlign: 'center', CommonHTML: { linebreaks: { automatic: true } } }); MathJax.Hub.Queue([\"Typeset\", MathJax.Hub]); } } init_mathjax(); In [ ]: Copied! def define_env ( env ): \"\"\" Set up specific environment for documentation site, with some convenience macro's. Available custom mkdocs-macros that produce Markdown content: { sobek_um(anchor, linktext) }: (deep)link to SOBEK User Manual PDF. { dflowfm_um(anchor, linktext) }: (deep)link to D-Flow FM User Manual PDF. { gh_issue(number, linktext) }: link to GitHub issue page. { gh_pr(number, linktext) }: link to GitHub pull request page. { gh_repo(path, linktext) }: link to a file's page in the GitHub repo. \"\"\" dflowfm_um_url = ( \"https://content.oss.deltares.nl/delft3dfm1d2d/D-Flow_FM_User_Manual_1D2D.pdf\" ) sobek_um_url = \"https://content.oss.deltares.nl/sobek2/SOBEK_User_Manual.pdf\" hydrolib_core_url = \"https://github.com/Deltares/HYDROLIB-core\" def _get_url ( url : str , anchor : str = None ): return url + ( \"#\" + anchor if anchor else \"\" ) @env . macro def dflowfm_um ( anchor : str = \"\" , linktext : str = \"D-Flow FM UM\" ): \"\"\"Create Markdown link for D-Flow FM User Manual, with optional anchor/bookmark.\"\"\" return \"[\" + linktext + \"](\" + _get_url ( dflowfm_um_url , anchor ) + \")\" @env . macro def sobek_um ( anchor : str = \"\" , linktext : str = \"SOBEK UM\" ): \"\"\"Create Markdown link for SOBEK User Manual, with optional anchor/bookmark.\"\"\" return \"[\" + linktext + \"](\" + _get_url ( sobek_um_url , anchor ) + \")\" @env . macro def gh_issue ( number : int , linktext : str = None ): \"\"\"Create Markdown link to GitHub issue page.\"\"\" return ( \"[\" + ( linktext or \"#\" + str ( number )) + \"](\" + hydrolib_core_url + \"/issues/\" + str ( number ) + \")\" ) @env . macro def gh_pr ( number : int , linktext : str = None ): \"\"\"Create Markdown link to GitHub pull request page.\"\"\" return ( \"[\" + ( linktext or \"#\" + str ( number )) + \"](\" + hydrolib_core_url + \"/pull/\" + str ( number ) + \")\" ) @env . macro def gh_repo ( path : str , linktext : str = None ): \"\"\"Create Markdown link to a file's page in the GitHub repo.\"\"\" return ( \"[\" + ( linktext or \"#\" + path ) + \"](\" + hydrolib_core_url + \"/blob/main/\" + path + \")\" ) def define_env(env): \"\"\" Set up specific environment for documentation site, with some convenience macro's. Available custom mkdocs-macros that produce Markdown content: { sobek_um(anchor, linktext) }: (deep)link to SOBEK User Manual PDF. { dflowfm_um(anchor, linktext) }: (deep)link to D-Flow FM User Manual PDF. { gh_issue(number, linktext) }: link to GitHub issue page. { gh_pr(number, linktext) }: link to GitHub pull request page. { gh_repo(path, linktext) }: link to a file's page in the GitHub repo. \"\"\" dflowfm_um_url = ( \"https://content.oss.deltares.nl/delft3dfm1d2d/D-Flow_FM_User_Manual_1D2D.pdf\" ) sobek_um_url = \"https://content.oss.deltares.nl/sobek2/SOBEK_User_Manual.pdf\" hydrolib_core_url = \"https://github.com/Deltares/HYDROLIB-core\" def _get_url(url: str, anchor: str = None): return url + (\"#\" + anchor if anchor else \"\") @env.macro def dflowfm_um(anchor: str = \"\", linktext: str = \"D-Flow FM UM\"): \"\"\"Create Markdown link for D-Flow FM User Manual, with optional anchor/bookmark.\"\"\" return \"[\" + linktext + \"](\" + _get_url(dflowfm_um_url, anchor) + \")\" @env.macro def sobek_um(anchor: str = \"\", linktext: str = \"SOBEK UM\"): \"\"\"Create Markdown link for SOBEK User Manual, with optional anchor/bookmark.\"\"\" return \"[\" + linktext + \"](\" + _get_url(sobek_um_url, anchor) + \")\" @env.macro def gh_issue(number: int, linktext: str = None): \"\"\"Create Markdown link to GitHub issue page.\"\"\" return ( \"[\" + (linktext or \"#\" + str(number)) + \"](\" + hydrolib_core_url + \"/issues/\" + str(number) + \")\" ) @env.macro def gh_pr(number: int, linktext: str = None): \"\"\"Create Markdown link to GitHub pull request page.\"\"\" return ( \"[\" + (linktext or \"#\" + str(number)) + \"](\" + hydrolib_core_url + \"/pull/\" + str(number) + \")\" ) @env.macro def gh_repo(path: str, linktext: str = None): \"\"\"Create Markdown link to a file's page in the GitHub repo.\"\"\" return ( \"[\" + (linktext or \"#\" + path) + \"](\" + hydrolib_core_url + \"/blob/main/\" + path + \")\" )","title":"Main"},{"location":"reference/api/","text":"API \u00b6 Much of HYDROLIB-core's classes that represent input data are based on BaseModel and FileModel . These build upon the pydantic package for data validation. BaseModel and FileModel \u00b6 Here we define our Pydantic BaseModel with custom settings, as well as a FileModel that inherits from a BaseModel but also represents a file on disk. BaseModel ( BaseModel ) pydantic-model \u00b6 Config \u00b6 alias_generator ( string : str ) -> str \u00b6 Construct a key name from a given field name. The given field name may be a Pydantic Field alias, and the key name is intended to be used as a BaseModel class member variable name. Parameters: Name Type Description Default string str input field name required Source code in hydrolib/core/basemodel.py def to_key ( string : str ) -> str : \"\"\" Construct a key name from a given field name. The given field name may be a Pydantic Field alias, and the key name is intended to be used as a BaseModel class member variable name. Args: string (str): input field name \"\"\" # First replace any leading digits, because those are undesirable # in variable names. digitdict = { \"0\" : \"zero\" , \"1\" : \"one\" , \"2\" : \"two\" , \"3\" : \"three\" , \"4\" : \"four\" , \"5\" : \"five\" , \"6\" : \"six\" , \"7\" : \"seven\" , \"8\" : \"eight\" , \"9\" : \"nine\" , } m = re . search ( r \"^\\d+\" , string ) if m : digitstring = string [ 0 : m . end ()] for key , val in digitdict . items (): digitstring = digitstring . replace ( key , val ) string = digitstring + string [ m . end () :] # Next, replace spaces and hyphens in the potential variable name. return string . lower () . replace ( \" \" , \"_\" ) . replace ( \"-\" , \"\" ) __init__ ( self , ** data : Any ) -> None special \u00b6 Initialize a BaseModel with the provided data. Exceptions: Type Description ValidationError A validation error when the data is invalid. Source code in hydrolib/core/basemodel.py def __init__ ( self , ** data : Any ) -> None : \"\"\"Initialize a BaseModel with the provided data. Raises: ValidationError: A validation error when the data is invalid. \"\"\" try : super () . __init__ ( ** data ) except ValidationError as e : # Give a special message for faulty list input for re in e . raw_errors : if ( hasattr ( re , \"_loc\" ) and hasattr ( re . exc , \"msg_template\" ) and isinstance ( data . get ( to_key ( re . _loc )), list ) ): re . exc . msg_template += ( f \". The key { re . _loc } might be duplicated in the input file.\" ) # Update error with specific model location name identifier = self . _get_identifier ( data ) if identifier is None : raise e else : # If there is an identifier, include this in the ValidationError messages. raise ValidationError ([ ErrorWrapper ( e , loc = identifier )], self . __class__ ) is_file_link ( self ) -> bool \u00b6 Generic attribute for models backed by a file. Source code in hydrolib/core/basemodel.py def is_file_link ( self ) -> bool : \"\"\"Generic attribute for models backed by a file.\"\"\" return False is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/basemodel.py def is_intermediate_link ( self ) -> bool : \"\"\"Generic attribute for models that have children fields that could contain files.\"\"\" return self . is_file_link () show_tree ( self , indent = 0 ) \u00b6 Recursive print function for showing a tree of a model. Source code in hydrolib/core/basemodel.py def show_tree ( self , indent = 0 ): \"\"\"Recursive print function for showing a tree of a model.\"\"\" angle = \"\u221f\" if indent > 0 else \"\" # Only print if we're backed by a file if self . is_file_link (): print ( \" \" * indent * 2 , angle , self ) # Otherwise we recurse through the fields of a model for _ , value in self : # Handle lists of items if not isinstance ( value , list ): value = [ value ] for v in value : if hasattr ( v , \"is_intermediate_link\" ) and v . is_intermediate_link (): # If the field is only an intermediate, print the name only if not v . is_file_link (): print ( \" \" * ( indent * 2 + 2 ), angle , v . __class__ . __name__ ) v . show_tree ( indent + 1 ) DiskOnlyFileModel ( FileModel ) pydantic-model \u00b6 DiskOnlyFileModel provides a stub implementation for file based models which are not explicitly implemented within hydrolib.core. It implements the FileModel with a void parser and serializer, and a save method which copies the file associated with the FileModel to a new location if it exists. We further explicitly assume that when the filepath is None, no file will be written. Actual file model implementations should not inherit from the DiskOnlyFileModel and instead inherit directly from FileModel. is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/basemodel.py def is_intermediate_link ( self ) -> bool : # If the filepath is not None, there is an underlying file, and as such we need # to traverse it. return self . filepath is not None FileCasingResolver \u00b6 Class for resolving file path in a case-insensitive manner. resolve ( self , path : Path ) -> Path \u00b6 Resolve the casing of a file path when the file does exist but not with the exact casing. Parameters: Name Type Description Default path Path The path of the file or directory for which the casing needs to be resolved. required Returns: Type Description Path The file path with the matched casing if a match exists; otherwise, the original file path. Exceptions: Type Description NotImplementedError When this function is called with an operating system other than Windows, Linux or MacOS. Source code in hydrolib/core/basemodel.py def resolve ( self , path : Path ) -> Path : \"\"\"Resolve the casing of a file path when the file does exist but not with the exact casing. Args: path (Path): The path of the file or directory for which the casing needs to be resolved. Returns: Path: The file path with the matched casing if a match exists; otherwise, the original file path. Raises: NotImplementedError: When this function is called with an operating system other than Windows, Linux or MacOS. \"\"\" operating_system = get_operating_system () if operating_system == OperatingSystem . WINDOWS : return self . _resolve_casing_windows ( path ) if operating_system == OperatingSystem . LINUX : return self . _resolve_casing_linux ( path ) if operating_system == OperatingSystem . MACOS : return self . _resolve_casing_macos ( path ) else : raise NotImplementedError ( f \"Path case resolving for operating system { operating_system } is not supported yet.\" ) FileLoadContext \u00b6 FileLoadContext provides the context necessary to resolve paths during the init of a FileModel, as well as ensure the relevant models are only read once. __init__ ( self ) -> None special \u00b6 Create a new empty FileLoadContext. Source code in hydrolib/core/basemodel.py def __init__ ( self ) -> None : \"\"\"Create a new empty FileLoadContext.\"\"\" self . _path_resolver = FilePathResolver () self . _cache = FileModelCache () self . _file_casing_resolver = FileCasingResolver () self . _file_path_style_converter = FilePathStyleConverter () self . _load_settings : Optional [ ModelLoadSettings ] = None cache_is_empty ( self ) -> bool \u00b6 Whether or not the file model cache is empty. Returns: Type Description bool Whether or not the file model cache is empty. Source code in hydrolib/core/basemodel.py def cache_is_empty ( self ) -> bool : \"\"\"Whether or not the file model cache is empty. Returns: bool: Whether or not the file model cache is empty. \"\"\" return self . _cache . is_empty () convert_path_style ( self , file_path : Path ) -> Path \u00b6 Resolve the file path by converting it from its own file path style to the path style for the current operating system. Parameters: Name Type Description Default file_path Path The file path to convert to the OS path style. required Returns: Type Description Path The resolved file path. Source code in hydrolib/core/basemodel.py def convert_path_style ( self , file_path : Path ) -> Path : \"\"\"Resolve the file path by converting it from its own file path style to the path style for the current operating system. Args: file_path (Path): The file path to convert to the OS path style. Returns: Path: The resolved file path. \"\"\" if file_path . is_absolute (): return file_path converted_file_path = self . _file_path_style_converter . convert_to_os_style ( file_path , self . load_settings . path_style ) return Path ( converted_file_path ) get_current_parent ( self ) -> Path \u00b6 Get the current absolute path with which files are resolved. If the current mode is relative to the parent, the latest added parent is added. If the current mode is relative to an anchor path, the latest added anchor path is returned. Returns: Type Description Path The absolute path to the current parent. Source code in hydrolib/core/basemodel.py def get_current_parent ( self ) -> Path : \"\"\"Get the current absolute path with which files are resolved. If the current mode is relative to the parent, the latest added parent is added. If the current mode is relative to an anchor path, the latest added anchor path is returned. Returns: Path: The absolute path to the current parent. \"\"\" return self . _path_resolver . get_current_parent () initialize_load_settings ( self , recurse : bool , resolve_casing : bool , path_style : PathStyle ) \u00b6 Initialize the global model load setting. Can only be set once. Parameters: Name Type Description Default recurse bool Whether or not to recursively load the whole model. required resolve_casing bool Whether or not to resolve the file casing. required path_style PathStyle Which path style is used in the loaded files. required Source code in hydrolib/core/basemodel.py def initialize_load_settings ( self , recurse : bool , resolve_casing : bool , path_style : PathStyle ): \"\"\"Initialize the global model load setting. Can only be set once. Args: recurse (bool): Whether or not to recursively load the whole model. resolve_casing (bool): Whether or not to resolve the file casing. path_style (PathStyle): Which path style is used in the loaded files. \"\"\" if self . _load_settings is None : self . _load_settings = ModelLoadSettings ( recurse , resolve_casing , path_style ) load_settings : ModelLoadSettings property readonly \u00b6 Gets the model load settings. Exceptions: Type Description ValueError When the model load settings have not been initialized yet. Returns: Type Description ModelLoadSettings The model load settings. pop_last_parent ( self ) -> None \u00b6 Pop the last added parent off this FileLoadContext. Source code in hydrolib/core/basemodel.py def pop_last_parent ( self ) -> None : \"\"\"Pop the last added parent off this FileLoadContext.\"\"\" self . _path_resolver . pop_last_parent () push_new_parent ( self , parent_path : Path , relative_mode : ResolveRelativeMode ) -> None \u00b6 Push a new parent_path with the given relative_mode on this FileLoadContext. Parameters: Name Type Description Default parent_path Path The parent path to be added to this FileLoadContext. required relative_mode ResolveRelativeMode The relative mode. required Source code in hydrolib/core/basemodel.py def push_new_parent ( self , parent_path : Path , relative_mode : ResolveRelativeMode ) -> None : \"\"\"Push a new parent_path with the given relative_mode on this FileLoadContext. Args: parent_path (Path): The parent path to be added to this FileLoadContext. relative_mode (ResolveRelativeMode): The relative mode. \"\"\" self . _path_resolver . push_new_parent ( parent_path , relative_mode ) register_model ( self , path : Path , model : FileModel ) -> None \u00b6 Associate the provided model with the provided path. Relative paths will be resolved based on the current state of the FileLoadContext. Parameters: Name Type Description Default path Path The relative path from which the model was loaded. required model FileModel The loaded model. required Source code in hydrolib/core/basemodel.py def register_model ( self , path : Path , model : \"FileModel\" ) -> None : \"\"\"Associate the provided model with the provided path. Relative paths will be resolved based on the current state of the FileLoadContext. Args: path (Path): The relative path from which the model was loaded. model (FileModel): The loaded model. \"\"\" absolute_path = self . _path_resolver . resolve ( path ) self . _cache . register_model ( absolute_path , model ) resolve ( self , path : Path ) -> Path \u00b6 Resolve the provided path. If path is already absolute, it will be returned as is. Otherwise it will be resolved based on the current state of this FileLoadContext. Parameters: Name Type Description Default path Path The path to be resolved. required Returns: Type Description Path An absolute path resolved based on the current state. Source code in hydrolib/core/basemodel.py def resolve ( self , path : Path ) -> Path : \"\"\"Resolve the provided path. If path is already absolute, it will be returned as is. Otherwise it will be resolved based on the current state of this FileLoadContext. Args: path (Path): The path to be resolved. Returns: Path: An absolute path resolved based on the current state. \"\"\" return self . _path_resolver . resolve ( path ) resolve_casing ( self , file_path : Path ) -> Path \u00b6 Resolve the file casing for the provided file path. Parameters: Name Type Description Default file_path Path The file path to resolve the casing for. required Returns: Type Description Path The resolved file path. Source code in hydrolib/core/basemodel.py def resolve_casing ( self , file_path : Path ) -> Path : \"\"\"Resolve the file casing for the provided file path. Args: file_path (Path): The file path to resolve the casing for. Returns: Path: The resolved file path. \"\"\" if self . load_settings . resolve_casing : return self . _file_casing_resolver . resolve ( file_path ) return file_path retrieve_model ( self , path : Optional [ pathlib . Path ]) -> Optional [ FileModel ] \u00b6 Retrieve the model associated with the path. If no model has been associated with the provided path, or the path is None, then None will be returned. Relative paths will be resolved based on the current state of the FileLoadContext. Returns: Type Description [Optional[FileModel]] The file model associated with the provided path if it has been registered, else None. Source code in hydrolib/core/basemodel.py def retrieve_model ( self , path : Optional [ Path ]) -> Optional [ \"FileModel\" ]: \"\"\"Retrieve the model associated with the path. If no model has been associated with the provided path, or the path is None, then None will be returned. Relative paths will be resolved based on the current state of the FileLoadContext. Returns: [Optional[FileModel]]: The file model associated with the provided path if it has been registered, else None. \"\"\" if path is None : return None absolute_path = self . _path_resolver . resolve ( path ) return self . _cache . retrieve_model ( absolute_path ) FileModel ( BaseModel , ABC ) pydantic-model \u00b6 Base class to represent models with a file representation. It therefore always has a filepath and if it is given on initilization, it will parse that file. The filepath can be relative, in which case the paths are expected to be resolved relative to some root model. If a path is absolute, this path will always be used, regardless of a root parent. When saving a model, if the current filepath is relative, the last resolved absolute path will be used. If the model has just been read, the This class extends the validate option of Pydantic, so when when a Path is given to a field with type FileModel , it doesn't error, but actually initializes the FileModel . Attributes: Name Type Description filepath Optional[Path] The path of this FileModel. This path can be either absolute or relative. If it is a relative path, it is assumed to be resolved from some root model. save_location Path A readonly property corresponding with the (current) save location of this FileModel. If read from a file or after saving recursively or after calling synchronize_filepath, this value will be updated to its new state. If made from memory and filepath is not set, it will correspond with cwd / filename.extension __init__ ( self , filepath : Union [ pathlib . Path , str ] = None , resolve_casing : bool = False , recurse : bool = True , path_style : Optional [ str ] = None , * args , ** kwargs ) special \u00b6 Create a new FileModel from the given filepath. If no filepath is provided, the model is initialized as an empty model with default values. If the filepath is provided, it is read from disk. Parameters: Name Type Description Default filepath Optional[PathOrStr] The file path. Defaults to None. None resolve_casing bool Whether or not to resolve the file name references so that they match the case with what is on disk. Defaults to False. False recurse bool Whether or not to recursively load the model. Defaults to True. True path_style Optional[str] Which path style is used in the loaded files. Defaults to the path style that matches the current operating system. Options: 'unix', 'windows'. None Exceptions: Type Description ValueError When an unsupported path style is passed. Source code in hydrolib/core/basemodel.py def __init__ ( self , filepath : Optional [ PathOrStr ] = None , resolve_casing : bool = False , recurse : bool = True , path_style : Optional [ str ] = None , * args , ** kwargs , ): \"\"\"Create a new FileModel from the given filepath. If no filepath is provided, the model is initialized as an empty model with default values. If the filepath is provided, it is read from disk. Args: filepath (Optional[PathOrStr], optional): The file path. Defaults to None. resolve_casing (bool, optional): Whether or not to resolve the file name references so that they match the case with what is on disk. Defaults to False. recurse (bool, optional): Whether or not to recursively load the model. Defaults to True. path_style (Optional[str], optional): Which path style is used in the loaded files. Defaults to the path style that matches the current operating system. Options: 'unix', 'windows'. Raises: ValueError: When an unsupported path style is passed. \"\"\" if not filepath : super () . __init__ ( * args , ** kwargs ) return filepath = FileModel . _change_to_path ( filepath ) path_style = path_style_validator . validate ( path_style ) with file_load_context () as context : context . initialize_load_settings ( recurse , resolve_casing , path_style ) filepath = context . convert_path_style ( filepath ) if not FileModel . _should_load_model ( context ): super () . __init__ ( * args , ** kwargs ) self . filepath = filepath return self . _absolute_anchor_path = context . get_current_parent () loading_path = context . resolve ( filepath ) loading_path = context . resolve_casing ( loading_path ) if context . load_settings . resolve_casing : filepath = self . _get_updated_file_path ( filepath , loading_path ) logger . info ( f \"Loading data from { filepath } \" ) data = self . _load ( loading_path ) context . register_model ( filepath , self ) data [ \"filepath\" ] = filepath kwargs . update ( data ) context . register_model ( filepath , self ) # Note: the relative mode needs to be obtained from the data directly # because self._relative_mode has not been resolved yet (this is done as # part of the __init__), however during the __init__ we need to already # have pushed the new parent. As such we cannot move this call later. relative_mode = self . _get_relative_mode_from_data ( data ) context . push_new_parent ( filepath . parent , relative_mode ) super () . __init__ ( * args , ** kwargs ) self . _post_init_load () context . pop_last_parent () __new__ ( cls , filepath : Union [ pathlib . Path , str ] = None , * args , ** kwargs ) special staticmethod \u00b6 Create a new model. If the file at the provided file path was already parsed, this instance is returned. Parameters: Name Type Description Default filepath Optional[PathOrStr] The file path to the file. Defaults to None. None Returns: Type Description FileModel A file model. Source code in hydrolib/core/basemodel.py def __new__ ( cls , filepath : Optional [ PathOrStr ] = None , * args , ** kwargs ): \"\"\"Create a new model. If the file at the provided file path was already parsed, this instance is returned. Args: filepath (Optional[PathOrStr], optional): The file path to the file. Defaults to None. Returns: FileModel: A file model. \"\"\" filepath = FileModel . _change_to_path ( filepath ) with file_load_context () as context : if ( file_model := context . retrieve_model ( filepath )) is not None : return file_model else : return super () . __new__ ( cls ) __str__ ( self ) -> str special \u00b6 Return str(self). Source code in hydrolib/core/basemodel.py def __str__ ( self ) -> str : return str ( self . filepath if self . filepath else \"\" ) is_file_link ( self ) -> bool \u00b6 Generic attribute for models backed by a file. Source code in hydrolib/core/basemodel.py def is_file_link ( self ) -> bool : return True save ( self , filepath : Optional [ pathlib . Path ] = None , recurse : bool = False , path_style : Optional [ str ] = None ) -> None \u00b6 Save the model to disk. If recurse is set to True, all of the child FileModels will be saved as well. Relative child models are stored relative to this Model, according to the model file hierarchy specified with the respective filepaths. Absolute paths will be written to their respective locations. Note that this will overwrite any existing files that are stored in this location. Note that if recurse is set to True, the save_location properties of the children are updated to their respective new locations. If filepath it is specified, the filepath of this FileModel is set to the specified path before the save operation is executed. If none is specified it will use the current filepath. If the used filepath is relative, it will be stored at the current save_location. If you only want to save a child model of some root model, it is recommended to first call synchronize_filepaths on the root model, to ensure the child model's save_location is correctly determined. Parameters: Name Type Description Default filepath Optional[Path] The file path at which this model is saved. If None is specified it defaults to the filepath currently stored in the filemodel. Defaults to None. None recurse bool Whether to save all children of this FileModel (when set to True), or only save this model (when set to False). Defaults to False. False path_style Optional[str] With which file path style to save the model. File references will be written with the specified path style. Defaults to the path style used by the current operating system. Options: 'unix', 'windows'. None Exceptions: Type Description ValueError When an unsupported path style is passed. Source code in hydrolib/core/basemodel.py def save ( self , filepath : Optional [ Path ] = None , recurse : bool = False , path_style : Optional [ str ] = None , ) -> None : \"\"\"Save the model to disk. If recurse is set to True, all of the child FileModels will be saved as well. Relative child models are stored relative to this Model, according to the model file hierarchy specified with the respective filepaths. Absolute paths will be written to their respective locations. Note that this will overwrite any existing files that are stored in this location. Note that if recurse is set to True, the save_location properties of the children are updated to their respective new locations. If filepath it is specified, the filepath of this FileModel is set to the specified path before the save operation is executed. If none is specified it will use the current filepath. If the used filepath is relative, it will be stored at the current save_location. If you only want to save a child model of some root model, it is recommended to first call synchronize_filepaths on the root model, to ensure the child model's save_location is correctly determined. Args: filepath (Optional[Path], optional): The file path at which this model is saved. If None is specified it defaults to the filepath currently stored in the filemodel. Defaults to None. recurse (bool, optional): Whether to save all children of this FileModel (when set to True), or only save this model (when set to False). Defaults to False. path_style (Optional[str], optional): With which file path style to save the model. File references will be written with the specified path style. Defaults to the path style used by the current operating system. Options: 'unix', 'windows'. Raises: ValueError: When an unsupported path style is passed. \"\"\" if filepath is not None : self . filepath = filepath path_style = path_style_validator . validate ( path_style ) save_settings = ModelSaveSettings ( path_style = path_style ) # Handle save with file_load_context () as context : context . push_new_parent ( self . _absolute_anchor_path , self . _relative_mode ) if recurse : self . _save_tree ( context , save_settings ) else : self . _save_instance ( save_settings ) save_location : Optional [ pathlib . Path ] property readonly \u00b6 Get the current save location which will be used when calling save() This value can be None if the filepath is None and no name can be generated. Returns: Type Description Path The location at which this model will be saved. synchronize_filepaths ( self ) -> None \u00b6 Synchronize the save_location properties of all child models respective to this FileModel's save_location. Source code in hydrolib/core/basemodel.py def synchronize_filepaths ( self ) -> None : \"\"\"Synchronize the save_location properties of all child models respective to this FileModel's save_location. \"\"\" def sync_pre ( model : BaseModel , acc : FileLoadContext ) -> FileLoadContext : if isinstance ( model , FileModel ): acc . push_new_parent ( model . filepath . parent , model . _relative_mode ) # type: ignore[arg-type] return acc def sync_post ( model : BaseModel , acc : FileLoadContext ) -> FileLoadContext : if isinstance ( model , FileModel ): acc . pop_last_parent () model . _absolute_anchor_path = acc . get_current_parent () return acc traverser = ModelTreeTraverser [ FileLoadContext ]( should_traverse = _should_traverse , should_execute = _should_execute , pre_traverse_func = sync_pre , post_traverse_func = sync_post , ) with file_load_context () as context : context . push_new_parent ( self . _absolute_anchor_path , self . _relative_mode ) traverser . traverse ( self , context ) FileModelCache \u00b6 FileModelCache provides a simple structure to register and retrieve FileModel objects. __init__ ( self ) special \u00b6 Create a new empty FileModelCache. Source code in hydrolib/core/basemodel.py def __init__ ( self ): \"\"\"Create a new empty FileModelCache.\"\"\" self . _cache_dict : Dict [ Path , \"FileModel\" ] = {} is_empty ( self ) -> bool \u00b6 Whether or not this file model cache is empty. Returns: Type Description bool Whether or not the cache is empty. Source code in hydrolib/core/basemodel.py def is_empty ( self ) -> bool : \"\"\"Whether or not this file model cache is empty. Returns: bool: Whether or not the cache is empty. \"\"\" return not any ( self . _cache_dict ) register_model ( self , path : Path , model : FileModel ) -> None \u00b6 Register the model with the specified path in this FileModelCache. Parameters: Name Type Description Default path Path The path to associate the model with. required model FileModel The model to be associated with the path. required Source code in hydrolib/core/basemodel.py def register_model ( self , path : Path , model : \"FileModel\" ) -> None : \"\"\"Register the model with the specified path in this FileModelCache. Args: path (Path): The path to associate the model with. model (FileModel): The model to be associated with the path. \"\"\" self . _cache_dict [ path ] = model retrieve_model ( self , path : Path ) -> Optional [ FileModel ] \u00b6 Retrieve the model associated with the (absolute) path if it has been registered before, otherwise return None. Returns: Type Description [Optional[FileModel]] The FileModel associated with the Path if it has been registered before, otherwise None. Source code in hydrolib/core/basemodel.py def retrieve_model ( self , path : Path ) -> Optional [ \"FileModel\" ]: \"\"\"Retrieve the model associated with the (absolute) path if it has been registered before, otherwise return None. Returns: [Optional[FileModel]]: The FileModel associated with the Path if it has been registered before, otherwise None. \"\"\" return self . _cache_dict . get ( path , None ) FilePathResolver \u00b6 FilePathResolver is responsible for resolving relative paths. The current state to which paths are resolved can be altered by pushing a new parent path to the FilePathResolver, or removing the latest added parent path from the FilePathResolver __init__ ( self ) -> None special \u00b6 Create a new empty FilePathResolver. Source code in hydrolib/core/basemodel.py def __init__ ( self ) -> None : \"\"\"Create a new empty FilePathResolver.\"\"\" self . _anchors : List [ Path ] = [] self . _parents : List [ Tuple [ Path , ResolveRelativeMode ]] = [] get_current_parent ( self ) -> Path \u00b6 Get the current absolute path with which files are resolved. If the current mode is relative to the parent, the latest added parent is added. If the current mode is relative to an anchor path, the latest added anchor path is returned. Returns: Type Description Path The absolute path to the current parent. Source code in hydrolib/core/basemodel.py def get_current_parent ( self ) -> Path : \"\"\"Get the current absolute path with which files are resolved. If the current mode is relative to the parent, the latest added parent is added. If the current mode is relative to an anchor path, the latest added anchor path is returned. Returns: Path: The absolute path to the current parent. \"\"\" if self . _anchor : return self . _anchor return self . _direct_parent pop_last_parent ( self ) -> None \u00b6 Pop the last added parent from this FilePathResolver If there are currently no parents defined, nothing will happen. Source code in hydrolib/core/basemodel.py def pop_last_parent ( self ) -> None : \"\"\"Pop the last added parent from this FilePathResolver If there are currently no parents defined, nothing will happen. \"\"\" if not self . _parents : return _ , relative_mode = self . _parents . pop () if relative_mode == ResolveRelativeMode . ToAnchor : self . _anchors . pop () push_new_parent ( self , parent_path : Path , relative_mode : ResolveRelativeMode ) -> None \u00b6 Push a new parent_path with the given relative_mode to this FilePathResolver. Relative paths added to this FilePathResolver will be resolved with respect to the current state, i.e. similar to FilePathResolver.resolve. Parameters: Name Type Description Default parent_path Path The parent path required relative_mode ResolveRelativeMode The relative mode used to resolve. required Source code in hydrolib/core/basemodel.py def push_new_parent ( self , parent_path : Path , relative_mode : ResolveRelativeMode ) -> None : \"\"\"Push a new parent_path with the given relative_mode to this FilePathResolver. Relative paths added to this FilePathResolver will be resolved with respect to the current state, i.e. similar to FilePathResolver.resolve. Args: parent_path (Path): The parent path relative_mode (ResolveRelativeMode): The relative mode used to resolve. \"\"\" absolute_parent_path = self . resolve ( parent_path ) if relative_mode == ResolveRelativeMode . ToAnchor : self . _anchors . append ( absolute_parent_path ) self . _parents . append (( absolute_parent_path , relative_mode )) resolve ( self , path : Path ) -> Path \u00b6 Resolve the provided path to an absolute path given the current state. If the provided path is already absolute, it will be returned as is. Parameters: Name Type Description Default path Path The path to resolve required Returns: Type Description Path An absolute path resolved given the current state. Source code in hydrolib/core/basemodel.py def resolve ( self , path : Path ) -> Path : \"\"\"Resolve the provided path to an absolute path given the current state. If the provided path is already absolute, it will be returned as is. Args: path (Path): The path to resolve Returns: Path: An absolute path resolved given the current state. \"\"\" if path . is_absolute (): return path parent = self . get_current_parent () return ( parent / path ) . resolve () ModelLoadSettings \u00b6 A class that holds the global settings for model loading. __init__ ( self , recurse : bool , resolve_casing : bool , path_style : PathStyle ) -> None special \u00b6 Initializes a new instance of the ModelLoadSettings class. Parameters: Name Type Description Default recurse bool Whether or not to recursively load the whole model. required resolve_casing bool Whether or not to resolve the file casing. required path_style PathStyle Which path style is used in the loaded files. required Source code in hydrolib/core/basemodel.py def __init__ ( self , recurse : bool , resolve_casing : bool , path_style : PathStyle ) -> None : \"\"\"Initializes a new instance of the ModelLoadSettings class. Args: recurse (bool): Whether or not to recursively load the whole model. resolve_casing (bool): Whether or not to resolve the file casing. path_style (PathStyle): Which path style is used in the loaded files. \"\"\" self . _recurse = recurse self . _resolve_casing = resolve_casing self . _path_style = path_style path_style : PathStyle property readonly \u00b6 Gets the path style setting. Returns: Type Description PathStyle Which path style is used in the loaded files. recurse : bool property readonly \u00b6 Gets the recurse setting. Returns: Type Description bool Whether or not to recursively load the whole model. resolve_casing : bool property readonly \u00b6 Gets the resolve casing setting. Returns: Type Description bool Whether or not to resolve the file casing. ModelSaveSettings \u00b6 A class that holds the global settings for model saving. __init__ ( self , path_style : Optional [ hydrolib . core . utils . PathStyle ] = None ) -> None special \u00b6 Initializes a new instance of the ModelSaveSettings class. Parameters: Name Type Description Default path_style Optional[PathStyle] Which file path style to use when saving the model. Defaults to the path style that matches the current operating system. None Source code in hydrolib/core/basemodel.py def __init__ ( self , path_style : Optional [ PathStyle ] = None ) -> None : \"\"\"Initializes a new instance of the ModelSaveSettings class. Args: path_style (Optional[PathStyle], optional): Which file path style to use when saving the model. Defaults to the path style that matches the current operating system. \"\"\" if path_style is None : path_style = self . _os_path_style self . _path_style = path_style path_style : PathStyle property readonly \u00b6 Gets the path style setting. Returns: Type Description PathStyle Which path style is used to save the files. ModelTreeTraverser ( Generic ) \u00b6 ModelTreeTraverser is responsible for traversing a ModelTree using the provided functions. The ModelTreeTraverser will only traverse BaseModel and derived objects. Type parameter TAcc defines the type of Accumulator to be used. __init__ ( self , should_traverse : Optional [ Callable [[ hydrolib . core . basemodel . BaseModel , ~ TAcc ], bool ]] = None , should_execute : Optional [ Callable [[ hydrolib . core . basemodel . BaseModel , ~ TAcc ], bool ]] = None , pre_traverse_func : Optional [ Callable [[ hydrolib . core . basemodel . BaseModel , ~ TAcc ], ~ TAcc ]] = None , post_traverse_func : Optional [ Callable [[ hydrolib . core . basemodel . BaseModel , ~ TAcc ], ~ TAcc ]] = None ) special \u00b6 Create a new ModelTreeTraverser with the given functions. If a predicate it is not defined, it is assumed to always be true, i.e. we will always traverse to the next node, or always execute the traverse functions. If a traverse function is not defined, it will be skipped. The traverse functions share an accumulator, i.e. the accumulator argument is passed through all evaluated traverse functions. It is expected that the traverse function return the (potentially) changed accumulator. Parameters: Name Type Description Default should_traverse Optional[Callable[[BaseModel, TAcc], bool]] Function to evaluate whether to traverse to the provided BaseModel. Defaults to None. None should_execute Optional[Callable[[BaseModel, TAcc], bool]] Function to evaluate whether to execute the traverse functions for the provided BaseModel. Defaults to None. None pre_traverse_func Callable[[BaseModel, TAcc], TAcc] Traverse function executed before we traverse into the next BaseModel, i.e. top-down traversal. Defaults to None. None post_traverse_func Callable[[BaseModel, TAcc], TAcc] Traverse function executed after we traverse into the next BaseModel, i.e. bottom-up traversal. Defaults to None. None Source code in hydrolib/core/basemodel.py def __init__ ( self , should_traverse : Optional [ Callable [[ BaseModel , TAcc ], bool ]] = None , should_execute : Optional [ Callable [[ BaseModel , TAcc ], bool ]] = None , pre_traverse_func : Optional [ Callable [[ BaseModel , TAcc ], TAcc ]] = None , post_traverse_func : Optional [ Callable [[ BaseModel , TAcc ], TAcc ]] = None , ): \"\"\"Create a new ModelTreeTraverser with the given functions. If a predicate it is not defined, it is assumed to always be true, i.e. we will always traverse to the next node, or always execute the traverse functions. If a traverse function is not defined, it will be skipped. The traverse functions share an accumulator, i.e. the accumulator argument is passed through all evaluated traverse functions. It is expected that the traverse function return the (potentially) changed accumulator. Args: should_traverse (Optional[Callable[[BaseModel, TAcc], bool]], optional): Function to evaluate whether to traverse to the provided BaseModel. Defaults to None. should_execute (Optional[Callable[[BaseModel, TAcc], bool]], optional): Function to evaluate whether to execute the traverse functions for the provided BaseModel. Defaults to None. pre_traverse_func (Callable[[BaseModel, TAcc], TAcc], optional): Traverse function executed before we traverse into the next BaseModel, i.e. top-down traversal. Defaults to None. post_traverse_func (Callable[[BaseModel, TAcc], TAcc], optional): Traverse function executed after we traverse into the next BaseModel, i.e. bottom-up traversal. Defaults to None. \"\"\" self . _should_traverse_func = should_traverse self . _should_execute_func = should_execute self . _pre_traverse_func = pre_traverse_func self . _post_traverse_func = post_traverse_func traverse ( self , model : BaseModel , acc : ~ TAcc ) -> ~ TAcc \u00b6 Traverse the model tree of BaseModels including the model as the root, with the provided state of the acc and return the final accumulator. The actual executed functions as well as the predicates defining whether these functions should be executed for this model as well as whether child BaseModel objects should be traversed are provided in the constructor of the ModelTreeTraverser. The final accumulator is returned. Parameters: Name Type Description Default model BaseModel The root model in which the traversal of the model tree starts. required acc TAcc The current accumulator. required Returns: Type Description TAcc The accumulator after the traversal of the model tree. Source code in hydrolib/core/basemodel.py def traverse ( self , model : BaseModel , acc : TAcc ) -> TAcc : \"\"\"Traverse the model tree of BaseModels including the model as the root, with the provided state of the acc and return the final accumulator. The actual executed functions as well as the predicates defining whether these functions should be executed for this model as well as whether child BaseModel objects should be traversed are provided in the constructor of the ModelTreeTraverser. The final accumulator is returned. Args: model (BaseModel): The root model in which the traversal of the model tree starts. acc (TAcc): The current accumulator. Returns: TAcc: The accumulator after the traversal of the model tree. \"\"\" if self . _should_execute_pre ( model , acc ): acc = self . _pre_traverse_func ( model , acc ) # type: ignore[arg-type] for _ , value in model : if not isinstance ( value , list ): value = [ value ] for v in value : if self . _should_traverse ( v , acc ): acc = self . traverse ( v , acc ) if self . _should_execute_post ( model , acc ): acc = self . _post_traverse_func ( model , acc ) # type: ignore[arg-type] return acc ParsableFileModel ( FileModel ) pydantic-model \u00b6 ParsableFileModel defines a FileModel which can be parsed and serialized with a serializer . Each ParsableFileModel has a default _filename and _ext, which are used to generate the file name of any instance where the filepath is not (yet) set. Children of the ParsableFileModel are expected to implement a serializer function which takes a Path and Dict and writes the ParsableFileModel to disk, and a parser function which takes a Path and outputs a Dict. If more complicated solutions are required, a ParsableFileModel child can also opt to overwrite the _serialize and _parse methods, to skip the _get_serializer and _get_parser methods respectively. dict ( self , * args , ** kwargs ) \u00b6 Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/basemodel.py def dict ( self , * args , ** kwargs ): kwargs [ \"exclude\" ] = self . _exclude_fields () return super () . dict ( * args , ** kwargs ) PathStyleValidator \u00b6 Class to take care of path style validation. validate ( self , path_style : Optional [ str ]) -> PathStyle \u00b6 Validates the path style as string on whether it is a supported path style. If it is a valid path style the path style enum value will be return as a result. Parameters: Name Type Description Default path_style Optional[str] The path style as string value. required Returns: Type Description PathStyle The converted PathStyle object. Exceptions: Type Description ValueError When an unsupported path style is passed. Source code in hydrolib/core/basemodel.py def validate ( self , path_style : Optional [ str ]) -> PathStyle : \"\"\"Validates the path style as string on whether it is a supported path style. If it is a valid path style the path style enum value will be return as a result. Args: path_style (Optional[str]): The path style as string value. Returns: PathStyle: The converted PathStyle object. Raises: ValueError: When an unsupported path style is passed. \"\"\" if path_style is None : return self . _os_path_style supported_path_styles = list ( PathStyle ) if path_style in supported_path_styles : return PathStyle ( path_style ) supported_path_style_str = \", \" . join (([ x . value for x in supported_path_styles ])) raise ValueError ( f \"Path style ' { path_style } ' not supported. Supported path styles: { supported_path_style_str } \" ) ResolveRelativeMode ( IntEnum ) \u00b6 ResolveRelativeMode defines the possible resolve modes used within the FilePathResolver. It determines how the relative paths to child models within some FileModel should be interpreted. By default it should be relative to the parent model, i.e. the model in which the mode is defined. However there exist some exceptions, where the relative paths should be evaluated relative to some other folder, regardless of the current parent location. Options Toparent Relative paths should be resolved relative to their direct parent model. Toanchor All relative paths should be resolved relative to the specified regardless of subsequent parent model locations. SerializerConfig ( BaseModel , ABC ) pydantic-model \u00b6 Class that holds the configuration settings for serialization. file_load_context () \u00b6 Provide a FileLoadingContext. If none has been created in the context of this call stack yet, a new one will be created, which will be maintained until it goes out of scope. Yields [FileLoadContext]: The file load context. Source code in hydrolib/core/basemodel.py @contextmanager def file_load_context (): \"\"\"Provide a FileLoadingContext. If none has been created in the context of this call stack yet, a new one will be created, which will be maintained until it goes out of scope. Yields: [FileLoadContext]: The file load context. \"\"\" file_loading_context = context_file_loading . get ( None ) context_reset_token = None if not file_loading_context : file_loading_context = FileLoadContext () context_reset_token = context_file_loading . set ( file_loading_context ) try : yield file_loading_context finally : if context_reset_token is not None : context_file_loading . reset ( context_reset_token ) validator_set_default_disk_only_file_model_when_none () -> classmethod \u00b6 Validator to ensure a default empty DiskOnlyFileModel is created when the corresponding field is initialized with None. Returns: Type Description classmethod Validator to adjust None values to empty DiskOnlyFileModel objects Source code in hydrolib/core/basemodel.py def validator_set_default_disk_only_file_model_when_none () -> classmethod : \"\"\"Validator to ensure a default empty DiskOnlyFileModel is created when the corresponding field is initialized with None. Returns: classmethod: Validator to adjust None values to empty DiskOnlyFileModel objects \"\"\" def adjust_none ( v : Any , field : ModelField ) -> Any : if field . type_ is DiskOnlyFileModel and v is None : return { \"filepath\" : None } return v return validator ( \"*\" , allow_reuse = True , pre = True )( adjust_none )","title":"API"},{"location":"reference/api/#api","text":"Much of HYDROLIB-core's classes that represent input data are based on BaseModel and FileModel . These build upon the pydantic package for data validation.","title":"API"},{"location":"reference/api/#basemodel-and-filemodel","text":"Here we define our Pydantic BaseModel with custom settings, as well as a FileModel that inherits from a BaseModel but also represents a file on disk.","title":"BaseModel and FileModel"},{"location":"reference/api/#hydrolib.core.basemodel.BaseModel","text":"","title":"BaseModel"},{"location":"reference/api/#hydrolib.core.basemodel.BaseModel.Config","text":"","title":"Config"},{"location":"reference/api/#hydrolib.core.basemodel.BaseModel.Config.alias_generator","text":"Construct a key name from a given field name. The given field name may be a Pydantic Field alias, and the key name is intended to be used as a BaseModel class member variable name. Parameters: Name Type Description Default string str input field name required Source code in hydrolib/core/basemodel.py def to_key ( string : str ) -> str : \"\"\" Construct a key name from a given field name. The given field name may be a Pydantic Field alias, and the key name is intended to be used as a BaseModel class member variable name. Args: string (str): input field name \"\"\" # First replace any leading digits, because those are undesirable # in variable names. digitdict = { \"0\" : \"zero\" , \"1\" : \"one\" , \"2\" : \"two\" , \"3\" : \"three\" , \"4\" : \"four\" , \"5\" : \"five\" , \"6\" : \"six\" , \"7\" : \"seven\" , \"8\" : \"eight\" , \"9\" : \"nine\" , } m = re . search ( r \"^\\d+\" , string ) if m : digitstring = string [ 0 : m . end ()] for key , val in digitdict . items (): digitstring = digitstring . replace ( key , val ) string = digitstring + string [ m . end () :] # Next, replace spaces and hyphens in the potential variable name. return string . lower () . replace ( \" \" , \"_\" ) . replace ( \"-\" , \"\" )","title":"alias_generator()"},{"location":"reference/api/#hydrolib.core.basemodel.BaseModel.__init__","text":"Initialize a BaseModel with the provided data. Exceptions: Type Description ValidationError A validation error when the data is invalid. Source code in hydrolib/core/basemodel.py def __init__ ( self , ** data : Any ) -> None : \"\"\"Initialize a BaseModel with the provided data. Raises: ValidationError: A validation error when the data is invalid. \"\"\" try : super () . __init__ ( ** data ) except ValidationError as e : # Give a special message for faulty list input for re in e . raw_errors : if ( hasattr ( re , \"_loc\" ) and hasattr ( re . exc , \"msg_template\" ) and isinstance ( data . get ( to_key ( re . _loc )), list ) ): re . exc . msg_template += ( f \". The key { re . _loc } might be duplicated in the input file.\" ) # Update error with specific model location name identifier = self . _get_identifier ( data ) if identifier is None : raise e else : # If there is an identifier, include this in the ValidationError messages. raise ValidationError ([ ErrorWrapper ( e , loc = identifier )], self . __class__ )","title":"__init__()"},{"location":"reference/api/#hydrolib.core.basemodel.BaseModel.is_file_link","text":"Generic attribute for models backed by a file. Source code in hydrolib/core/basemodel.py def is_file_link ( self ) -> bool : \"\"\"Generic attribute for models backed by a file.\"\"\" return False","title":"is_file_link()"},{"location":"reference/api/#hydrolib.core.basemodel.BaseModel.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/basemodel.py def is_intermediate_link ( self ) -> bool : \"\"\"Generic attribute for models that have children fields that could contain files.\"\"\" return self . is_file_link ()","title":"is_intermediate_link()"},{"location":"reference/api/#hydrolib.core.basemodel.BaseModel.show_tree","text":"Recursive print function for showing a tree of a model. Source code in hydrolib/core/basemodel.py def show_tree ( self , indent = 0 ): \"\"\"Recursive print function for showing a tree of a model.\"\"\" angle = \"\u221f\" if indent > 0 else \"\" # Only print if we're backed by a file if self . is_file_link (): print ( \" \" * indent * 2 , angle , self ) # Otherwise we recurse through the fields of a model for _ , value in self : # Handle lists of items if not isinstance ( value , list ): value = [ value ] for v in value : if hasattr ( v , \"is_intermediate_link\" ) and v . is_intermediate_link (): # If the field is only an intermediate, print the name only if not v . is_file_link (): print ( \" \" * ( indent * 2 + 2 ), angle , v . __class__ . __name__ ) v . show_tree ( indent + 1 )","title":"show_tree()"},{"location":"reference/api/#hydrolib.core.basemodel.DiskOnlyFileModel","text":"DiskOnlyFileModel provides a stub implementation for file based models which are not explicitly implemented within hydrolib.core. It implements the FileModel with a void parser and serializer, and a save method which copies the file associated with the FileModel to a new location if it exists. We further explicitly assume that when the filepath is None, no file will be written. Actual file model implementations should not inherit from the DiskOnlyFileModel and instead inherit directly from FileModel.","title":"DiskOnlyFileModel"},{"location":"reference/api/#hydrolib.core.basemodel.DiskOnlyFileModel.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/basemodel.py def is_intermediate_link ( self ) -> bool : # If the filepath is not None, there is an underlying file, and as such we need # to traverse it. return self . filepath is not None","title":"is_intermediate_link()"},{"location":"reference/api/#hydrolib.core.basemodel.FileCasingResolver","text":"Class for resolving file path in a case-insensitive manner.","title":"FileCasingResolver"},{"location":"reference/api/#hydrolib.core.basemodel.FileCasingResolver.resolve","text":"Resolve the casing of a file path when the file does exist but not with the exact casing. Parameters: Name Type Description Default path Path The path of the file or directory for which the casing needs to be resolved. required Returns: Type Description Path The file path with the matched casing if a match exists; otherwise, the original file path. Exceptions: Type Description NotImplementedError When this function is called with an operating system other than Windows, Linux or MacOS. Source code in hydrolib/core/basemodel.py def resolve ( self , path : Path ) -> Path : \"\"\"Resolve the casing of a file path when the file does exist but not with the exact casing. Args: path (Path): The path of the file or directory for which the casing needs to be resolved. Returns: Path: The file path with the matched casing if a match exists; otherwise, the original file path. Raises: NotImplementedError: When this function is called with an operating system other than Windows, Linux or MacOS. \"\"\" operating_system = get_operating_system () if operating_system == OperatingSystem . WINDOWS : return self . _resolve_casing_windows ( path ) if operating_system == OperatingSystem . LINUX : return self . _resolve_casing_linux ( path ) if operating_system == OperatingSystem . MACOS : return self . _resolve_casing_macos ( path ) else : raise NotImplementedError ( f \"Path case resolving for operating system { operating_system } is not supported yet.\" )","title":"resolve()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext","text":"FileLoadContext provides the context necessary to resolve paths during the init of a FileModel, as well as ensure the relevant models are only read once.","title":"FileLoadContext"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.__init__","text":"Create a new empty FileLoadContext. Source code in hydrolib/core/basemodel.py def __init__ ( self ) -> None : \"\"\"Create a new empty FileLoadContext.\"\"\" self . _path_resolver = FilePathResolver () self . _cache = FileModelCache () self . _file_casing_resolver = FileCasingResolver () self . _file_path_style_converter = FilePathStyleConverter () self . _load_settings : Optional [ ModelLoadSettings ] = None","title":"__init__()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.cache_is_empty","text":"Whether or not the file model cache is empty. Returns: Type Description bool Whether or not the file model cache is empty. Source code in hydrolib/core/basemodel.py def cache_is_empty ( self ) -> bool : \"\"\"Whether or not the file model cache is empty. Returns: bool: Whether or not the file model cache is empty. \"\"\" return self . _cache . is_empty ()","title":"cache_is_empty()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.convert_path_style","text":"Resolve the file path by converting it from its own file path style to the path style for the current operating system. Parameters: Name Type Description Default file_path Path The file path to convert to the OS path style. required Returns: Type Description Path The resolved file path. Source code in hydrolib/core/basemodel.py def convert_path_style ( self , file_path : Path ) -> Path : \"\"\"Resolve the file path by converting it from its own file path style to the path style for the current operating system. Args: file_path (Path): The file path to convert to the OS path style. Returns: Path: The resolved file path. \"\"\" if file_path . is_absolute (): return file_path converted_file_path = self . _file_path_style_converter . convert_to_os_style ( file_path , self . load_settings . path_style ) return Path ( converted_file_path )","title":"convert_path_style()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.get_current_parent","text":"Get the current absolute path with which files are resolved. If the current mode is relative to the parent, the latest added parent is added. If the current mode is relative to an anchor path, the latest added anchor path is returned. Returns: Type Description Path The absolute path to the current parent. Source code in hydrolib/core/basemodel.py def get_current_parent ( self ) -> Path : \"\"\"Get the current absolute path with which files are resolved. If the current mode is relative to the parent, the latest added parent is added. If the current mode is relative to an anchor path, the latest added anchor path is returned. Returns: Path: The absolute path to the current parent. \"\"\" return self . _path_resolver . get_current_parent ()","title":"get_current_parent()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.initialize_load_settings","text":"Initialize the global model load setting. Can only be set once. Parameters: Name Type Description Default recurse bool Whether or not to recursively load the whole model. required resolve_casing bool Whether or not to resolve the file casing. required path_style PathStyle Which path style is used in the loaded files. required Source code in hydrolib/core/basemodel.py def initialize_load_settings ( self , recurse : bool , resolve_casing : bool , path_style : PathStyle ): \"\"\"Initialize the global model load setting. Can only be set once. Args: recurse (bool): Whether or not to recursively load the whole model. resolve_casing (bool): Whether or not to resolve the file casing. path_style (PathStyle): Which path style is used in the loaded files. \"\"\" if self . _load_settings is None : self . _load_settings = ModelLoadSettings ( recurse , resolve_casing , path_style )","title":"initialize_load_settings()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.load_settings","text":"Gets the model load settings. Exceptions: Type Description ValueError When the model load settings have not been initialized yet. Returns: Type Description ModelLoadSettings The model load settings.","title":"load_settings"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.pop_last_parent","text":"Pop the last added parent off this FileLoadContext. Source code in hydrolib/core/basemodel.py def pop_last_parent ( self ) -> None : \"\"\"Pop the last added parent off this FileLoadContext.\"\"\" self . _path_resolver . pop_last_parent ()","title":"pop_last_parent()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.push_new_parent","text":"Push a new parent_path with the given relative_mode on this FileLoadContext. Parameters: Name Type Description Default parent_path Path The parent path to be added to this FileLoadContext. required relative_mode ResolveRelativeMode The relative mode. required Source code in hydrolib/core/basemodel.py def push_new_parent ( self , parent_path : Path , relative_mode : ResolveRelativeMode ) -> None : \"\"\"Push a new parent_path with the given relative_mode on this FileLoadContext. Args: parent_path (Path): The parent path to be added to this FileLoadContext. relative_mode (ResolveRelativeMode): The relative mode. \"\"\" self . _path_resolver . push_new_parent ( parent_path , relative_mode )","title":"push_new_parent()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.register_model","text":"Associate the provided model with the provided path. Relative paths will be resolved based on the current state of the FileLoadContext. Parameters: Name Type Description Default path Path The relative path from which the model was loaded. required model FileModel The loaded model. required Source code in hydrolib/core/basemodel.py def register_model ( self , path : Path , model : \"FileModel\" ) -> None : \"\"\"Associate the provided model with the provided path. Relative paths will be resolved based on the current state of the FileLoadContext. Args: path (Path): The relative path from which the model was loaded. model (FileModel): The loaded model. \"\"\" absolute_path = self . _path_resolver . resolve ( path ) self . _cache . register_model ( absolute_path , model )","title":"register_model()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.resolve","text":"Resolve the provided path. If path is already absolute, it will be returned as is. Otherwise it will be resolved based on the current state of this FileLoadContext. Parameters: Name Type Description Default path Path The path to be resolved. required Returns: Type Description Path An absolute path resolved based on the current state. Source code in hydrolib/core/basemodel.py def resolve ( self , path : Path ) -> Path : \"\"\"Resolve the provided path. If path is already absolute, it will be returned as is. Otherwise it will be resolved based on the current state of this FileLoadContext. Args: path (Path): The path to be resolved. Returns: Path: An absolute path resolved based on the current state. \"\"\" return self . _path_resolver . resolve ( path )","title":"resolve()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.resolve_casing","text":"Resolve the file casing for the provided file path. Parameters: Name Type Description Default file_path Path The file path to resolve the casing for. required Returns: Type Description Path The resolved file path. Source code in hydrolib/core/basemodel.py def resolve_casing ( self , file_path : Path ) -> Path : \"\"\"Resolve the file casing for the provided file path. Args: file_path (Path): The file path to resolve the casing for. Returns: Path: The resolved file path. \"\"\" if self . load_settings . resolve_casing : return self . _file_casing_resolver . resolve ( file_path ) return file_path","title":"resolve_casing()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.retrieve_model","text":"Retrieve the model associated with the path. If no model has been associated with the provided path, or the path is None, then None will be returned. Relative paths will be resolved based on the current state of the FileLoadContext. Returns: Type Description [Optional[FileModel]] The file model associated with the provided path if it has been registered, else None. Source code in hydrolib/core/basemodel.py def retrieve_model ( self , path : Optional [ Path ]) -> Optional [ \"FileModel\" ]: \"\"\"Retrieve the model associated with the path. If no model has been associated with the provided path, or the path is None, then None will be returned. Relative paths will be resolved based on the current state of the FileLoadContext. Returns: [Optional[FileModel]]: The file model associated with the provided path if it has been registered, else None. \"\"\" if path is None : return None absolute_path = self . _path_resolver . resolve ( path ) return self . _cache . retrieve_model ( absolute_path )","title":"retrieve_model()"},{"location":"reference/api/#hydrolib.core.basemodel.FileModel","text":"Base class to represent models with a file representation. It therefore always has a filepath and if it is given on initilization, it will parse that file. The filepath can be relative, in which case the paths are expected to be resolved relative to some root model. If a path is absolute, this path will always be used, regardless of a root parent. When saving a model, if the current filepath is relative, the last resolved absolute path will be used. If the model has just been read, the This class extends the validate option of Pydantic, so when when a Path is given to a field with type FileModel , it doesn't error, but actually initializes the FileModel . Attributes: Name Type Description filepath Optional[Path] The path of this FileModel. This path can be either absolute or relative. If it is a relative path, it is assumed to be resolved from some root model. save_location Path A readonly property corresponding with the (current) save location of this FileModel. If read from a file or after saving recursively or after calling synchronize_filepath, this value will be updated to its new state. If made from memory and filepath is not set, it will correspond with cwd / filename.extension","title":"FileModel"},{"location":"reference/api/#hydrolib.core.basemodel.FileModel.__init__","text":"Create a new FileModel from the given filepath. If no filepath is provided, the model is initialized as an empty model with default values. If the filepath is provided, it is read from disk. Parameters: Name Type Description Default filepath Optional[PathOrStr] The file path. Defaults to None. None resolve_casing bool Whether or not to resolve the file name references so that they match the case with what is on disk. Defaults to False. False recurse bool Whether or not to recursively load the model. Defaults to True. True path_style Optional[str] Which path style is used in the loaded files. Defaults to the path style that matches the current operating system. Options: 'unix', 'windows'. None Exceptions: Type Description ValueError When an unsupported path style is passed. Source code in hydrolib/core/basemodel.py def __init__ ( self , filepath : Optional [ PathOrStr ] = None , resolve_casing : bool = False , recurse : bool = True , path_style : Optional [ str ] = None , * args , ** kwargs , ): \"\"\"Create a new FileModel from the given filepath. If no filepath is provided, the model is initialized as an empty model with default values. If the filepath is provided, it is read from disk. Args: filepath (Optional[PathOrStr], optional): The file path. Defaults to None. resolve_casing (bool, optional): Whether or not to resolve the file name references so that they match the case with what is on disk. Defaults to False. recurse (bool, optional): Whether or not to recursively load the model. Defaults to True. path_style (Optional[str], optional): Which path style is used in the loaded files. Defaults to the path style that matches the current operating system. Options: 'unix', 'windows'. Raises: ValueError: When an unsupported path style is passed. \"\"\" if not filepath : super () . __init__ ( * args , ** kwargs ) return filepath = FileModel . _change_to_path ( filepath ) path_style = path_style_validator . validate ( path_style ) with file_load_context () as context : context . initialize_load_settings ( recurse , resolve_casing , path_style ) filepath = context . convert_path_style ( filepath ) if not FileModel . _should_load_model ( context ): super () . __init__ ( * args , ** kwargs ) self . filepath = filepath return self . _absolute_anchor_path = context . get_current_parent () loading_path = context . resolve ( filepath ) loading_path = context . resolve_casing ( loading_path ) if context . load_settings . resolve_casing : filepath = self . _get_updated_file_path ( filepath , loading_path ) logger . info ( f \"Loading data from { filepath } \" ) data = self . _load ( loading_path ) context . register_model ( filepath , self ) data [ \"filepath\" ] = filepath kwargs . update ( data ) context . register_model ( filepath , self ) # Note: the relative mode needs to be obtained from the data directly # because self._relative_mode has not been resolved yet (this is done as # part of the __init__), however during the __init__ we need to already # have pushed the new parent. As such we cannot move this call later. relative_mode = self . _get_relative_mode_from_data ( data ) context . push_new_parent ( filepath . parent , relative_mode ) super () . __init__ ( * args , ** kwargs ) self . _post_init_load () context . pop_last_parent ()","title":"__init__()"},{"location":"reference/api/#hydrolib.core.basemodel.FileModel.__new__","text":"Create a new model. If the file at the provided file path was already parsed, this instance is returned. Parameters: Name Type Description Default filepath Optional[PathOrStr] The file path to the file. Defaults to None. None Returns: Type Description FileModel A file model. Source code in hydrolib/core/basemodel.py def __new__ ( cls , filepath : Optional [ PathOrStr ] = None , * args , ** kwargs ): \"\"\"Create a new model. If the file at the provided file path was already parsed, this instance is returned. Args: filepath (Optional[PathOrStr], optional): The file path to the file. Defaults to None. Returns: FileModel: A file model. \"\"\" filepath = FileModel . _change_to_path ( filepath ) with file_load_context () as context : if ( file_model := context . retrieve_model ( filepath )) is not None : return file_model else : return super () . __new__ ( cls )","title":"__new__()"},{"location":"reference/api/#hydrolib.core.basemodel.FileModel.__str__","text":"Return str(self). Source code in hydrolib/core/basemodel.py def __str__ ( self ) -> str : return str ( self . filepath if self . filepath else \"\" )","title":"__str__()"},{"location":"reference/api/#hydrolib.core.basemodel.FileModel.is_file_link","text":"Generic attribute for models backed by a file. Source code in hydrolib/core/basemodel.py def is_file_link ( self ) -> bool : return True","title":"is_file_link()"},{"location":"reference/api/#hydrolib.core.basemodel.FileModel.save","text":"Save the model to disk. If recurse is set to True, all of the child FileModels will be saved as well. Relative child models are stored relative to this Model, according to the model file hierarchy specified with the respective filepaths. Absolute paths will be written to their respective locations. Note that this will overwrite any existing files that are stored in this location. Note that if recurse is set to True, the save_location properties of the children are updated to their respective new locations. If filepath it is specified, the filepath of this FileModel is set to the specified path before the save operation is executed. If none is specified it will use the current filepath. If the used filepath is relative, it will be stored at the current save_location. If you only want to save a child model of some root model, it is recommended to first call synchronize_filepaths on the root model, to ensure the child model's save_location is correctly determined. Parameters: Name Type Description Default filepath Optional[Path] The file path at which this model is saved. If None is specified it defaults to the filepath currently stored in the filemodel. Defaults to None. None recurse bool Whether to save all children of this FileModel (when set to True), or only save this model (when set to False). Defaults to False. False path_style Optional[str] With which file path style to save the model. File references will be written with the specified path style. Defaults to the path style used by the current operating system. Options: 'unix', 'windows'. None Exceptions: Type Description ValueError When an unsupported path style is passed. Source code in hydrolib/core/basemodel.py def save ( self , filepath : Optional [ Path ] = None , recurse : bool = False , path_style : Optional [ str ] = None , ) -> None : \"\"\"Save the model to disk. If recurse is set to True, all of the child FileModels will be saved as well. Relative child models are stored relative to this Model, according to the model file hierarchy specified with the respective filepaths. Absolute paths will be written to their respective locations. Note that this will overwrite any existing files that are stored in this location. Note that if recurse is set to True, the save_location properties of the children are updated to their respective new locations. If filepath it is specified, the filepath of this FileModel is set to the specified path before the save operation is executed. If none is specified it will use the current filepath. If the used filepath is relative, it will be stored at the current save_location. If you only want to save a child model of some root model, it is recommended to first call synchronize_filepaths on the root model, to ensure the child model's save_location is correctly determined. Args: filepath (Optional[Path], optional): The file path at which this model is saved. If None is specified it defaults to the filepath currently stored in the filemodel. Defaults to None. recurse (bool, optional): Whether to save all children of this FileModel (when set to True), or only save this model (when set to False). Defaults to False. path_style (Optional[str], optional): With which file path style to save the model. File references will be written with the specified path style. Defaults to the path style used by the current operating system. Options: 'unix', 'windows'. Raises: ValueError: When an unsupported path style is passed. \"\"\" if filepath is not None : self . filepath = filepath path_style = path_style_validator . validate ( path_style ) save_settings = ModelSaveSettings ( path_style = path_style ) # Handle save with file_load_context () as context : context . push_new_parent ( self . _absolute_anchor_path , self . _relative_mode ) if recurse : self . _save_tree ( context , save_settings ) else : self . _save_instance ( save_settings )","title":"save()"},{"location":"reference/api/#hydrolib.core.basemodel.FileModel.save_location","text":"Get the current save location which will be used when calling save() This value can be None if the filepath is None and no name can be generated. Returns: Type Description Path The location at which this model will be saved.","title":"save_location"},{"location":"reference/api/#hydrolib.core.basemodel.FileModel.synchronize_filepaths","text":"Synchronize the save_location properties of all child models respective to this FileModel's save_location. Source code in hydrolib/core/basemodel.py def synchronize_filepaths ( self ) -> None : \"\"\"Synchronize the save_location properties of all child models respective to this FileModel's save_location. \"\"\" def sync_pre ( model : BaseModel , acc : FileLoadContext ) -> FileLoadContext : if isinstance ( model , FileModel ): acc . push_new_parent ( model . filepath . parent , model . _relative_mode ) # type: ignore[arg-type] return acc def sync_post ( model : BaseModel , acc : FileLoadContext ) -> FileLoadContext : if isinstance ( model , FileModel ): acc . pop_last_parent () model . _absolute_anchor_path = acc . get_current_parent () return acc traverser = ModelTreeTraverser [ FileLoadContext ]( should_traverse = _should_traverse , should_execute = _should_execute , pre_traverse_func = sync_pre , post_traverse_func = sync_post , ) with file_load_context () as context : context . push_new_parent ( self . _absolute_anchor_path , self . _relative_mode ) traverser . traverse ( self , context )","title":"synchronize_filepaths()"},{"location":"reference/api/#hydrolib.core.basemodel.FileModelCache","text":"FileModelCache provides a simple structure to register and retrieve FileModel objects.","title":"FileModelCache"},{"location":"reference/api/#hydrolib.core.basemodel.FileModelCache.__init__","text":"Create a new empty FileModelCache. Source code in hydrolib/core/basemodel.py def __init__ ( self ): \"\"\"Create a new empty FileModelCache.\"\"\" self . _cache_dict : Dict [ Path , \"FileModel\" ] = {}","title":"__init__()"},{"location":"reference/api/#hydrolib.core.basemodel.FileModelCache.is_empty","text":"Whether or not this file model cache is empty. Returns: Type Description bool Whether or not the cache is empty. Source code in hydrolib/core/basemodel.py def is_empty ( self ) -> bool : \"\"\"Whether or not this file model cache is empty. Returns: bool: Whether or not the cache is empty. \"\"\" return not any ( self . _cache_dict )","title":"is_empty()"},{"location":"reference/api/#hydrolib.core.basemodel.FileModelCache.register_model","text":"Register the model with the specified path in this FileModelCache. Parameters: Name Type Description Default path Path The path to associate the model with. required model FileModel The model to be associated with the path. required Source code in hydrolib/core/basemodel.py def register_model ( self , path : Path , model : \"FileModel\" ) -> None : \"\"\"Register the model with the specified path in this FileModelCache. Args: path (Path): The path to associate the model with. model (FileModel): The model to be associated with the path. \"\"\" self . _cache_dict [ path ] = model","title":"register_model()"},{"location":"reference/api/#hydrolib.core.basemodel.FileModelCache.retrieve_model","text":"Retrieve the model associated with the (absolute) path if it has been registered before, otherwise return None. Returns: Type Description [Optional[FileModel]] The FileModel associated with the Path if it has been registered before, otherwise None. Source code in hydrolib/core/basemodel.py def retrieve_model ( self , path : Path ) -> Optional [ \"FileModel\" ]: \"\"\"Retrieve the model associated with the (absolute) path if it has been registered before, otherwise return None. Returns: [Optional[FileModel]]: The FileModel associated with the Path if it has been registered before, otherwise None. \"\"\" return self . _cache_dict . get ( path , None )","title":"retrieve_model()"},{"location":"reference/api/#hydrolib.core.basemodel.FilePathResolver","text":"FilePathResolver is responsible for resolving relative paths. The current state to which paths are resolved can be altered by pushing a new parent path to the FilePathResolver, or removing the latest added parent path from the FilePathResolver","title":"FilePathResolver"},{"location":"reference/api/#hydrolib.core.basemodel.FilePathResolver.__init__","text":"Create a new empty FilePathResolver. Source code in hydrolib/core/basemodel.py def __init__ ( self ) -> None : \"\"\"Create a new empty FilePathResolver.\"\"\" self . _anchors : List [ Path ] = [] self . _parents : List [ Tuple [ Path , ResolveRelativeMode ]] = []","title":"__init__()"},{"location":"reference/api/#hydrolib.core.basemodel.FilePathResolver.get_current_parent","text":"Get the current absolute path with which files are resolved. If the current mode is relative to the parent, the latest added parent is added. If the current mode is relative to an anchor path, the latest added anchor path is returned. Returns: Type Description Path The absolute path to the current parent. Source code in hydrolib/core/basemodel.py def get_current_parent ( self ) -> Path : \"\"\"Get the current absolute path with which files are resolved. If the current mode is relative to the parent, the latest added parent is added. If the current mode is relative to an anchor path, the latest added anchor path is returned. Returns: Path: The absolute path to the current parent. \"\"\" if self . _anchor : return self . _anchor return self . _direct_parent","title":"get_current_parent()"},{"location":"reference/api/#hydrolib.core.basemodel.FilePathResolver.pop_last_parent","text":"Pop the last added parent from this FilePathResolver If there are currently no parents defined, nothing will happen. Source code in hydrolib/core/basemodel.py def pop_last_parent ( self ) -> None : \"\"\"Pop the last added parent from this FilePathResolver If there are currently no parents defined, nothing will happen. \"\"\" if not self . _parents : return _ , relative_mode = self . _parents . pop () if relative_mode == ResolveRelativeMode . ToAnchor : self . _anchors . pop ()","title":"pop_last_parent()"},{"location":"reference/api/#hydrolib.core.basemodel.FilePathResolver.push_new_parent","text":"Push a new parent_path with the given relative_mode to this FilePathResolver. Relative paths added to this FilePathResolver will be resolved with respect to the current state, i.e. similar to FilePathResolver.resolve. Parameters: Name Type Description Default parent_path Path The parent path required relative_mode ResolveRelativeMode The relative mode used to resolve. required Source code in hydrolib/core/basemodel.py def push_new_parent ( self , parent_path : Path , relative_mode : ResolveRelativeMode ) -> None : \"\"\"Push a new parent_path with the given relative_mode to this FilePathResolver. Relative paths added to this FilePathResolver will be resolved with respect to the current state, i.e. similar to FilePathResolver.resolve. Args: parent_path (Path): The parent path relative_mode (ResolveRelativeMode): The relative mode used to resolve. \"\"\" absolute_parent_path = self . resolve ( parent_path ) if relative_mode == ResolveRelativeMode . ToAnchor : self . _anchors . append ( absolute_parent_path ) self . _parents . append (( absolute_parent_path , relative_mode ))","title":"push_new_parent()"},{"location":"reference/api/#hydrolib.core.basemodel.FilePathResolver.resolve","text":"Resolve the provided path to an absolute path given the current state. If the provided path is already absolute, it will be returned as is. Parameters: Name Type Description Default path Path The path to resolve required Returns: Type Description Path An absolute path resolved given the current state. Source code in hydrolib/core/basemodel.py def resolve ( self , path : Path ) -> Path : \"\"\"Resolve the provided path to an absolute path given the current state. If the provided path is already absolute, it will be returned as is. Args: path (Path): The path to resolve Returns: Path: An absolute path resolved given the current state. \"\"\" if path . is_absolute (): return path parent = self . get_current_parent () return ( parent / path ) . resolve ()","title":"resolve()"},{"location":"reference/api/#hydrolib.core.basemodel.ModelLoadSettings","text":"A class that holds the global settings for model loading.","title":"ModelLoadSettings"},{"location":"reference/api/#hydrolib.core.basemodel.ModelLoadSettings.__init__","text":"Initializes a new instance of the ModelLoadSettings class. Parameters: Name Type Description Default recurse bool Whether or not to recursively load the whole model. required resolve_casing bool Whether or not to resolve the file casing. required path_style PathStyle Which path style is used in the loaded files. required Source code in hydrolib/core/basemodel.py def __init__ ( self , recurse : bool , resolve_casing : bool , path_style : PathStyle ) -> None : \"\"\"Initializes a new instance of the ModelLoadSettings class. Args: recurse (bool): Whether or not to recursively load the whole model. resolve_casing (bool): Whether or not to resolve the file casing. path_style (PathStyle): Which path style is used in the loaded files. \"\"\" self . _recurse = recurse self . _resolve_casing = resolve_casing self . _path_style = path_style","title":"__init__()"},{"location":"reference/api/#hydrolib.core.basemodel.ModelLoadSettings.path_style","text":"Gets the path style setting. Returns: Type Description PathStyle Which path style is used in the loaded files.","title":"path_style"},{"location":"reference/api/#hydrolib.core.basemodel.ModelLoadSettings.recurse","text":"Gets the recurse setting. Returns: Type Description bool Whether or not to recursively load the whole model.","title":"recurse"},{"location":"reference/api/#hydrolib.core.basemodel.ModelLoadSettings.resolve_casing","text":"Gets the resolve casing setting. Returns: Type Description bool Whether or not to resolve the file casing.","title":"resolve_casing"},{"location":"reference/api/#hydrolib.core.basemodel.ModelSaveSettings","text":"A class that holds the global settings for model saving.","title":"ModelSaveSettings"},{"location":"reference/api/#hydrolib.core.basemodel.ModelSaveSettings.__init__","text":"Initializes a new instance of the ModelSaveSettings class. Parameters: Name Type Description Default path_style Optional[PathStyle] Which file path style to use when saving the model. Defaults to the path style that matches the current operating system. None Source code in hydrolib/core/basemodel.py def __init__ ( self , path_style : Optional [ PathStyle ] = None ) -> None : \"\"\"Initializes a new instance of the ModelSaveSettings class. Args: path_style (Optional[PathStyle], optional): Which file path style to use when saving the model. Defaults to the path style that matches the current operating system. \"\"\" if path_style is None : path_style = self . _os_path_style self . _path_style = path_style","title":"__init__()"},{"location":"reference/api/#hydrolib.core.basemodel.ModelSaveSettings.path_style","text":"Gets the path style setting. Returns: Type Description PathStyle Which path style is used to save the files.","title":"path_style"},{"location":"reference/api/#hydrolib.core.basemodel.ModelTreeTraverser","text":"ModelTreeTraverser is responsible for traversing a ModelTree using the provided functions. The ModelTreeTraverser will only traverse BaseModel and derived objects. Type parameter TAcc defines the type of Accumulator to be used.","title":"ModelTreeTraverser"},{"location":"reference/api/#hydrolib.core.basemodel.ModelTreeTraverser.__init__","text":"Create a new ModelTreeTraverser with the given functions. If a predicate it is not defined, it is assumed to always be true, i.e. we will always traverse to the next node, or always execute the traverse functions. If a traverse function is not defined, it will be skipped. The traverse functions share an accumulator, i.e. the accumulator argument is passed through all evaluated traverse functions. It is expected that the traverse function return the (potentially) changed accumulator. Parameters: Name Type Description Default should_traverse Optional[Callable[[BaseModel, TAcc], bool]] Function to evaluate whether to traverse to the provided BaseModel. Defaults to None. None should_execute Optional[Callable[[BaseModel, TAcc], bool]] Function to evaluate whether to execute the traverse functions for the provided BaseModel. Defaults to None. None pre_traverse_func Callable[[BaseModel, TAcc], TAcc] Traverse function executed before we traverse into the next BaseModel, i.e. top-down traversal. Defaults to None. None post_traverse_func Callable[[BaseModel, TAcc], TAcc] Traverse function executed after we traverse into the next BaseModel, i.e. bottom-up traversal. Defaults to None. None Source code in hydrolib/core/basemodel.py def __init__ ( self , should_traverse : Optional [ Callable [[ BaseModel , TAcc ], bool ]] = None , should_execute : Optional [ Callable [[ BaseModel , TAcc ], bool ]] = None , pre_traverse_func : Optional [ Callable [[ BaseModel , TAcc ], TAcc ]] = None , post_traverse_func : Optional [ Callable [[ BaseModel , TAcc ], TAcc ]] = None , ): \"\"\"Create a new ModelTreeTraverser with the given functions. If a predicate it is not defined, it is assumed to always be true, i.e. we will always traverse to the next node, or always execute the traverse functions. If a traverse function is not defined, it will be skipped. The traverse functions share an accumulator, i.e. the accumulator argument is passed through all evaluated traverse functions. It is expected that the traverse function return the (potentially) changed accumulator. Args: should_traverse (Optional[Callable[[BaseModel, TAcc], bool]], optional): Function to evaluate whether to traverse to the provided BaseModel. Defaults to None. should_execute (Optional[Callable[[BaseModel, TAcc], bool]], optional): Function to evaluate whether to execute the traverse functions for the provided BaseModel. Defaults to None. pre_traverse_func (Callable[[BaseModel, TAcc], TAcc], optional): Traverse function executed before we traverse into the next BaseModel, i.e. top-down traversal. Defaults to None. post_traverse_func (Callable[[BaseModel, TAcc], TAcc], optional): Traverse function executed after we traverse into the next BaseModel, i.e. bottom-up traversal. Defaults to None. \"\"\" self . _should_traverse_func = should_traverse self . _should_execute_func = should_execute self . _pre_traverse_func = pre_traverse_func self . _post_traverse_func = post_traverse_func","title":"__init__()"},{"location":"reference/api/#hydrolib.core.basemodel.ModelTreeTraverser.traverse","text":"Traverse the model tree of BaseModels including the model as the root, with the provided state of the acc and return the final accumulator. The actual executed functions as well as the predicates defining whether these functions should be executed for this model as well as whether child BaseModel objects should be traversed are provided in the constructor of the ModelTreeTraverser. The final accumulator is returned. Parameters: Name Type Description Default model BaseModel The root model in which the traversal of the model tree starts. required acc TAcc The current accumulator. required Returns: Type Description TAcc The accumulator after the traversal of the model tree. Source code in hydrolib/core/basemodel.py def traverse ( self , model : BaseModel , acc : TAcc ) -> TAcc : \"\"\"Traverse the model tree of BaseModels including the model as the root, with the provided state of the acc and return the final accumulator. The actual executed functions as well as the predicates defining whether these functions should be executed for this model as well as whether child BaseModel objects should be traversed are provided in the constructor of the ModelTreeTraverser. The final accumulator is returned. Args: model (BaseModel): The root model in which the traversal of the model tree starts. acc (TAcc): The current accumulator. Returns: TAcc: The accumulator after the traversal of the model tree. \"\"\" if self . _should_execute_pre ( model , acc ): acc = self . _pre_traverse_func ( model , acc ) # type: ignore[arg-type] for _ , value in model : if not isinstance ( value , list ): value = [ value ] for v in value : if self . _should_traverse ( v , acc ): acc = self . traverse ( v , acc ) if self . _should_execute_post ( model , acc ): acc = self . _post_traverse_func ( model , acc ) # type: ignore[arg-type] return acc","title":"traverse()"},{"location":"reference/api/#hydrolib.core.basemodel.ParsableFileModel","text":"ParsableFileModel defines a FileModel which can be parsed and serialized with a serializer . Each ParsableFileModel has a default _filename and _ext, which are used to generate the file name of any instance where the filepath is not (yet) set. Children of the ParsableFileModel are expected to implement a serializer function which takes a Path and Dict and writes the ParsableFileModel to disk, and a parser function which takes a Path and outputs a Dict. If more complicated solutions are required, a ParsableFileModel child can also opt to overwrite the _serialize and _parse methods, to skip the _get_serializer and _get_parser methods respectively.","title":"ParsableFileModel"},{"location":"reference/api/#hydrolib.core.basemodel.ParsableFileModel.dict","text":"Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/basemodel.py def dict ( self , * args , ** kwargs ): kwargs [ \"exclude\" ] = self . _exclude_fields () return super () . dict ( * args , ** kwargs )","title":"dict()"},{"location":"reference/api/#hydrolib.core.basemodel.PathStyleValidator","text":"Class to take care of path style validation.","title":"PathStyleValidator"},{"location":"reference/api/#hydrolib.core.basemodel.PathStyleValidator.validate","text":"Validates the path style as string on whether it is a supported path style. If it is a valid path style the path style enum value will be return as a result. Parameters: Name Type Description Default path_style Optional[str] The path style as string value. required Returns: Type Description PathStyle The converted PathStyle object. Exceptions: Type Description ValueError When an unsupported path style is passed. Source code in hydrolib/core/basemodel.py def validate ( self , path_style : Optional [ str ]) -> PathStyle : \"\"\"Validates the path style as string on whether it is a supported path style. If it is a valid path style the path style enum value will be return as a result. Args: path_style (Optional[str]): The path style as string value. Returns: PathStyle: The converted PathStyle object. Raises: ValueError: When an unsupported path style is passed. \"\"\" if path_style is None : return self . _os_path_style supported_path_styles = list ( PathStyle ) if path_style in supported_path_styles : return PathStyle ( path_style ) supported_path_style_str = \", \" . join (([ x . value for x in supported_path_styles ])) raise ValueError ( f \"Path style ' { path_style } ' not supported. Supported path styles: { supported_path_style_str } \" )","title":"validate()"},{"location":"reference/api/#hydrolib.core.basemodel.ResolveRelativeMode","text":"ResolveRelativeMode defines the possible resolve modes used within the FilePathResolver. It determines how the relative paths to child models within some FileModel should be interpreted. By default it should be relative to the parent model, i.e. the model in which the mode is defined. However there exist some exceptions, where the relative paths should be evaluated relative to some other folder, regardless of the current parent location. Options Toparent Relative paths should be resolved relative to their direct parent model. Toanchor All relative paths should be resolved relative to the specified regardless of subsequent parent model locations.","title":"ResolveRelativeMode"},{"location":"reference/api/#hydrolib.core.basemodel.SerializerConfig","text":"Class that holds the configuration settings for serialization.","title":"SerializerConfig"},{"location":"reference/api/#hydrolib.core.basemodel.file_load_context","text":"Provide a FileLoadingContext. If none has been created in the context of this call stack yet, a new one will be created, which will be maintained until it goes out of scope. Yields [FileLoadContext]: The file load context. Source code in hydrolib/core/basemodel.py @contextmanager def file_load_context (): \"\"\"Provide a FileLoadingContext. If none has been created in the context of this call stack yet, a new one will be created, which will be maintained until it goes out of scope. Yields: [FileLoadContext]: The file load context. \"\"\" file_loading_context = context_file_loading . get ( None ) context_reset_token = None if not file_loading_context : file_loading_context = FileLoadContext () context_reset_token = context_file_loading . set ( file_loading_context ) try : yield file_loading_context finally : if context_reset_token is not None : context_file_loading . reset ( context_reset_token )","title":"file_load_context()"},{"location":"reference/api/#hydrolib.core.basemodel.validator_set_default_disk_only_file_model_when_none","text":"Validator to ensure a default empty DiskOnlyFileModel is created when the corresponding field is initialized with None. Returns: Type Description classmethod Validator to adjust None values to empty DiskOnlyFileModel objects Source code in hydrolib/core/basemodel.py def validator_set_default_disk_only_file_model_when_none () -> classmethod : \"\"\"Validator to ensure a default empty DiskOnlyFileModel is created when the corresponding field is initialized with None. Returns: classmethod: Validator to adjust None values to empty DiskOnlyFileModel objects \"\"\" def adjust_none ( v : Any , field : ModelField ) -> Any : if field . type_ is DiskOnlyFileModel and v is None : return { \"filepath\" : None } return v return validator ( \"*\" , allow_reuse = True , pre = True )( adjust_none )","title":"validator_set_default_disk_only_file_model_when_none()"},{"location":"reference/crosssection/","text":"Cross section files \u00b6 The crosssection module provides the specific logic for accessing cross section files (location and definition) for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. The cross section files are represented by the classes below. Model \u00b6 CircleCrsDef ( CrossSectionDefinition ) pydantic-model \u00b6 Crosssection definition with type=circle , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the circle input as described in UM Sec.C.16.1.1 . CrossDefGeneral ( INIGeneral ) pydantic-model \u00b6 The crosssection definition file's [General] section with file meta data. CrossDefModel ( INIModel ) pydantic-model \u00b6 The overall crosssection definition model that contains the contents of one crossdef file. This model is typically referenced under a FMModel .geometry.crossdeffile . Attributes: Name Type Description general CrossdefGeneral [General] block with file metadata. definition List[CrossSectionDefinition] List of [Definition] blocks for all cross sections. CrossLocGeneral ( INIGeneral ) pydantic-model \u00b6 The crosssection location file's [General] section with file meta data. CrossLocModel ( INIModel ) pydantic-model \u00b6 The overall crosssection location model that contains the contents of one crossloc file. This model is typically referenced under a FMModel .geometry.crosslocfile . Attributes: Name Type Description general CrossLocGeneral [General] block with file metadata. crosssection List[CrossSection] List of [CrossSection] blocks for all cross section locations. CrossSection ( INIBasedModel ) pydantic-model \u00b6 A [CrossSection] block for use inside a crosssection location file, i.e., a CrossLocModel . Attributes: Name Type Description id str Unique cross-section location id. branchid str Branch on which the cross section is located. chainage str Chainage on the branch (m). x str x-coordinate of the location of the cross section. y str y-coordinate of the location of the cross section. shift float Vertical shift of the cross section definition [m]. Defined positive upwards. definitionid str Id of cross section definition. validate_that_location_specification_is_correct ( values : Dict ) -> Dict classmethod \u00b6 Validates that the correct location specification is given. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def validate_that_location_specification_is_correct ( cls , values : Dict ) -> Dict : \"\"\"Validates that the correct location specification is given.\"\"\" return validate_location_specification ( values , config = LocationValidationConfiguration ( validate_node = False , validate_num_coordinates = False ), fields = LocationValidationFieldNames ( x_coordinates = \"x\" , y_coordinates = \"y\" ), ) CrossSectionDefinition ( INIBasedModel ) pydantic-model \u00b6 A [Definition] block for use inside a crosssection definition file, i.e., a CrossDefModel . This class is intended as an abstract class: various subclasses should define they actual types of crosssection definitions. validate ( v ) classmethod \u00b6 Try to initialize subclass based on the type field. This field is compared to each type field of the derived models of CrossSectionDefinition . The derived model with an equal crosssection definition type will be initialized. Exceptions: Type Description ValueError When the given type is not a known crosssection definition type. Source code in hydrolib/core/dflowfm/crosssection/models.py @classmethod def validate ( cls , v ): \"\"\"Try to initialize subclass based on the `type` field. This field is compared to each `type` field of the derived models of `CrossSectionDefinition`. The derived model with an equal crosssection definition type will be initialized. Raises: ValueError: When the given type is not a known crosssection definition type. \"\"\" # should be replaced by discriminated unions once merged # https://github.com/samuelcolvin/pydantic/pull/2336 if isinstance ( v , dict ): for c in cls . __subclasses__ (): if ( c . __fields__ . get ( \"type\" ) . default . lower () == v . get ( \"type\" , \"\" ) . lower () ): v = c ( ** v ) break else : raise ValueError ( f \"Type of { cls . __name__ } with id= { v . get ( 'id' , '' ) } and type= { v . get ( 'type' , '' ) } is not recognized.\" ) return super () . validate ( v ) RectangleCrsDef ( CrossSectionDefinition ) pydantic-model \u00b6 Crosssection definition with type=rectangle , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the rectangle input as described in UM Sec.C.16.1.2 . XYZCrsDef ( YZCrsDef , CrossSectionDefinition ) pydantic-model \u00b6 Crosssection definition with type=xyz , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the xyz input as described in UM Sec.C.16.1.5 . This class extends the YZCrsDef class with x-coordinates and an optional branchId field. Most other attributes are inherited, but the coordcount is overridden under the Pydantic alias \"xyzCount\". Attributes: Name Type Description yzcount Optional[int] dummy attribute that should not be set nor used. Only present to mask the inherited attribute from parent class YZCrsDef. xyzcount int Number of XYZ-coordinates. Always use this instead of yzcount. check_list_lengths_coordinates ( values ) classmethod \u00b6 Validates that the length of the xcoordinates, ycoordinates and zcoordinates field are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths_coordinates ( cls , values ): \"\"\"Validates that the length of the xcoordinates, ycoordinates and zcoordinates field are as expected.\"\"\" return validate_correct_length ( values , \"xcoordinates\" , \"ycoordinates\" , \"zcoordinates\" , length_name = \"xyzcount\" , ) validate_xyzcount_without_yzcount ( field_value : int , values : dict ) -> int classmethod \u00b6 Validates whether this XYZCrsDef does have attribute xyzcount, but not the parent class's yzcount. Parameters: Name Type Description Default field_value Optional[Path] Value given for xyzcount. required values dict Dictionary of values already validated. required Exceptions: Type Description ValueError When yzcount is present. Returns: Type Description int The value given for xyzcount. Source code in hydrolib/core/dflowfm/crosssection/models.py @validator ( \"xyzcount\" ) @classmethod def validate_xyzcount_without_yzcount ( cls , field_value : int , values : dict ) -> int : \"\"\" Validates whether this XYZCrsDef does have attribute xyzcount, but not the parent class's yzcount. Args: field_value (Optional[Path]): Value given for xyzcount. values (dict): Dictionary of values already validated. Raises: ValueError: When yzcount is present. Returns: int: The value given for xyzcount. \"\"\" # Retrieve the algorithm value (if not found use 0). yzcount_value = values . get ( \"yzcount\" ) if field_value is not None and yzcount_value is not None : # yzcount should not be set, when xyzcount is set. raise ValueError ( f \"xyz cross section definition should not contain field yzCount (rather: xyzCount), current value: { yzcount_value } .\" ) return field_value YZCrsDef ( CrossSectionDefinition ) pydantic-model \u00b6 Crosssection definition with type=yz , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the yz input as described in UM Sec.C.16.1.6 . check_list_length_frictionpositions ( values ) classmethod \u00b6 Validates that the length of the frictionpositions field is as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_length_frictionpositions ( cls , values ): \"\"\"Validates that the length of the frictionpositions field is as expected.\"\"\" return validate_correct_length ( values , \"frictionpositions\" , length_name = \"sectioncount\" , length_incr = 1 , # 1 extra for frictionpositions ) check_list_lengths_coordinates ( values ) classmethod \u00b6 Validates that the length of the ycoordinates and zcoordinates fields are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths_coordinates ( cls , values ): \"\"\"Validates that the length of the ycoordinates and zcoordinates fields are as expected.\"\"\" return validate_correct_length ( values , \"ycoordinates\" , \"zcoordinates\" , length_name = \"yzcount\" , ) check_list_lengths_friction ( values ) classmethod \u00b6 Validates that the length of the frictionids, frictiontypes and frictionvalues field are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths_friction ( cls , values ): \"\"\"Validates that the length of the frictionids, frictiontypes and frictionvalues field are as expected.\"\"\" return validate_correct_length ( values , \"frictionids\" , \"frictiontypes\" , \"frictionvalues\" , length_name = \"sectioncount\" , ) ZWCrsDef ( CrossSectionDefinition ) pydantic-model \u00b6 Crosssection definition with type=zw , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the zw input as described in UM Sec.C.16.1.4 . check_list_lengths ( values ) classmethod \u00b6 Validates that the length of the levels, flowwidths and totalwidths fields are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths ( cls , values ): \"\"\"Validates that the length of the levels, flowwidths and totalwidths fields are as expected.\"\"\" return validate_correct_length ( values , \"levels\" , \"flowwidths\" , \"totalwidths\" , length_name = \"numlevels\" , ) ZWRiverCrsDef ( CrossSectionDefinition ) pydantic-model \u00b6 Crosssection definition with type=zwRiver , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the zwRiver input as described in UM Sec.C.16.1.3 . check_list_lengths ( values ) classmethod \u00b6 Validates that the length of the levels, flowwidths and totalwidths fields are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths ( cls , values ): \"\"\"Validates that the length of the levels, flowwidths and totalwidths fields are as expected.\"\"\" return validate_correct_length ( values , \"levels\" , \"flowwidths\" , \"totalwidths\" , length_name = \"numlevels\" , )","title":"Cross section files"},{"location":"reference/crosssection/#cross-section-files","text":"The crosssection module provides the specific logic for accessing cross section files (location and definition) for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. The cross section files are represented by the classes below.","title":"Cross section files"},{"location":"reference/crosssection/#model","text":"","title":"Model"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.CircleCrsDef","text":"Crosssection definition with type=circle , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the circle input as described in UM Sec.C.16.1.1 .","title":"CircleCrsDef"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.CrossDefGeneral","text":"The crosssection definition file's [General] section with file meta data.","title":"CrossDefGeneral"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.CrossDefModel","text":"The overall crosssection definition model that contains the contents of one crossdef file. This model is typically referenced under a FMModel .geometry.crossdeffile . Attributes: Name Type Description general CrossdefGeneral [General] block with file metadata. definition List[CrossSectionDefinition] List of [Definition] blocks for all cross sections.","title":"CrossDefModel"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.CrossLocGeneral","text":"The crosssection location file's [General] section with file meta data.","title":"CrossLocGeneral"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.CrossLocModel","text":"The overall crosssection location model that contains the contents of one crossloc file. This model is typically referenced under a FMModel .geometry.crosslocfile . Attributes: Name Type Description general CrossLocGeneral [General] block with file metadata. crosssection List[CrossSection] List of [CrossSection] blocks for all cross section locations.","title":"CrossLocModel"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.CrossSection","text":"A [CrossSection] block for use inside a crosssection location file, i.e., a CrossLocModel . Attributes: Name Type Description id str Unique cross-section location id. branchid str Branch on which the cross section is located. chainage str Chainage on the branch (m). x str x-coordinate of the location of the cross section. y str y-coordinate of the location of the cross section. shift float Vertical shift of the cross section definition [m]. Defined positive upwards. definitionid str Id of cross section definition.","title":"CrossSection"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.CrossSection.validate_that_location_specification_is_correct","text":"Validates that the correct location specification is given. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def validate_that_location_specification_is_correct ( cls , values : Dict ) -> Dict : \"\"\"Validates that the correct location specification is given.\"\"\" return validate_location_specification ( values , config = LocationValidationConfiguration ( validate_node = False , validate_num_coordinates = False ), fields = LocationValidationFieldNames ( x_coordinates = \"x\" , y_coordinates = \"y\" ), )","title":"validate_that_location_specification_is_correct()"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.CrossSectionDefinition","text":"A [Definition] block for use inside a crosssection definition file, i.e., a CrossDefModel . This class is intended as an abstract class: various subclasses should define they actual types of crosssection definitions.","title":"CrossSectionDefinition"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.CrossSectionDefinition.validate","text":"Try to initialize subclass based on the type field. This field is compared to each type field of the derived models of CrossSectionDefinition . The derived model with an equal crosssection definition type will be initialized. Exceptions: Type Description ValueError When the given type is not a known crosssection definition type. Source code in hydrolib/core/dflowfm/crosssection/models.py @classmethod def validate ( cls , v ): \"\"\"Try to initialize subclass based on the `type` field. This field is compared to each `type` field of the derived models of `CrossSectionDefinition`. The derived model with an equal crosssection definition type will be initialized. Raises: ValueError: When the given type is not a known crosssection definition type. \"\"\" # should be replaced by discriminated unions once merged # https://github.com/samuelcolvin/pydantic/pull/2336 if isinstance ( v , dict ): for c in cls . __subclasses__ (): if ( c . __fields__ . get ( \"type\" ) . default . lower () == v . get ( \"type\" , \"\" ) . lower () ): v = c ( ** v ) break else : raise ValueError ( f \"Type of { cls . __name__ } with id= { v . get ( 'id' , '' ) } and type= { v . get ( 'type' , '' ) } is not recognized.\" ) return super () . validate ( v )","title":"validate()"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.RectangleCrsDef","text":"Crosssection definition with type=rectangle , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the rectangle input as described in UM Sec.C.16.1.2 .","title":"RectangleCrsDef"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.XYZCrsDef","text":"Crosssection definition with type=xyz , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the xyz input as described in UM Sec.C.16.1.5 . This class extends the YZCrsDef class with x-coordinates and an optional branchId field. Most other attributes are inherited, but the coordcount is overridden under the Pydantic alias \"xyzCount\". Attributes: Name Type Description yzcount Optional[int] dummy attribute that should not be set nor used. Only present to mask the inherited attribute from parent class YZCrsDef. xyzcount int Number of XYZ-coordinates. Always use this instead of yzcount.","title":"XYZCrsDef"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.XYZCrsDef.check_list_lengths_coordinates","text":"Validates that the length of the xcoordinates, ycoordinates and zcoordinates field are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths_coordinates ( cls , values ): \"\"\"Validates that the length of the xcoordinates, ycoordinates and zcoordinates field are as expected.\"\"\" return validate_correct_length ( values , \"xcoordinates\" , \"ycoordinates\" , \"zcoordinates\" , length_name = \"xyzcount\" , )","title":"check_list_lengths_coordinates()"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.XYZCrsDef.validate_xyzcount_without_yzcount","text":"Validates whether this XYZCrsDef does have attribute xyzcount, but not the parent class's yzcount. Parameters: Name Type Description Default field_value Optional[Path] Value given for xyzcount. required values dict Dictionary of values already validated. required Exceptions: Type Description ValueError When yzcount is present. Returns: Type Description int The value given for xyzcount. Source code in hydrolib/core/dflowfm/crosssection/models.py @validator ( \"xyzcount\" ) @classmethod def validate_xyzcount_without_yzcount ( cls , field_value : int , values : dict ) -> int : \"\"\" Validates whether this XYZCrsDef does have attribute xyzcount, but not the parent class's yzcount. Args: field_value (Optional[Path]): Value given for xyzcount. values (dict): Dictionary of values already validated. Raises: ValueError: When yzcount is present. Returns: int: The value given for xyzcount. \"\"\" # Retrieve the algorithm value (if not found use 0). yzcount_value = values . get ( \"yzcount\" ) if field_value is not None and yzcount_value is not None : # yzcount should not be set, when xyzcount is set. raise ValueError ( f \"xyz cross section definition should not contain field yzCount (rather: xyzCount), current value: { yzcount_value } .\" ) return field_value","title":"validate_xyzcount_without_yzcount()"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.YZCrsDef","text":"Crosssection definition with type=yz , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the yz input as described in UM Sec.C.16.1.6 .","title":"YZCrsDef"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.YZCrsDef.check_list_length_frictionpositions","text":"Validates that the length of the frictionpositions field is as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_length_frictionpositions ( cls , values ): \"\"\"Validates that the length of the frictionpositions field is as expected.\"\"\" return validate_correct_length ( values , \"frictionpositions\" , length_name = \"sectioncount\" , length_incr = 1 , # 1 extra for frictionpositions )","title":"check_list_length_frictionpositions()"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.YZCrsDef.check_list_lengths_coordinates","text":"Validates that the length of the ycoordinates and zcoordinates fields are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths_coordinates ( cls , values ): \"\"\"Validates that the length of the ycoordinates and zcoordinates fields are as expected.\"\"\" return validate_correct_length ( values , \"ycoordinates\" , \"zcoordinates\" , length_name = \"yzcount\" , )","title":"check_list_lengths_coordinates()"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.YZCrsDef.check_list_lengths_friction","text":"Validates that the length of the frictionids, frictiontypes and frictionvalues field are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths_friction ( cls , values ): \"\"\"Validates that the length of the frictionids, frictiontypes and frictionvalues field are as expected.\"\"\" return validate_correct_length ( values , \"frictionids\" , \"frictiontypes\" , \"frictionvalues\" , length_name = \"sectioncount\" , )","title":"check_list_lengths_friction()"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.ZWCrsDef","text":"Crosssection definition with type=zw , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the zw input as described in UM Sec.C.16.1.4 .","title":"ZWCrsDef"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.ZWCrsDef.check_list_lengths","text":"Validates that the length of the levels, flowwidths and totalwidths fields are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths ( cls , values ): \"\"\"Validates that the length of the levels, flowwidths and totalwidths fields are as expected.\"\"\" return validate_correct_length ( values , \"levels\" , \"flowwidths\" , \"totalwidths\" , length_name = \"numlevels\" , )","title":"check_list_lengths()"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.ZWRiverCrsDef","text":"Crosssection definition with type=zwRiver , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the zwRiver input as described in UM Sec.C.16.1.3 .","title":"ZWRiverCrsDef"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.ZWRiverCrsDef.check_list_lengths","text":"Validates that the length of the levels, flowwidths and totalwidths fields are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths ( cls , values ): \"\"\"Validates that the length of the levels, flowwidths and totalwidths fields are as expected.\"\"\" return validate_correct_length ( values , \"levels\" , \"flowwidths\" , \"totalwidths\" , length_name = \"numlevels\" , )","title":"check_list_lengths()"},{"location":"reference/dimr/","text":"DIMR xml files \u00b6 The input to the Deltares Integrated Model Runner ( DIMR ) is a single XML file, represented by the classes below. Model \u00b6 Component ( BaseModel , ABC ) pydantic-model \u00b6 Specification of a BMI-compliant model component instance that will be executed by DIMR. Attributes: Name Type Description library str The library name of the compoment. name str The component name. workingDir Path The working directory. inputFile Path The name of the input file. process Optional[int] Number of subprocesses in the component. setting Optional[List[hydrolib.core.dimr.models.KeyValuePair]] A list of variables that are provided to the BMI model before initialization. parameter Optional[List[hydrolib.core.dimr.models.KeyValuePair]] A list of variables that are provided to the BMI model after initialization. mpiCommunicator Optional[str] The MPI communicator value. model Optional[hydrolib.core.basemodel.FileModel] The model represented by this component. dict ( self , * args , ** kwargs ) \u00b6 Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dimr/models.py def dict ( self , * args , ** kwargs ): # Exclude the FileModel from any DIMR serialization. kwargs [ \"exclude\" ] = { \"model\" } return super () . dict ( * args , ** kwargs ) is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dimr/models.py def is_intermediate_link ( self ) -> bool : return True ComponentOrCouplerRef ( BaseModel ) pydantic-model \u00b6 Reference to a BMI-compliant model component instance. Attributes: Name Type Description name str Name of the reference to a BMI-compliant model component instance. ControlModel ( BaseModel ) pydantic-model \u00b6 Overrides to make sure that the control elements in the DIMR are parsed and serialized correctly. dict ( self , * args , ** kwargs ) \u00b6 Add control element prefixes for serialized data. Source code in hydrolib/core/dimr/models.py def dict ( self , * args , ** kwargs ): \"\"\"Add control element prefixes for serialized data.\"\"\" return { str ( self . _type ): super () . dict ( * args , ** kwargs ), } validate ( v ) classmethod \u00b6 Remove control element prefixes from parsed data. Source code in hydrolib/core/dimr/models.py @classmethod def validate ( cls , v ): \"\"\"Remove control element prefixes from parsed data.\"\"\" # should be replaced by discriminated unions once merged # https://github.com/samuelcolvin/pydantic/pull/2336 if isinstance ( v , dict ) and len ( v . keys ()) == 1 : key = list ( v . keys ())[ 0 ] v = v [ key ] return super () . validate ( v ) CoupledItem ( BaseModel ) pydantic-model \u00b6 Specification of an item that has to be exchanged. Attributes: Name Type Description sourceName str Name of the item at the source component. targetName str Name of the item at the target component. is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dimr/models.py def is_intermediate_link ( self ) -> bool : # TODO set to True once we replace Paths with FileModels return False Coupler ( BaseModel ) pydantic-model \u00b6 Specification of the coupling actions to be performed between two BMI-compliant model components. Attributes: Name Type Description name str The name of the coupler. sourceComponent str The component that provides the data to has to be exchanged. targetComponent str The component that consumes the data to has to be exchanged. item List[hydrolib.core.dimr.models.CoupledItem] A list of items that have to be exchanged. logger Optional[hydrolib.core.dimr.models.Logger] Logger for logging the values that get exchanged. is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dimr/models.py def is_intermediate_link ( self ) -> bool : # TODO set to True once we replace Paths with FileModels return False DIMR ( ParsableFileModel ) pydantic-model \u00b6 DIMR model representation. Attributes: Name Type Description documentation Documentation File metadata. control List[Union[Start, Parallel]] The element with a list of Start and Parallel sub-elements, which defines the (sequence of) program(s) to be run. May be empty while constructing, but must be non-empty when saving! Also, all referenced components must be present in component when saving. Similarly, all referenced couplers must be present in coupler . component List[Union[RRComponent, FMComponent, Component]] List of elements that defines which programs can be used inside the subelements. Must be non-empty when saving! coupler Optional[List[Coupler]] optional list of elements that defines which couplers can be used inside the elements under . waitFile Optional[str] Optional waitfile name for debugging. global_settings Optional[GlobalSettings] Optional global DIMR settings. dict ( self , * args , ** kwargs ) \u00b6 Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dimr/models.py def dict ( self , * args , ** kwargs ): kwargs [ \"exclude_none\" ] = True return super () . dict ( * args , ** kwargs ) Documentation ( BaseModel ) pydantic-model \u00b6 Information on the present DIMR configuration file. Attributes: Name Type Description fileVersion str The DIMR file version. createdBy str Creators of the DIMR file. creationDate datetime The creation date of the DIMR file. FMComponent ( Component ) pydantic-model \u00b6 Component to include the D-Flow FM program in a DIMR control flow. GlobalSettings ( BaseModel ) pydantic-model \u00b6 Global settings for the DIMR configuration. Attributes: Name Type Description logger_ncFormat int NetCDF format type for logging. KeyValuePair ( BaseModel ) pydantic-model \u00b6 Key value pair to specify settings and parameters. Attributes: Name Type Description key str The key. value str The value. Logger ( BaseModel ) pydantic-model \u00b6 Used to log values to the specified file in workingdir for each timestep Attributes: Name Type Description workingDir Path Directory where the log file is written. outputFile Path Name of the log file. Parallel ( ControlModel ) pydantic-model \u00b6 Specification of a parallel control flow: one main component and a group of related components and couplers. Step wise execution order according to order in parallel control flow. Attributes: Name Type Description startGroup StartGroup Group of components and couplers to be executed. start ComponentOrCouplerRef Main component to be executed step wise (provides start time, end time and time step). RRComponent ( Component ) pydantic-model \u00b6 Component to include the RainfallRunoff program in a DIMR control flow. Start ( ControlModel ) pydantic-model \u00b6 Specification of a serial control flow: one main component. Attributes: Name Type Description name str Name of the reference to a BMI-compliant model component instance StartGroup ( BaseModel ) pydantic-model \u00b6 Specification of model components and couplers to be executed with a certain frequency. Attributes: Name Type Description time str Time frame specification for the present group: start time, stop time and frequency. Expressed in terms of the time frame of the main component. start List[hydrolib.core.dimr.models.ComponentOrCouplerRef] Ordered list of components to be executed. coupler List[hydrolib.core.dimr.models.ComponentOrCouplerRef] Oredered list of couplers to be executed. Parser \u00b6 DIMRParser \u00b6 A parser for DIMR xml files. parse ( path : Path ) -> dict staticmethod \u00b6 Parses a DIMR file to a dictionary. Parameters: Name Type Description Default path Path Path to the DIMR configuration file. required Source code in hydrolib/core/dimr/parser.py @staticmethod def parse ( path : Path ) -> dict : \"\"\"Parses a DIMR file to a dictionary. Args: path (Path): Path to the DIMR configuration file. \"\"\" if not path . is_file (): warn ( f \"File: ` { path } ` not found, skipped parsing.\" ) return {} parser = etree . XMLParser ( remove_comments = True , resolve_entities = False , no_network = True ) root = etree . parse ( str ( path ), parser = parser ) . getroot () return DIMRParser . _node_to_dictionary ( root , True ) Serializer \u00b6 DIMRSerializer \u00b6 A serializer for DIMR files. serialize ( path : Path , data : dict , config : SerializerConfig , save_settings : ModelSaveSettings ) staticmethod \u00b6 Serializes the DIMR data to the file at the specified path. Attributes: Name Type Description path Path The path to the destination file. data Dict The data to be serialized. config SerializerConfig The serialization configuration. save_settings ModelSaveSettings The model save settings. Source code in hydrolib/core/dimr/serializer.py @staticmethod def serialize ( path : Path , data : dict , config : SerializerConfig , save_settings : ModelSaveSettings , ): \"\"\" Serializes the DIMR data to the file at the specified path. Attributes: path (Path): The path to the destination file. data (Dict): The data to be serialized. config (SerializerConfig): The serialization configuration. save_settings (ModelSaveSettings): The model save settings. \"\"\" path . parent . mkdir ( parents = True , exist_ok = True ) xmlns = \"http://schemas.deltares.nl/dimr\" xsi = \"http://www.w3.org/2001/XMLSchema-instance\" schema_location = \"http://content.oss.deltares.nl/schemas/dimr-1.3.xsd\" attrib = { e . QName ( xsi , \"schemaLocation\" ): f \" { xmlns } { schema_location } \" } namespaces = { None : xmlns , \"xsi\" : xsi } root = e . Element ( \"dimrConfig\" , attrib = attrib , nsmap = namespaces , ) path_style_converter = FilePathStyleConverter () DIMRSerializer . _build_tree ( root , data , config , save_settings , path_style_converter ) to_string = minidom . parseString ( e . tostring ( root )) xml = to_string . toprettyxml ( indent = \" \" , encoding = \"utf-8\" ) with path . open ( \"wb\" ) as f : f . write ( xml )","title":"DIMR xml files"},{"location":"reference/dimr/#dimr-xml-files","text":"The input to the Deltares Integrated Model Runner ( DIMR ) is a single XML file, represented by the classes below.","title":"DIMR xml files"},{"location":"reference/dimr/#model","text":"","title":"Model"},{"location":"reference/dimr/#hydrolib.core.dimr.models.Component","text":"Specification of a BMI-compliant model component instance that will be executed by DIMR. Attributes: Name Type Description library str The library name of the compoment. name str The component name. workingDir Path The working directory. inputFile Path The name of the input file. process Optional[int] Number of subprocesses in the component. setting Optional[List[hydrolib.core.dimr.models.KeyValuePair]] A list of variables that are provided to the BMI model before initialization. parameter Optional[List[hydrolib.core.dimr.models.KeyValuePair]] A list of variables that are provided to the BMI model after initialization. mpiCommunicator Optional[str] The MPI communicator value. model Optional[hydrolib.core.basemodel.FileModel] The model represented by this component.","title":"Component"},{"location":"reference/dimr/#hydrolib.core.dimr.models.Component.dict","text":"Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dimr/models.py def dict ( self , * args , ** kwargs ): # Exclude the FileModel from any DIMR serialization. kwargs [ \"exclude\" ] = { \"model\" } return super () . dict ( * args , ** kwargs )","title":"dict()"},{"location":"reference/dimr/#hydrolib.core.dimr.models.Component.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dimr/models.py def is_intermediate_link ( self ) -> bool : return True","title":"is_intermediate_link()"},{"location":"reference/dimr/#hydrolib.core.dimr.models.ComponentOrCouplerRef","text":"Reference to a BMI-compliant model component instance. Attributes: Name Type Description name str Name of the reference to a BMI-compliant model component instance.","title":"ComponentOrCouplerRef"},{"location":"reference/dimr/#hydrolib.core.dimr.models.ControlModel","text":"Overrides to make sure that the control elements in the DIMR are parsed and serialized correctly.","title":"ControlModel"},{"location":"reference/dimr/#hydrolib.core.dimr.models.ControlModel.dict","text":"Add control element prefixes for serialized data. Source code in hydrolib/core/dimr/models.py def dict ( self , * args , ** kwargs ): \"\"\"Add control element prefixes for serialized data.\"\"\" return { str ( self . _type ): super () . dict ( * args , ** kwargs ), }","title":"dict()"},{"location":"reference/dimr/#hydrolib.core.dimr.models.ControlModel.validate","text":"Remove control element prefixes from parsed data. Source code in hydrolib/core/dimr/models.py @classmethod def validate ( cls , v ): \"\"\"Remove control element prefixes from parsed data.\"\"\" # should be replaced by discriminated unions once merged # https://github.com/samuelcolvin/pydantic/pull/2336 if isinstance ( v , dict ) and len ( v . keys ()) == 1 : key = list ( v . keys ())[ 0 ] v = v [ key ] return super () . validate ( v )","title":"validate()"},{"location":"reference/dimr/#hydrolib.core.dimr.models.CoupledItem","text":"Specification of an item that has to be exchanged. Attributes: Name Type Description sourceName str Name of the item at the source component. targetName str Name of the item at the target component.","title":"CoupledItem"},{"location":"reference/dimr/#hydrolib.core.dimr.models.CoupledItem.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dimr/models.py def is_intermediate_link ( self ) -> bool : # TODO set to True once we replace Paths with FileModels return False","title":"is_intermediate_link()"},{"location":"reference/dimr/#hydrolib.core.dimr.models.Coupler","text":"Specification of the coupling actions to be performed between two BMI-compliant model components. Attributes: Name Type Description name str The name of the coupler. sourceComponent str The component that provides the data to has to be exchanged. targetComponent str The component that consumes the data to has to be exchanged. item List[hydrolib.core.dimr.models.CoupledItem] A list of items that have to be exchanged. logger Optional[hydrolib.core.dimr.models.Logger] Logger for logging the values that get exchanged.","title":"Coupler"},{"location":"reference/dimr/#hydrolib.core.dimr.models.Coupler.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dimr/models.py def is_intermediate_link ( self ) -> bool : # TODO set to True once we replace Paths with FileModels return False","title":"is_intermediate_link()"},{"location":"reference/dimr/#hydrolib.core.dimr.models.DIMR","text":"DIMR model representation. Attributes: Name Type Description documentation Documentation File metadata. control List[Union[Start, Parallel]] The element with a list of Start and Parallel sub-elements, which defines the (sequence of) program(s) to be run. May be empty while constructing, but must be non-empty when saving! Also, all referenced components must be present in component when saving. Similarly, all referenced couplers must be present in coupler . component List[Union[RRComponent, FMComponent, Component]] List of elements that defines which programs can be used inside the subelements. Must be non-empty when saving! coupler Optional[List[Coupler]] optional list of elements that defines which couplers can be used inside the elements under . waitFile Optional[str] Optional waitfile name for debugging. global_settings Optional[GlobalSettings] Optional global DIMR settings.","title":"DIMR"},{"location":"reference/dimr/#hydrolib.core.dimr.models.DIMR.dict","text":"Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dimr/models.py def dict ( self , * args , ** kwargs ): kwargs [ \"exclude_none\" ] = True return super () . dict ( * args , ** kwargs )","title":"dict()"},{"location":"reference/dimr/#hydrolib.core.dimr.models.Documentation","text":"Information on the present DIMR configuration file. Attributes: Name Type Description fileVersion str The DIMR file version. createdBy str Creators of the DIMR file. creationDate datetime The creation date of the DIMR file.","title":"Documentation"},{"location":"reference/dimr/#hydrolib.core.dimr.models.FMComponent","text":"Component to include the D-Flow FM program in a DIMR control flow.","title":"FMComponent"},{"location":"reference/dimr/#hydrolib.core.dimr.models.GlobalSettings","text":"Global settings for the DIMR configuration. Attributes: Name Type Description logger_ncFormat int NetCDF format type for logging.","title":"GlobalSettings"},{"location":"reference/dimr/#hydrolib.core.dimr.models.KeyValuePair","text":"Key value pair to specify settings and parameters. Attributes: Name Type Description key str The key. value str The value.","title":"KeyValuePair"},{"location":"reference/dimr/#hydrolib.core.dimr.models.Logger","text":"Used to log values to the specified file in workingdir for each timestep Attributes: Name Type Description workingDir Path Directory where the log file is written. outputFile Path Name of the log file.","title":"Logger"},{"location":"reference/dimr/#hydrolib.core.dimr.models.Parallel","text":"Specification of a parallel control flow: one main component and a group of related components and couplers. Step wise execution order according to order in parallel control flow. Attributes: Name Type Description startGroup StartGroup Group of components and couplers to be executed. start ComponentOrCouplerRef Main component to be executed step wise (provides start time, end time and time step).","title":"Parallel"},{"location":"reference/dimr/#hydrolib.core.dimr.models.RRComponent","text":"Component to include the RainfallRunoff program in a DIMR control flow.","title":"RRComponent"},{"location":"reference/dimr/#hydrolib.core.dimr.models.Start","text":"Specification of a serial control flow: one main component. Attributes: Name Type Description name str Name of the reference to a BMI-compliant model component instance","title":"Start"},{"location":"reference/dimr/#hydrolib.core.dimr.models.StartGroup","text":"Specification of model components and couplers to be executed with a certain frequency. Attributes: Name Type Description time str Time frame specification for the present group: start time, stop time and frequency. Expressed in terms of the time frame of the main component. start List[hydrolib.core.dimr.models.ComponentOrCouplerRef] Ordered list of components to be executed. coupler List[hydrolib.core.dimr.models.ComponentOrCouplerRef] Oredered list of couplers to be executed.","title":"StartGroup"},{"location":"reference/dimr/#parser","text":"","title":"Parser"},{"location":"reference/dimr/#hydrolib.core.dimr.parser.DIMRParser","text":"A parser for DIMR xml files.","title":"DIMRParser"},{"location":"reference/dimr/#hydrolib.core.dimr.parser.DIMRParser.parse","text":"Parses a DIMR file to a dictionary. Parameters: Name Type Description Default path Path Path to the DIMR configuration file. required Source code in hydrolib/core/dimr/parser.py @staticmethod def parse ( path : Path ) -> dict : \"\"\"Parses a DIMR file to a dictionary. Args: path (Path): Path to the DIMR configuration file. \"\"\" if not path . is_file (): warn ( f \"File: ` { path } ` not found, skipped parsing.\" ) return {} parser = etree . XMLParser ( remove_comments = True , resolve_entities = False , no_network = True ) root = etree . parse ( str ( path ), parser = parser ) . getroot () return DIMRParser . _node_to_dictionary ( root , True )","title":"parse()"},{"location":"reference/dimr/#serializer","text":"","title":"Serializer"},{"location":"reference/dimr/#hydrolib.core.dimr.serializer.DIMRSerializer","text":"A serializer for DIMR files.","title":"DIMRSerializer"},{"location":"reference/dimr/#hydrolib.core.dimr.serializer.DIMRSerializer.serialize","text":"Serializes the DIMR data to the file at the specified path. Attributes: Name Type Description path Path The path to the destination file. data Dict The data to be serialized. config SerializerConfig The serialization configuration. save_settings ModelSaveSettings The model save settings. Source code in hydrolib/core/dimr/serializer.py @staticmethod def serialize ( path : Path , data : dict , config : SerializerConfig , save_settings : ModelSaveSettings , ): \"\"\" Serializes the DIMR data to the file at the specified path. Attributes: path (Path): The path to the destination file. data (Dict): The data to be serialized. config (SerializerConfig): The serialization configuration. save_settings (ModelSaveSettings): The model save settings. \"\"\" path . parent . mkdir ( parents = True , exist_ok = True ) xmlns = \"http://schemas.deltares.nl/dimr\" xsi = \"http://www.w3.org/2001/XMLSchema-instance\" schema_location = \"http://content.oss.deltares.nl/schemas/dimr-1.3.xsd\" attrib = { e . QName ( xsi , \"schemaLocation\" ): f \" { xmlns } { schema_location } \" } namespaces = { None : xmlns , \"xsi\" : xsi } root = e . Element ( \"dimrConfig\" , attrib = attrib , nsmap = namespaces , ) path_style_converter = FilePathStyleConverter () DIMRSerializer . _build_tree ( root , data , config , save_settings , path_style_converter ) to_string = minidom . parseString ( e . tostring ( root )) xml = to_string . toprettyxml ( indent = \" \" , encoding = \"utf-8\" ) with path . open ( \"wb\" ) as f : f . write ( xml )","title":"serialize()"},{"location":"reference/ext/","text":"External forcings file \u00b6 The external forcing .ext file contains the forcing data for a D-Flow FM model. This includes open boundaries, lateral discharges and meteorological forcings. The documentation below only concerns the 'new' format ( ExtForceFileNew in the MDU file). Model \u00b6 Boundary ( INIBasedModel ) pydantic-model \u00b6 A [Boundary] block for use inside an external forcings file, i.e., a ExtModel . All lowercased attributes match with the boundary input as described in UM Sec.C.5.2.1 . check_nodeid_or_locationfile_present ( values : Dict ) classmethod \u00b6 Verifies that either nodeid or locationfile properties have been set. Parameters: Name Type Description Default values Dict Dictionary with values already validated. required Exceptions: Type Description ValueError When none of the values are present. Returns: Type Description Dict Validated dictionary of values for Boundary. Source code in hydrolib/core/dflowfm/ext/models.py @root_validator @classmethod def check_nodeid_or_locationfile_present ( cls , values : Dict ): \"\"\" Verifies that either nodeid or locationfile properties have been set. Args: values (Dict): Dictionary with values already validated. Raises: ValueError: When none of the values are present. Returns: Dict: Validated dictionary of values for Boundary. \"\"\" node_id = values . get ( \"nodeid\" , None ) location_file = values . get ( \"locationfile\" , None ) if str_is_empty_or_none ( node_id ) and not cls . _is_valid_locationfile_data ( location_file ): raise ValueError ( \"Either nodeId or locationFile fields should be specified.\" ) return values forcing : ForcingBase property readonly \u00b6 Retrieves the corresponding forcing data for this boundary. Returns: Type Description ForcingBase The corresponding forcing data. None when this boundary does not have a forcing file or when the data cannot be found. is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/ext/models.py def is_intermediate_link ( self ) -> bool : return True ExtGeneral ( INIGeneral ) pydantic-model \u00b6 The external forcing file's [General] section with file meta data. ExtModel ( INIModel ) pydantic-model \u00b6 The overall external forcings model that contains the contents of one external forcings file (new format). This model is typically referenced under a FMModel .external_forcing.extforcefilenew . Attributes: Name Type Description general ExtGeneral [General] block with file metadata. boundary List[Boundary] List of [Boundary] blocks for all boundary conditions. lateral List[Lateral] List of [Lateral] blocks for all lateral discharges. meteo List[Meteo] List of [Meteo] blocks for all meteorological forcings. Lateral ( INIBasedModel ) pydantic-model \u00b6 A [Lateral] block for use inside an external forcings file, i.e., a ExtModel . All lowercased attributes match with the lateral input as described in UM Sec.C.5.2.2 . is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/ext/models.py def is_intermediate_link ( self ) -> bool : return True validate_location_type ( v : str ) -> str classmethod \u00b6 Method to validate whether the specified location type is correct. Parameters: Name Type Description Default v str Given value for the locationtype field. required Exceptions: Type Description ValueError When the value given for locationtype is unknown. Returns: Type Description str Validated locationtype string. Source code in hydrolib/core/dflowfm/ext/models.py @validator ( \"locationtype\" ) @classmethod def validate_location_type ( cls , v : str ) -> str : \"\"\" Method to validate whether the specified location type is correct. Args: v (str): Given value for the locationtype field. Raises: ValueError: When the value given for locationtype is unknown. Returns: str: Validated locationtype string. \"\"\" possible_values = [ \"1d\" , \"2d\" , \"all\" ] if v . lower () not in possible_values : raise ValueError ( \"Value given ( {} ) not accepted, should be one of: {} \" . format ( v , \", \" . join ( possible_values ) ) ) return v validate_that_location_specification_is_correct ( values : Dict ) -> Dict classmethod \u00b6 Validates that the correct location specification is given. Source code in hydrolib/core/dflowfm/ext/models.py @root_validator ( allow_reuse = True ) def validate_that_location_specification_is_correct ( cls , values : Dict ) -> Dict : \"\"\"Validates that the correct location specification is given.\"\"\" return validate_location_specification ( values , config = LocationValidationConfiguration ( minimum_num_coordinates = 1 ) ) Meteo ( INIBasedModel ) pydantic-model \u00b6 A [Meteo] block for use inside an external forcings file, i.e., a ExtModel . All lowercased attributes match with the meteo input as described in UM Sec.C.5.2.3 . is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/ext/models.py def is_intermediate_link ( self ) -> bool : return True MeteoForcingFileType ( str , Enum ) \u00b6 Enum class containing the valid values for the forcingFileType attribute in Meteo class. bcascii \u00b6 str: Space-uniform time series in <*.bc> file. netcdf \u00b6 str: NetCDF, either with gridded data, or multiple station time series. uniform \u00b6 str: Space-uniform time series in <*.tim> file. MeteoInterpolationMethod ( str , Enum ) \u00b6 Enum class containing the valid values for the interpolationMethod attribute in Meteo class. nearestnb \u00b6 str: Nearest-neighbour interpolation, only with station-data in forcingFileType=netcdf","title":"External forcings file"},{"location":"reference/ext/#external-forcings-file","text":"The external forcing .ext file contains the forcing data for a D-Flow FM model. This includes open boundaries, lateral discharges and meteorological forcings. The documentation below only concerns the 'new' format ( ExtForceFileNew in the MDU file).","title":"External forcings file"},{"location":"reference/ext/#model","text":"","title":"Model"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Boundary","text":"A [Boundary] block for use inside an external forcings file, i.e., a ExtModel . All lowercased attributes match with the boundary input as described in UM Sec.C.5.2.1 .","title":"Boundary"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Boundary.check_nodeid_or_locationfile_present","text":"Verifies that either nodeid or locationfile properties have been set. Parameters: Name Type Description Default values Dict Dictionary with values already validated. required Exceptions: Type Description ValueError When none of the values are present. Returns: Type Description Dict Validated dictionary of values for Boundary. Source code in hydrolib/core/dflowfm/ext/models.py @root_validator @classmethod def check_nodeid_or_locationfile_present ( cls , values : Dict ): \"\"\" Verifies that either nodeid or locationfile properties have been set. Args: values (Dict): Dictionary with values already validated. Raises: ValueError: When none of the values are present. Returns: Dict: Validated dictionary of values for Boundary. \"\"\" node_id = values . get ( \"nodeid\" , None ) location_file = values . get ( \"locationfile\" , None ) if str_is_empty_or_none ( node_id ) and not cls . _is_valid_locationfile_data ( location_file ): raise ValueError ( \"Either nodeId or locationFile fields should be specified.\" ) return values","title":"check_nodeid_or_locationfile_present()"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Boundary.forcing","text":"Retrieves the corresponding forcing data for this boundary. Returns: Type Description ForcingBase The corresponding forcing data. None when this boundary does not have a forcing file or when the data cannot be found.","title":"forcing"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Boundary.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/ext/models.py def is_intermediate_link ( self ) -> bool : return True","title":"is_intermediate_link()"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.ExtGeneral","text":"The external forcing file's [General] section with file meta data.","title":"ExtGeneral"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.ExtModel","text":"The overall external forcings model that contains the contents of one external forcings file (new format). This model is typically referenced under a FMModel .external_forcing.extforcefilenew . Attributes: Name Type Description general ExtGeneral [General] block with file metadata. boundary List[Boundary] List of [Boundary] blocks for all boundary conditions. lateral List[Lateral] List of [Lateral] blocks for all lateral discharges. meteo List[Meteo] List of [Meteo] blocks for all meteorological forcings.","title":"ExtModel"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Lateral","text":"A [Lateral] block for use inside an external forcings file, i.e., a ExtModel . All lowercased attributes match with the lateral input as described in UM Sec.C.5.2.2 .","title":"Lateral"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Lateral.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/ext/models.py def is_intermediate_link ( self ) -> bool : return True","title":"is_intermediate_link()"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Lateral.validate_location_type","text":"Method to validate whether the specified location type is correct. Parameters: Name Type Description Default v str Given value for the locationtype field. required Exceptions: Type Description ValueError When the value given for locationtype is unknown. Returns: Type Description str Validated locationtype string. Source code in hydrolib/core/dflowfm/ext/models.py @validator ( \"locationtype\" ) @classmethod def validate_location_type ( cls , v : str ) -> str : \"\"\" Method to validate whether the specified location type is correct. Args: v (str): Given value for the locationtype field. Raises: ValueError: When the value given for locationtype is unknown. Returns: str: Validated locationtype string. \"\"\" possible_values = [ \"1d\" , \"2d\" , \"all\" ] if v . lower () not in possible_values : raise ValueError ( \"Value given ( {} ) not accepted, should be one of: {} \" . format ( v , \", \" . join ( possible_values ) ) ) return v","title":"validate_location_type()"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Lateral.validate_that_location_specification_is_correct","text":"Validates that the correct location specification is given. Source code in hydrolib/core/dflowfm/ext/models.py @root_validator ( allow_reuse = True ) def validate_that_location_specification_is_correct ( cls , values : Dict ) -> Dict : \"\"\"Validates that the correct location specification is given.\"\"\" return validate_location_specification ( values , config = LocationValidationConfiguration ( minimum_num_coordinates = 1 ) )","title":"validate_that_location_specification_is_correct()"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Meteo","text":"A [Meteo] block for use inside an external forcings file, i.e., a ExtModel . All lowercased attributes match with the meteo input as described in UM Sec.C.5.2.3 .","title":"Meteo"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Meteo.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/ext/models.py def is_intermediate_link ( self ) -> bool : return True","title":"is_intermediate_link()"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.MeteoForcingFileType","text":"Enum class containing the valid values for the forcingFileType attribute in Meteo class.","title":"MeteoForcingFileType"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.MeteoForcingFileType.bcascii","text":"str: Space-uniform time series in <*.bc> file.","title":"bcascii"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.MeteoForcingFileType.netcdf","text":"str: NetCDF, either with gridded data, or multiple station time series.","title":"netcdf"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.MeteoForcingFileType.uniform","text":"str: Space-uniform time series in <*.tim> file.","title":"uniform"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.MeteoInterpolationMethod","text":"Enum class containing the valid values for the interpolationMethod attribute in Meteo class.","title":"MeteoInterpolationMethod"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.MeteoInterpolationMethod.nearestnb","text":"str: Nearest-neighbour interpolation, only with station-data in forcingFileType=netcdf","title":"nearestnb"},{"location":"reference/extold/","text":"External forcings file \u00b6 The external forcing .ext file contains the forcing data for a D-Flow FM model. This includes open boundaries, lateral discharges and meteorological forcings. The documentation below only concerns the 'old' format ( ExtForceFile in the MDU file). Model \u00b6 ExtOldExtrapolationMethod ( IntEnum ) \u00b6 Enum class containing the valid values for the extrapolation_method attribute in the ExtOldForcing class. NoSpatialExtrapolation \u00b6 No spatial extrapolation. SpatialExtrapolationOutsideOfSourceDataBoundingBox \u00b6 Do spatial extrapolation outside of source data bounding box. ExtOldFileType ( IntEnum ) \u00b6 Enum class containing the valid values for the filetype attribute in the ExtOldForcing class. ArcInfo \u00b6 ArcInfo CurvilinearData \u00b6 Space-time data on curvilinear grid NetCDFGridData \u00b6 NetCDF grid data (e.g. meteo fields) NetCDFWaveData \u00b6 NetCDF wave data Polyfile \u00b6 Polyfile (< .pol/ .pli>-file). uniform value inside polygon for INITIAL fields Polyline \u00b6 Polyline (<*.pli>-file) Samples \u00b6 Samples SpatiallyVaryingWindPressure \u00b6 Spatially varying wind and pressure SpiderWebData \u00b6 Spiderweb data (cyclones) TimeSeries \u00b6 Time series TimeSeriesMagnitudeAndDirection \u00b6 Time series magnitude and direction TriangulationMagnitudeAndDirection \u00b6 Triangulation magnitude and direction ExtOldForcing ( BaseModel ) pydantic-model \u00b6 Class holding the external forcing values. ExtOldMethod ( IntEnum ) \u00b6 Enum class containing the valid values for the method attribute in the ExtOldForcing class. AveragingSpace \u00b6 Averaging in space InterpolateExtrapolateTime \u00b6 Interpolate/Extrapolate time InterpolateSpace \u00b6 Interpolate space InterpolateTime \u00b6 Interpolate time InterpolateTimeAndSpace \u00b6 Interpolate time and space InterpolateTimeAndSpaceSaveWeights \u00b6 Interpolate time and space, save weights PassThrough \u00b6 Pass through (no interpolation) ExtOldModel ( ParsableFileModel ) pydantic-model \u00b6 The overall external forcings model that contains the contents of one external forcings file (old format). This model is typically referenced under a FMModel .external_forcing.extforcefile . dict ( self , * args , ** kwargs ) \u00b6 Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dflowfm/extold/models.py def dict ( self , * args , ** kwargs ): return dict ( comment = self . comment , forcing = [ dict ( f ) for f in self . forcing ]) ExtOldQuantity ( str , Enum ) \u00b6 Enum class containing the valid values for the boundary conditions category of the external forcings. AdvectionType \u00b6 Type of advection scheme AirDensity \u00b6 Air density AirPressure \u00b6 AirPressure AirPressureWindXWindY \u00b6 Atmospheric pressure and wind components AirPressureWindXWindYCharnock \u00b6 Atmospheric pressure and wind components Charnock AirTemperature \u00b6 AirTemperature AirpressureStressXStressY \u00b6 Airpressure, eastward and northward wind stress AtmosphericPressure \u00b6 Atmospheric pressure BedLevel \u00b6 Bed level Charnock \u00b6 Charnock coefficient Cloudiness \u00b6 Cloudiness, or cloud cover (fraction) DamLevel \u00b6 Dam level DewPointAirTemperatureCloudiness \u00b6 Dew point air temperature cloudiness Dewpoint \u00b6 Dewpoint temperature DewpointAirTemperatureCloudinessSolarradiation \u00b6 Dewpoint temperature, air temperature, cloudiness, solarradiation DischargeBnd \u00b6 Discharge DischargeSalinityTemperatureSorSin \u00b6 Discharge, salinity temperature source-sinks FrictionCoefficient \u00b6 Friction coefficient GateLowerEdgeLevel \u00b6 Gate lower edge level GeneralStructure \u00b6 General structure HorizontalEddyDiffusivityCoefficient \u00b6 Horizontal eddy diffusivity coefficient HorizontalEddyViscosityCoefficient \u00b6 Horizontal eddy viscosity coefficient Humidity \u00b6 Humidity HumidityAirTemperatureCloudiness \u00b6 Combined heat flux terms HumidityAirTemperatureCloudinessSolarRadiation \u00b6 Combined heat flux terms IBotLevType \u00b6 Type of bed-level handling InitialSalinity \u00b6 Initial salinity InitialSalinityTop \u00b6 Initial salinity top layer InitialTemperature \u00b6 Initial temperature InitialVerticalSalinityProfile \u00b6 Initial vertical salinity profile InitialVerticalTemperatureProfile \u00b6 Initial vertical temperature profile InitialWaterLevel \u00b6 Initial water level InternalTidesFrictionCoefficient \u00b6 Internal tides friction coefficient LongWaveRadiation \u00b6 Long wave radiation MovingStationXY \u00b6 Moving observation point for output (time, x, y) NeumannBnd \u00b6 Water level gradient NormalVelocityBnd \u00b6 Normal velocity NudgeSalinityTemperature \u00b6 Nudging salinity and temperature OutflowBnd \u00b6 Outflow Pump \u00b6 Pump capacity QhBnd \u00b6 Discharge-water level dependency Rainfall \u00b6 Precipitation RainfallRate \u00b6 Precipitation RiemannBnd \u00b6 Riemann invariant RiemannVelocityBnd \u00b6 Riemann invariant velocity SalinityBnd \u00b6 Salinity SedimentBnd \u00b6 Suspended sediment ShiptXY \u00b6 shiptxy SolarRadiation \u00b6 Solar radiation StressX \u00b6 eastward wind stress StressXY \u00b6 eastward and northward wind stress StressY \u00b6 northward wind stress TangentialVelocityBnd \u00b6 Tangentional velocity TemperatureBnd \u00b6 Temperature UXUYAdvectionVelocityBnd \u00b6 ux-uy advection velocity VelocityBnd \u00b6 Velocity WaterLevelBnd \u00b6 Water level WavePeriod \u00b6 Wave period WaveSignificantHeight \u00b6 Wave significant height WindFromDirection \u00b6 WindFromDirection WindSpeed \u00b6 WindSpeed WindX \u00b6 Wind x component WindXY \u00b6 Wind vector WindY \u00b6 Wind y component ExtOldTracerQuantity ( str , Enum ) \u00b6 Enum class containing the valid values for the boundary conditions category of the external forcings that are specific to tracers. InitialTracer \u00b6 Initial tracer TracerBnd \u00b6 User-defined tracer","title":"External forcings file"},{"location":"reference/extold/#external-forcings-file","text":"The external forcing .ext file contains the forcing data for a D-Flow FM model. This includes open boundaries, lateral discharges and meteorological forcings. The documentation below only concerns the 'old' format ( ExtForceFile in the MDU file).","title":"External forcings file"},{"location":"reference/extold/#model","text":"","title":"Model"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldExtrapolationMethod","text":"Enum class containing the valid values for the extrapolation_method attribute in the ExtOldForcing class.","title":"ExtOldExtrapolationMethod"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldExtrapolationMethod.NoSpatialExtrapolation","text":"No spatial extrapolation.","title":"NoSpatialExtrapolation"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldExtrapolationMethod.SpatialExtrapolationOutsideOfSourceDataBoundingBox","text":"Do spatial extrapolation outside of source data bounding box.","title":"SpatialExtrapolationOutsideOfSourceDataBoundingBox"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType","text":"Enum class containing the valid values for the filetype attribute in the ExtOldForcing class.","title":"ExtOldFileType"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.ArcInfo","text":"ArcInfo","title":"ArcInfo"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.CurvilinearData","text":"Space-time data on curvilinear grid","title":"CurvilinearData"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.NetCDFGridData","text":"NetCDF grid data (e.g. meteo fields)","title":"NetCDFGridData"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.NetCDFWaveData","text":"NetCDF wave data","title":"NetCDFWaveData"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.Polyfile","text":"Polyfile (< .pol/ .pli>-file). uniform value inside polygon for INITIAL fields","title":"Polyfile"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.Polyline","text":"Polyline (<*.pli>-file)","title":"Polyline"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.Samples","text":"Samples","title":"Samples"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.SpatiallyVaryingWindPressure","text":"Spatially varying wind and pressure","title":"SpatiallyVaryingWindPressure"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.SpiderWebData","text":"Spiderweb data (cyclones)","title":"SpiderWebData"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.TimeSeries","text":"Time series","title":"TimeSeries"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.TimeSeriesMagnitudeAndDirection","text":"Time series magnitude and direction","title":"TimeSeriesMagnitudeAndDirection"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.TriangulationMagnitudeAndDirection","text":"Triangulation magnitude and direction","title":"TriangulationMagnitudeAndDirection"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldForcing","text":"Class holding the external forcing values.","title":"ExtOldForcing"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldMethod","text":"Enum class containing the valid values for the method attribute in the ExtOldForcing class.","title":"ExtOldMethod"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldMethod.AveragingSpace","text":"Averaging in space","title":"AveragingSpace"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldMethod.InterpolateExtrapolateTime","text":"Interpolate/Extrapolate time","title":"InterpolateExtrapolateTime"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldMethod.InterpolateSpace","text":"Interpolate space","title":"InterpolateSpace"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldMethod.InterpolateTime","text":"Interpolate time","title":"InterpolateTime"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldMethod.InterpolateTimeAndSpace","text":"Interpolate time and space","title":"InterpolateTimeAndSpace"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldMethod.InterpolateTimeAndSpaceSaveWeights","text":"Interpolate time and space, save weights","title":"InterpolateTimeAndSpaceSaveWeights"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldMethod.PassThrough","text":"Pass through (no interpolation)","title":"PassThrough"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldModel","text":"The overall external forcings model that contains the contents of one external forcings file (old format). This model is typically referenced under a FMModel .external_forcing.extforcefile .","title":"ExtOldModel"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldModel.dict","text":"Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dflowfm/extold/models.py def dict ( self , * args , ** kwargs ): return dict ( comment = self . comment , forcing = [ dict ( f ) for f in self . forcing ])","title":"dict()"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity","text":"Enum class containing the valid values for the boundary conditions category of the external forcings.","title":"ExtOldQuantity"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.AdvectionType","text":"Type of advection scheme","title":"AdvectionType"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.AirDensity","text":"Air density","title":"AirDensity"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.AirPressure","text":"AirPressure","title":"AirPressure"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.AirPressureWindXWindY","text":"Atmospheric pressure and wind components","title":"AirPressureWindXWindY"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.AirPressureWindXWindYCharnock","text":"Atmospheric pressure and wind components Charnock","title":"AirPressureWindXWindYCharnock"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.AirTemperature","text":"AirTemperature","title":"AirTemperature"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.AirpressureStressXStressY","text":"Airpressure, eastward and northward wind stress","title":"AirpressureStressXStressY"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.AtmosphericPressure","text":"Atmospheric pressure","title":"AtmosphericPressure"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.BedLevel","text":"Bed level","title":"BedLevel"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.Charnock","text":"Charnock coefficient","title":"Charnock"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.Cloudiness","text":"Cloudiness, or cloud cover (fraction)","title":"Cloudiness"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.DamLevel","text":"Dam level","title":"DamLevel"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.DewPointAirTemperatureCloudiness","text":"Dew point air temperature cloudiness","title":"DewPointAirTemperatureCloudiness"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.Dewpoint","text":"Dewpoint temperature","title":"Dewpoint"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.DewpointAirTemperatureCloudinessSolarradiation","text":"Dewpoint temperature, air temperature, cloudiness, solarradiation","title":"DewpointAirTemperatureCloudinessSolarradiation"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.DischargeBnd","text":"Discharge","title":"DischargeBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.DischargeSalinityTemperatureSorSin","text":"Discharge, salinity temperature source-sinks","title":"DischargeSalinityTemperatureSorSin"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.FrictionCoefficient","text":"Friction coefficient","title":"FrictionCoefficient"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.GateLowerEdgeLevel","text":"Gate lower edge level","title":"GateLowerEdgeLevel"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.GeneralStructure","text":"General structure","title":"GeneralStructure"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.HorizontalEddyDiffusivityCoefficient","text":"Horizontal eddy diffusivity coefficient","title":"HorizontalEddyDiffusivityCoefficient"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.HorizontalEddyViscosityCoefficient","text":"Horizontal eddy viscosity coefficient","title":"HorizontalEddyViscosityCoefficient"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.Humidity","text":"Humidity","title":"Humidity"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.HumidityAirTemperatureCloudiness","text":"Combined heat flux terms","title":"HumidityAirTemperatureCloudiness"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.HumidityAirTemperatureCloudinessSolarRadiation","text":"Combined heat flux terms","title":"HumidityAirTemperatureCloudinessSolarRadiation"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.IBotLevType","text":"Type of bed-level handling","title":"IBotLevType"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.InitialSalinity","text":"Initial salinity","title":"InitialSalinity"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.InitialSalinityTop","text":"Initial salinity top layer","title":"InitialSalinityTop"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.InitialTemperature","text":"Initial temperature","title":"InitialTemperature"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.InitialVerticalSalinityProfile","text":"Initial vertical salinity profile","title":"InitialVerticalSalinityProfile"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.InitialVerticalTemperatureProfile","text":"Initial vertical temperature profile","title":"InitialVerticalTemperatureProfile"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.InitialWaterLevel","text":"Initial water level","title":"InitialWaterLevel"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.InternalTidesFrictionCoefficient","text":"Internal tides friction coefficient","title":"InternalTidesFrictionCoefficient"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.LongWaveRadiation","text":"Long wave radiation","title":"LongWaveRadiation"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.MovingStationXY","text":"Moving observation point for output (time, x, y)","title":"MovingStationXY"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.NeumannBnd","text":"Water level gradient","title":"NeumannBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.NormalVelocityBnd","text":"Normal velocity","title":"NormalVelocityBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.NudgeSalinityTemperature","text":"Nudging salinity and temperature","title":"NudgeSalinityTemperature"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.OutflowBnd","text":"Outflow","title":"OutflowBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.Pump","text":"Pump capacity","title":"Pump"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.QhBnd","text":"Discharge-water level dependency","title":"QhBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.Rainfall","text":"Precipitation","title":"Rainfall"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.RainfallRate","text":"Precipitation","title":"RainfallRate"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.RiemannBnd","text":"Riemann invariant","title":"RiemannBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.RiemannVelocityBnd","text":"Riemann invariant velocity","title":"RiemannVelocityBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.SalinityBnd","text":"Salinity","title":"SalinityBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.SedimentBnd","text":"Suspended sediment","title":"SedimentBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.ShiptXY","text":"shiptxy","title":"ShiptXY"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.SolarRadiation","text":"Solar radiation","title":"SolarRadiation"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.StressX","text":"eastward wind stress","title":"StressX"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.StressXY","text":"eastward and northward wind stress","title":"StressXY"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.StressY","text":"northward wind stress","title":"StressY"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.TangentialVelocityBnd","text":"Tangentional velocity","title":"TangentialVelocityBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.TemperatureBnd","text":"Temperature","title":"TemperatureBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.UXUYAdvectionVelocityBnd","text":"ux-uy advection velocity","title":"UXUYAdvectionVelocityBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.VelocityBnd","text":"Velocity","title":"VelocityBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.WaterLevelBnd","text":"Water level","title":"WaterLevelBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.WavePeriod","text":"Wave period","title":"WavePeriod"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.WaveSignificantHeight","text":"Wave significant height","title":"WaveSignificantHeight"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.WindFromDirection","text":"WindFromDirection","title":"WindFromDirection"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.WindSpeed","text":"WindSpeed","title":"WindSpeed"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.WindX","text":"Wind x component","title":"WindX"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.WindXY","text":"Wind vector","title":"WindXY"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.WindY","text":"Wind y component","title":"WindY"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldTracerQuantity","text":"Enum class containing the valid values for the boundary conditions category of the external forcings that are specific to tracers.","title":"ExtOldTracerQuantity"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldTracerQuantity.InitialTracer","text":"Initial tracer","title":"InitialTracer"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldTracerQuantity.TracerBnd","text":"User-defined tracer","title":"TracerBnd"},{"location":"reference/forcing/","text":"Forcings .bc file \u00b6 The forcings .bc files contain forcing data for point locations, for example time series input for a boundary condition. Various quantities and function types are supported. The forcings file is represented by the classes below. Model \u00b6 Representation of a .bc file in various classes. Most relevant classes are: ForcingModel: toplevel class containing the whole .bc file contents. ForcingBase subclasses: containing the actual data columns, for example: TimeSeries, HarmonicComponent, AstronomicComponent, HarmonicCorrection, AstronomicCorrection, Constant, T3D. Astronomic ( ForcingBase ) pydantic-model \u00b6 Subclass for a .bc file [Forcing] block with astronomic components data. AstronomicCorrection ( ForcingBase ) pydantic-model \u00b6 Subclass for a .bc file [Forcing] block with astronomic components correction data. Constant ( ForcingBase ) pydantic-model \u00b6 Subclass for a .bc file [Forcing] block with constant value data. ForcingBase ( DataBlockINIBasedModel ) pydantic-model \u00b6 The base class of a single [Forcing] block in a .bc forcings file. Typically subclassed, for the specific types of forcing data, e.g, Harmonic. This model is for example referenced under a ForcingModel .forcing[..] . __repr__ ( self ) -> str special \u00b6 Return repr(self). Source code in hydrolib/core/dflowfm/bc/models.py def __repr__ ( self ) -> str : data = dict ( self ) data [ \"datablock\" ] = \"\" representable = BaseModel . construct ( ** data ) return str ( representable ) validate ( v ) classmethod \u00b6 Try to initialize subclass based on the function field. This field is compared to each function field of the derived models of ForcingBase or models derived from derived models. The derived model with an equal function type will be initialized. Exceptions: Type Description ValueError When the given type is not a known structure type. Source code in hydrolib/core/dflowfm/bc/models.py @classmethod def validate ( cls , v ): \"\"\"Try to initialize subclass based on the `function` field. This field is compared to each `function` field of the derived models of `ForcingBase` or models derived from derived models. The derived model with an equal function type will be initialized. Raises: ValueError: When the given type is not a known structure type. \"\"\" # should be replaced by discriminated unions once merged # https://github.com/samuelcolvin/pydantic/pull/2336 if isinstance ( v , dict ): function_string = v . get ( \"function\" , \"\" ) . lower () function_type = get_type_based_on_subclass_default_value ( cls , \"function\" , function_string ) if function_type is not None : return function_type ( ** v ) else : raise ValueError ( f \"Function of { cls . __name__ } with name= { v . get ( 'name' , '' ) } and function= { v . get ( 'function' , '' ) } is not recognized.\" ) return v ForcingData \u00b6 Data type that selects from three different types of forcing data: * a scalar float constant * \"realtime\" keyword, indicating externally controlled. * A ForcingModel coming from a .bc file. ForcingGeneral ( INIGeneral ) pydantic-model \u00b6 [General] section with .bc file metadata. ForcingModel ( INIModel ) pydantic-model \u00b6 The overall model that contains the contents of one .bc forcings file. This model is for example referenced under a ExtModel .boundary[..].forcingfile[..] . Harmonic ( ForcingBase ) pydantic-model \u00b6 Subclass for a .bc file [Forcing] block with harmonic components data. HarmonicCorrection ( ForcingBase ) pydantic-model \u00b6 Subclass for a .bc file [Forcing] block with harmonic components correction data. QHTable ( ForcingBase ) pydantic-model \u00b6 Subclass for a .bc file [Forcing] block with Q-h table data. QuantityUnitPair ( BaseModel ) pydantic-model \u00b6 A .bc file header lines tuple containing a quantity name, its unit and optionally a vertical position index. RealTime ( str , Enum ) \u00b6 Enum class containing the valid value for the \"realtime\" reserved keyword for real-time controlled forcing data, e.g., for hydraulic structures. This class is used inside the ForcingData Union, to force detection of the realtime keyword, prior to considering it a filename. realtime \u00b6 str: Realtime data source, externally provided T3D ( VectorForcingBase ) pydantic-model \u00b6 Subclass for a .bc file [Forcing] block with 3D timeseries data. get_number_of_repetitions ( values : Dict ) -> int classmethod \u00b6 Gets the number of expected quantityunitpairs for each vector element. Defaults to 1. Source code in hydrolib/core/dflowfm/bc/models.py @classmethod def get_number_of_repetitions ( cls , values : Dict ) -> int : verticalpositions = values . get ( \"vertpositions\" ) # Since the renaming root validator may not have been run yet, in this # method we explicitly check old keywords for backwards compatibility: if verticalpositions is None : # try to get the value from any of the older keywords for old_keyword in cls . _keys_to_rename [ \"vertpositions\" ]: verticalpositions = values . get ( old_keyword ) if verticalpositions is not None : break if verticalpositions is None : raise ValueError ( \"vertPositions is not provided\" ) number_of_verticalpositions = ( len ( verticalpositions ) if isinstance ( verticalpositions , List ) else len ( verticalpositions . split ()) ) return number_of_verticalpositions rename_keys ( values : Dict ) -> Dict classmethod \u00b6 Renames some old keywords to the currently supported keywords. Source code in hydrolib/core/dflowfm/bc/models.py @root_validator ( allow_reuse = True , pre = True ) def rename_keys ( cls , values : Dict ) -> Dict : \"\"\"Renames some old keywords to the currently supported keywords.\"\"\" return rename_keys_for_backwards_compatibility ( values , cls . _keys_to_rename ) TimeInterpolation ( str , Enum ) \u00b6 Enum class containing the valid values for the time interpolation. block_from \u00b6 str: Equal to that at the start of the time interval (latest specified time value). block_to \u00b6 str: Equal to that at the end of the time interval (upcoming specified time value). linear \u00b6 str: Linear interpolation between times. TimeSeries ( VectorForcingBase ) pydantic-model \u00b6 Subclass for a .bc file [Forcing] block with timeseries data. rename_keys ( values : Dict ) -> Dict classmethod \u00b6 Renames some old keywords to the currently supported keywords. Source code in hydrolib/core/dflowfm/bc/models.py @root_validator ( allow_reuse = True , pre = True ) def rename_keys ( cls , values : Dict ) -> Dict : \"\"\"Renames some old keywords to the currently supported keywords.\"\"\" return rename_keys_for_backwards_compatibility ( values , { \"timeinterpolation\" : [ \"time_interpolation\" ], }, ) VectorForcingBase ( ForcingBase ) pydantic-model \u00b6 The base class of a single [Forcing] block that supports vectors in a .bc forcings file. get_number_of_repetitions ( values : Dict ) -> int classmethod \u00b6 Gets the number of expected quantityunitpairs for each vector element. Defaults to 1. Source code in hydrolib/core/dflowfm/bc/models.py @classmethod def get_number_of_repetitions ( cls , values : Dict ) -> int : \"\"\"Gets the number of expected quantityunitpairs for each vector element. Defaults to 1.\"\"\" return 1 validate_and_update_quantityunitpairs ( values : Dict ) -> Dict classmethod \u00b6 Validates and, if required, updates vector quantity unit pairs. Parameters: Name Type Description Default values Dict Dictionary of values to be used to validate or required Exceptions: Type Description ValueError When a quantity unit pair is found in a vector where it does not belong. ValueError When the number of quantity unit pairs in a vectors is not as expected. Returns: Type Description Dict Dictionary of validates values. Source code in hydrolib/core/dflowfm/bc/models.py @root_validator ( pre = True ) def validate_and_update_quantityunitpairs ( cls , values : Dict ) -> Dict : \"\"\" Validates and, if required, updates vector quantity unit pairs. Args: values (Dict): Dictionary of values to be used to validate or update vector quantity unit pairs. Raises: ValueError: When a quantity unit pair is found in a vector where it does not belong. ValueError: When the number of quantity unit pairs in a vectors is not as expected. Returns: Dict: Dictionary of validates values. \"\"\" quantityunitpairs = values [ \"quantityunitpair\" ] vector = values . get ( \"vector\" ) number_of_element_repetitions = cls . get_number_of_repetitions ( values ) VectorForcingBase . _process_vectordefinition_or_check_quantityunitpairs ( vector , quantityunitpairs , number_of_element_repetitions ) return values VectorQuantityUnitPairs ( BaseModel ) pydantic-model \u00b6 A subset of .bc file header lines containing a vector quantity definition, followed by all component quantity names, their unit and optionally their vertical position indexes. __str__ ( self ) -> str special \u00b6 Return str(self). Source code in hydrolib/core/dflowfm/bc/models.py def __str__ ( self ) -> str : return VectorQuantityUnitPairs . _to_vectordefinition_string ( self . vectorname , self . elementname ) VerticalInterpolation ( str , Enum ) \u00b6 Enum class containing the valid values for the vertical position type, which defines what the numeric values for vertical position specification mean. block \u00b6 str: Equal to the value at the directly lower specified vertical position. linear \u00b6 str: Linear interpolation between vertical positions. log \u00b6 str: Logarithmic interpolation between vertical positions (e.g. vertical velocity profiles). VerticalPositionType ( str , Enum ) \u00b6 Enum class containing the valid values for the vertical position type. percentage_bed \u00b6 str: Percentage with respect to the water depth from the bed upward. z_bed \u00b6 str: Absolute distance from the bed upward. z_datum \u00b6 str: z-coordinate with respect to the reference level of the model. z_surf \u00b6 str: Absolute distance from the free surface downward.","title":"Forcings .bc file"},{"location":"reference/forcing/#forcings-bc-file","text":"The forcings .bc files contain forcing data for point locations, for example time series input for a boundary condition. Various quantities and function types are supported. The forcings file is represented by the classes below.","title":"Forcings .bc file"},{"location":"reference/forcing/#model","text":"Representation of a .bc file in various classes. Most relevant classes are: ForcingModel: toplevel class containing the whole .bc file contents. ForcingBase subclasses: containing the actual data columns, for example: TimeSeries, HarmonicComponent, AstronomicComponent, HarmonicCorrection, AstronomicCorrection, Constant, T3D.","title":"Model"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.Astronomic","text":"Subclass for a .bc file [Forcing] block with astronomic components data.","title":"Astronomic"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.AstronomicCorrection","text":"Subclass for a .bc file [Forcing] block with astronomic components correction data.","title":"AstronomicCorrection"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.Constant","text":"Subclass for a .bc file [Forcing] block with constant value data.","title":"Constant"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.ForcingBase","text":"The base class of a single [Forcing] block in a .bc forcings file. Typically subclassed, for the specific types of forcing data, e.g, Harmonic. This model is for example referenced under a ForcingModel .forcing[..] .","title":"ForcingBase"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.ForcingBase.__repr__","text":"Return repr(self). Source code in hydrolib/core/dflowfm/bc/models.py def __repr__ ( self ) -> str : data = dict ( self ) data [ \"datablock\" ] = \"\" representable = BaseModel . construct ( ** data ) return str ( representable )","title":"__repr__()"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.ForcingBase.validate","text":"Try to initialize subclass based on the function field. This field is compared to each function field of the derived models of ForcingBase or models derived from derived models. The derived model with an equal function type will be initialized. Exceptions: Type Description ValueError When the given type is not a known structure type. Source code in hydrolib/core/dflowfm/bc/models.py @classmethod def validate ( cls , v ): \"\"\"Try to initialize subclass based on the `function` field. This field is compared to each `function` field of the derived models of `ForcingBase` or models derived from derived models. The derived model with an equal function type will be initialized. Raises: ValueError: When the given type is not a known structure type. \"\"\" # should be replaced by discriminated unions once merged # https://github.com/samuelcolvin/pydantic/pull/2336 if isinstance ( v , dict ): function_string = v . get ( \"function\" , \"\" ) . lower () function_type = get_type_based_on_subclass_default_value ( cls , \"function\" , function_string ) if function_type is not None : return function_type ( ** v ) else : raise ValueError ( f \"Function of { cls . __name__ } with name= { v . get ( 'name' , '' ) } and function= { v . get ( 'function' , '' ) } is not recognized.\" ) return v","title":"validate()"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.ForcingData","text":"Data type that selects from three different types of forcing data: * a scalar float constant * \"realtime\" keyword, indicating externally controlled. * A ForcingModel coming from a .bc file.","title":"ForcingData"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.ForcingGeneral","text":"[General] section with .bc file metadata.","title":"ForcingGeneral"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.ForcingModel","text":"The overall model that contains the contents of one .bc forcings file. This model is for example referenced under a ExtModel .boundary[..].forcingfile[..] .","title":"ForcingModel"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.Harmonic","text":"Subclass for a .bc file [Forcing] block with harmonic components data.","title":"Harmonic"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.HarmonicCorrection","text":"Subclass for a .bc file [Forcing] block with harmonic components correction data.","title":"HarmonicCorrection"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.QHTable","text":"Subclass for a .bc file [Forcing] block with Q-h table data.","title":"QHTable"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.QuantityUnitPair","text":"A .bc file header lines tuple containing a quantity name, its unit and optionally a vertical position index.","title":"QuantityUnitPair"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.RealTime","text":"Enum class containing the valid value for the \"realtime\" reserved keyword for real-time controlled forcing data, e.g., for hydraulic structures. This class is used inside the ForcingData Union, to force detection of the realtime keyword, prior to considering it a filename.","title":"RealTime"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.RealTime.realtime","text":"str: Realtime data source, externally provided","title":"realtime"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.T3D","text":"Subclass for a .bc file [Forcing] block with 3D timeseries data.","title":"T3D"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.T3D.get_number_of_repetitions","text":"Gets the number of expected quantityunitpairs for each vector element. Defaults to 1. Source code in hydrolib/core/dflowfm/bc/models.py @classmethod def get_number_of_repetitions ( cls , values : Dict ) -> int : verticalpositions = values . get ( \"vertpositions\" ) # Since the renaming root validator may not have been run yet, in this # method we explicitly check old keywords for backwards compatibility: if verticalpositions is None : # try to get the value from any of the older keywords for old_keyword in cls . _keys_to_rename [ \"vertpositions\" ]: verticalpositions = values . get ( old_keyword ) if verticalpositions is not None : break if verticalpositions is None : raise ValueError ( \"vertPositions is not provided\" ) number_of_verticalpositions = ( len ( verticalpositions ) if isinstance ( verticalpositions , List ) else len ( verticalpositions . split ()) ) return number_of_verticalpositions","title":"get_number_of_repetitions()"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.T3D.rename_keys","text":"Renames some old keywords to the currently supported keywords. Source code in hydrolib/core/dflowfm/bc/models.py @root_validator ( allow_reuse = True , pre = True ) def rename_keys ( cls , values : Dict ) -> Dict : \"\"\"Renames some old keywords to the currently supported keywords.\"\"\" return rename_keys_for_backwards_compatibility ( values , cls . _keys_to_rename )","title":"rename_keys()"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.TimeInterpolation","text":"Enum class containing the valid values for the time interpolation.","title":"TimeInterpolation"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.TimeInterpolation.block_from","text":"str: Equal to that at the start of the time interval (latest specified time value).","title":"block_from"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.TimeInterpolation.block_to","text":"str: Equal to that at the end of the time interval (upcoming specified time value).","title":"block_to"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.TimeInterpolation.linear","text":"str: Linear interpolation between times.","title":"linear"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.TimeSeries","text":"Subclass for a .bc file [Forcing] block with timeseries data.","title":"TimeSeries"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.TimeSeries.rename_keys","text":"Renames some old keywords to the currently supported keywords. Source code in hydrolib/core/dflowfm/bc/models.py @root_validator ( allow_reuse = True , pre = True ) def rename_keys ( cls , values : Dict ) -> Dict : \"\"\"Renames some old keywords to the currently supported keywords.\"\"\" return rename_keys_for_backwards_compatibility ( values , { \"timeinterpolation\" : [ \"time_interpolation\" ], }, )","title":"rename_keys()"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VectorForcingBase","text":"The base class of a single [Forcing] block that supports vectors in a .bc forcings file.","title":"VectorForcingBase"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VectorForcingBase.get_number_of_repetitions","text":"Gets the number of expected quantityunitpairs for each vector element. Defaults to 1. Source code in hydrolib/core/dflowfm/bc/models.py @classmethod def get_number_of_repetitions ( cls , values : Dict ) -> int : \"\"\"Gets the number of expected quantityunitpairs for each vector element. Defaults to 1.\"\"\" return 1","title":"get_number_of_repetitions()"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VectorForcingBase.validate_and_update_quantityunitpairs","text":"Validates and, if required, updates vector quantity unit pairs. Parameters: Name Type Description Default values Dict Dictionary of values to be used to validate or required Exceptions: Type Description ValueError When a quantity unit pair is found in a vector where it does not belong. ValueError When the number of quantity unit pairs in a vectors is not as expected. Returns: Type Description Dict Dictionary of validates values. Source code in hydrolib/core/dflowfm/bc/models.py @root_validator ( pre = True ) def validate_and_update_quantityunitpairs ( cls , values : Dict ) -> Dict : \"\"\" Validates and, if required, updates vector quantity unit pairs. Args: values (Dict): Dictionary of values to be used to validate or update vector quantity unit pairs. Raises: ValueError: When a quantity unit pair is found in a vector where it does not belong. ValueError: When the number of quantity unit pairs in a vectors is not as expected. Returns: Dict: Dictionary of validates values. \"\"\" quantityunitpairs = values [ \"quantityunitpair\" ] vector = values . get ( \"vector\" ) number_of_element_repetitions = cls . get_number_of_repetitions ( values ) VectorForcingBase . _process_vectordefinition_or_check_quantityunitpairs ( vector , quantityunitpairs , number_of_element_repetitions ) return values","title":"validate_and_update_quantityunitpairs()"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VectorQuantityUnitPairs","text":"A subset of .bc file header lines containing a vector quantity definition, followed by all component quantity names, their unit and optionally their vertical position indexes.","title":"VectorQuantityUnitPairs"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VectorQuantityUnitPairs.__str__","text":"Return str(self). Source code in hydrolib/core/dflowfm/bc/models.py def __str__ ( self ) -> str : return VectorQuantityUnitPairs . _to_vectordefinition_string ( self . vectorname , self . elementname )","title":"__str__()"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VerticalInterpolation","text":"Enum class containing the valid values for the vertical position type, which defines what the numeric values for vertical position specification mean.","title":"VerticalInterpolation"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VerticalInterpolation.block","text":"str: Equal to the value at the directly lower specified vertical position.","title":"block"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VerticalInterpolation.linear","text":"str: Linear interpolation between vertical positions.","title":"linear"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VerticalInterpolation.log","text":"str: Logarithmic interpolation between vertical positions (e.g. vertical velocity profiles).","title":"log"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VerticalPositionType","text":"Enum class containing the valid values for the vertical position type.","title":"VerticalPositionType"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VerticalPositionType.percentage_bed","text":"str: Percentage with respect to the water depth from the bed upward.","title":"percentage_bed"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VerticalPositionType.z_bed","text":"str: Absolute distance from the bed upward.","title":"z_bed"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VerticalPositionType.z_datum","text":"str: z-coordinate with respect to the reference level of the model.","title":"z_datum"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VerticalPositionType.z_surf","text":"str: Absolute distance from the free surface downward.","title":"z_surf"},{"location":"reference/friction/","text":"1D roughness .ini files \u00b6 The friction module provides the specific logic for accessing friction/1D roughness files for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. A 1D roughness file is described by the classes below. Model \u00b6 FrictBranch ( INIBasedModel ) pydantic-model \u00b6 A [Branch] block for use inside a friction file. Each block can define the roughness value(s) on a particular branch. FrictGeneral ( INIGeneral ) pydantic-model \u00b6 The friction file's [General] section with file meta data. FrictGlobal ( INIBasedModel ) pydantic-model \u00b6 A [Global] block for use inside a friction file. Multiple of such blocks may be present to define multiple frictionId classes. FrictionModel ( INIModel ) pydantic-model \u00b6 The overall friction model that contains the contents of one friction file. This model is typically referenced under a FMModel .geometry.frictfile[..] . Attributes: Name Type Description general FrictGeneral [General] block with file metadata. global_ List[FrictGlobal] Definitions of [Global] friction classes. branch List[FrictBranch] Definitions of [Branch] friction values. FrictionType ( str , Enum ) \u00b6 Enum class containing the valid values for the frictionType attribute in several subclasses of Structure/CrossSection/friction.models. chezy \u00b6 str: Ch\u00e9zy C [m 1/2 /s] debosbijkerk \u00b6 str: De Bos-Bijkerk \u03b3 [1/s] manning \u00b6 str: Manning n [s/m 1/3 ] strickler \u00b6 str: Strickler k_s [m 1/3 /s] stricklernikuradse \u00b6 str: Nikuradse k_n [m] walllawnikuradse \u00b6 str: Nikuradse k_n [m] whitecolebrook \u00b6 str: Nikuradse k_n [m]","title":"Friction"},{"location":"reference/friction/#1d-roughness-ini-files","text":"The friction module provides the specific logic for accessing friction/1D roughness files for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. A 1D roughness file is described by the classes below.","title":"1D roughness .ini files"},{"location":"reference/friction/#model","text":"","title":"Model"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictBranch","text":"A [Branch] block for use inside a friction file. Each block can define the roughness value(s) on a particular branch.","title":"FrictBranch"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictGeneral","text":"The friction file's [General] section with file meta data.","title":"FrictGeneral"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictGlobal","text":"A [Global] block for use inside a friction file. Multiple of such blocks may be present to define multiple frictionId classes.","title":"FrictGlobal"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictionModel","text":"The overall friction model that contains the contents of one friction file. This model is typically referenced under a FMModel .geometry.frictfile[..] . Attributes: Name Type Description general FrictGeneral [General] block with file metadata. global_ List[FrictGlobal] Definitions of [Global] friction classes. branch List[FrictBranch] Definitions of [Branch] friction values.","title":"FrictionModel"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictionType","text":"Enum class containing the valid values for the frictionType attribute in several subclasses of Structure/CrossSection/friction.models.","title":"FrictionType"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictionType.chezy","text":"str: Ch\u00e9zy C [m 1/2 /s]","title":"chezy"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictionType.debosbijkerk","text":"str: De Bos-Bijkerk \u03b3 [1/s]","title":"debosbijkerk"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictionType.manning","text":"str: Manning n [s/m 1/3 ]","title":"manning"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictionType.strickler","text":"str: Strickler k_s [m 1/3 /s]","title":"strickler"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictionType.stricklernikuradse","text":"str: Nikuradse k_n [m]","title":"stricklernikuradse"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictionType.walllawnikuradse","text":"str: Nikuradse k_n [m]","title":"walllawnikuradse"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictionType.whitecolebrook","text":"str: Nikuradse k_n [m]","title":"whitecolebrook"},{"location":"reference/glossary/","text":"Glossary \u00b6 The list below is a nonexhaustive list of terminology and concepts used in HYDROLIB(-core) and Delft3D Flexible Mesh. A \u00b6 B \u00b6 BC file \u00b6 Input file containing the actual forcing data for model forcings specified elsewhere in the model input, for example time series or astronomical components. Originates from boundary conditions as specified in the external forcings file , but nowadays also used in structure files . More details about the syntax and the various supported function types in the Delft3D FM User Manual . Boundary condition \u00b6 Flow (or constituent) boundary condition that forces a D-Flow FM model, such as waterlevel and discharge boundary conditions. Defined in the external forcings file . More details in the Delft3D FM User Manual . Branch \u00b6 The network edges in a network topology of 1D models. The computational grid points are positioned on these branches using branch id and a chainage value. Branch Id \u00b6 Identification text string for a particular branch in a 1D network. C \u00b6 Chainage \u00b6 The distance along a 1D network branch to define a specific location on that branch. Always used in combination with a branch Id . CF conventions \u00b6 Established metadata conventions for storing all kinds of data, e.g., model input and output, in NetCDF files. More details on: https://cfconventions.org/. HYDROLIB-core and Delft3D Flexible Mesh rely on CF, and extend this with UGRID conventions where unstructured grids are applicable. Computational backend \u00b6 Computational core, also called kernel. The program/library of simulation software that does the actual calculations. Often also available with a graphical user interface on top of it. Cross section files \u00b6 Input files for D-Flow FM that define the 1D network's cross sections. Two parts: cross section definition file and cross section location files . Not to be confused with observation cross section files ! Cross section definition file \u00b6 Input file for D-Flow FM that defines the various cross section shapes in a model with a 1D network. Format is INI-like. More details in the Delft3D FM User Manual . Cross section location file \u00b6 Input file for D-Flow FM that defines the location of cross section shapes in a model with a 1D network. Each location refers to a (possible shared) cross section definition . Format is INI-like. More details in the Delft3D FM User Manual . D \u00b6 Deltares conventions \u00b6 A proposal for additional NetCDF conventions that build on the existing UGRID conventions , intended to properly describe 1D network topologies as a coordinate space on which 1D computational grids are defined. Also 1D2D grid couplings are included. More details in: the Delft3D FM User Manual . D-Flow FM \u00b6 D-Flow Flexible Mesh. The computational backend that solves 1D/2D/3D hydrodynamics in the Delf3D Flexible Mesh Suite. Toplevel input is the MDU file . More details in the Delft3D FM User Manual . D-HYDRO Suite 1D2D (Beta) \u00b6 Integral software suite for hydraulic 1D2D modelling, including rainfall runoff and realtime control. More details on: https://www.deltares.nl/nl/d-hydro-suite-1d2d-beta/. DIMR \u00b6 Deltares Integrated Model Runner. Executable/library that runs integrated models by coupling multiple computational backends in a simulation timeloop. Uses a single DIMR config file as input. DIMR config file \u00b6 Input file for DIMR (typically dimr_config.xml ) for an integrated model run, describing which models are coupled and which quantities need to be exchanged. E \u00b6 Edge (mesh) \u00b6 A geometrical \"line\" in a 1D, 2D or 3D mesh. Connects two mesh nodes as its end points. Building block of the UGRID-conventions . External forcings file \u00b6 Input file for D-Flow FM describing model forcings such as boundary conditions , laterals and meteo . Format is INI-like. More details in the Delft3D FM User Manual . F \u00b6 Face (mesh) \u00b6 A geometrical \"cell\" in a 2D mesh. Formed by 3 or more mesh nodes as its vertices. Building block of the UGRID-conventions . Flow link \u00b6 An open connection/interface between two flow nodes in the staggered D-Flow FM model grid. Is the same as a \"velocity point\", and corresponds with (but is not equal to) an edge , both in 1D and in 2D. In 3D a flow link corresponds with a 3D face between two volumes . Flow node \u00b6 A single finite volume \"cell\" in the staggered D-Flow FM model grid. Is the same as a \"pressure point\", and is in fact a face in 2D/3D or a node in 1D. G \u00b6 Grid \u00b6 The computational grid on which a flow simulation is done. The grid for D-Flow FM is defined in an input net file , and also appears (slightly differently) in the output map file . Grid snapping \u00b6 The snapping of D-Flow FM model input in x,y-coordinates to discrete locations in the staggered model grid . This process makes most model input independent of the chosen model grid and grid resolution. Snapping is done either to (sets of) flow nodes or (sequence of) flow links , depending on whether pressure-point data or velocity-point data is concerned. H \u00b6 His file \u00b6 Output file of D-Flow FM containing model results as time series on a specific set of discrete locations, which are typically the hydraulic structures, observation stations and more. More details in the Delft3D FM User Manual . I \u00b6 Integrated model \u00b6 Model consisting of more than one model. Typically used when multiple computational backends are coupled, for example D-Flow FM and Rainfall Runoff or D-Flow FM and Real Time Control . Integrated models can be run using the Deltares Integrated Model Runner (DIMR) . INI-files \u00b6 Delft3D FM uses several input files that are formatted in an INI-like syntax. The abstract syntax depends on the particular file type, see: cross section files , initial field file , external forcings file , MDU file , observation files , rougness file , structure file . Initial field file \u00b6 Input file for D-Flow FM describing initial conditions and other spatially varying parameter fields. Format is INI-like. More details in the Delft3D FM User Manual . J \u00b6 K \u00b6 L \u00b6 Lateral \u00b6 Lateral discharge in D-Flow FM , which acts as a source (or sink) of volume. Defined in the external forcings file . The actual forcing data may come from timeseries in a .bc file or from RR a coupled/integrated model. More details in the Delft3D FM User Manual . M \u00b6 Map file \u00b6 Output file of D-Flow FM containing the model results on all grid points. More details in the Delft3D FM User Manual . MDU file \u00b6 Main input file of D-Flow FM . Format is INI-like. More details in the Delft3D FM User Manual . meteo \u00b6 Meteorological forcings of a model. Typically sources (or sinks) of volume via precipitation and evaporation, or forcing via wind. For D-Flow FM defined in the external forcings file . More details in the Delft3D FM User Manual . mesh \u00b6 See grid . N \u00b6 Net file \u00b6 Or grid file. Input file for D-Flow FM containing the computational model grid. Format is NetCDF, adhering to CF - and UGRID -conventions, and optionally also the Deltares-extension for 1D network topology and geometry. NetCDF \u00b6 File format used by HYDROLIB-core and Delft3D Flexible Mesh for the model input grid and for model results in output files. These files typically adhere to the CF conventions and sometimes UGRID conventions . Node (mesh) \u00b6 A geometrical \"point\" in a 1D, 2D or 3D mesh. Defined by x- and y-coordinate, in 3D also a z-coordinate. Can be connected by mesh edges , and can form the vertices of a mesh face . Building block of the UGRID-conventions . O \u00b6 Observation files \u00b6 Files that define the model locations for which output should be produced in the his file . Two types: observation point file and observation cross section file . Observation cross section file \u00b6 Input file for D-Flow FM that describes the model locations for which (cumulative) flow \"flux\" output should be produced in the his file . For example: cumulative discharge, salinity transport. Applies both to 1D, 2D, 1D2D and 3D models. Format is INI-like. More details in the Delft3D FM User Manual . Observation point file \u00b6 Input file for D-Flow FM that describes the model point locations for which local output should be produced in the his file . For example: waterlevel, velocity vector/magnitude, tracer concentration as instantanous values. Applies both to 1D, 2D, 1D2D and 3D models. Format is INI-like. More details in the Delft3D FM User Manual . P \u00b6 Polyline file \u00b6 File containing a sequence of polylines in model coordinates. Each polyline has header lines with a label and row+column count, and at least a list of x, y-points. More than 2 columns may be present (z, data1, ...) for particular model inputs, see for example the fixed weir file . More details in the Delft3D FM User Manual . Polygon file \u00b6 See polyline file . The point sequences are interpreted as closed polygons. Q \u00b6 R \u00b6 Rainfall Runoff \u00b6 RR for short. The computational backend that solves lumped rainfall runoff, offering various runoff concepts. Toplevel input is the sobek_3b.fnm file. Part of the D-Hydrology software module. More details on: https://www.deltares.nl/en/software/module/d-hydrology . Real Time Control \u00b6 RTC for short. The computational backend for real-time control of hydraulic model components (typically hydraulic structures). Toplevel input is in various rtc*.xml files. Part of the D-Real Time Control software module. More details on: https://www.deltares.nl/en/software/module/d-real-time-control . Roughness file \u00b6 Input file for D-Flow FM describing roughness values on the 1D network. Format is INI-like. More details in the Delft3D FM User Manual . S \u00b6 Sample file \u00b6 File containing an unstructured set of sample point values. Typically used as input file for initial fields or other spatially varying fields in the initial fields file . More details in the Delft3D FM User Manual . Staggered grid \u00b6 Discretization method used in D-Flow FM where the PDE variables are not all defined on the same topological grid locations. Water level, concentrations and other volume-related variables are defined on the pressure points (also: flow nodes ), and the fluxes and other transport-related variables are defined on the velocity points (also: flow links ). Structure file \u00b6 Input file for D-Flow FM containing the hydraulic structures. Format is INI-like. More details in the Delft3D FM User Manual . T \u00b6 U \u00b6 UGRID conventions \u00b6 Metadata conventions for storing unstructured grids in NetCDF files. More details on: http://ugrid-conventions.github.io/ugrid-conventions/ . V \u00b6 volume (mesh) \u00b6 A geometrical \"cell\" in a 3D mesh. Formed by 4 or more mesh nodes as its vertices (or: 4 or more mesh faces as its \"sides\"). Building block of the UGRID-conventions . W \u00b6 X \u00b6 XYZ file \u00b6 See sample file . Y \u00b6 Z \u00b6","title":"Glossary"},{"location":"reference/glossary/#glossary","text":"The list below is a nonexhaustive list of terminology and concepts used in HYDROLIB(-core) and Delft3D Flexible Mesh.","title":"Glossary"},{"location":"reference/glossary/#a","text":"","title":"A"},{"location":"reference/glossary/#b","text":"","title":"B"},{"location":"reference/glossary/#bc-file","text":"Input file containing the actual forcing data for model forcings specified elsewhere in the model input, for example time series or astronomical components. Originates from boundary conditions as specified in the external forcings file , but nowadays also used in structure files . More details about the syntax and the various supported function types in the Delft3D FM User Manual .","title":"BC file"},{"location":"reference/glossary/#boundary-condition","text":"Flow (or constituent) boundary condition that forces a D-Flow FM model, such as waterlevel and discharge boundary conditions. Defined in the external forcings file . More details in the Delft3D FM User Manual .","title":"Boundary condition"},{"location":"reference/glossary/#branch","text":"The network edges in a network topology of 1D models. The computational grid points are positioned on these branches using branch id and a chainage value.","title":"Branch"},{"location":"reference/glossary/#branch-id","text":"Identification text string for a particular branch in a 1D network.","title":"Branch Id"},{"location":"reference/glossary/#c","text":"","title":"C"},{"location":"reference/glossary/#chainage","text":"The distance along a 1D network branch to define a specific location on that branch. Always used in combination with a branch Id .","title":"Chainage"},{"location":"reference/glossary/#cf-conventions","text":"Established metadata conventions for storing all kinds of data, e.g., model input and output, in NetCDF files. More details on: https://cfconventions.org/. HYDROLIB-core and Delft3D Flexible Mesh rely on CF, and extend this with UGRID conventions where unstructured grids are applicable.","title":"CF conventions"},{"location":"reference/glossary/#computational-backend","text":"Computational core, also called kernel. The program/library of simulation software that does the actual calculations. Often also available with a graphical user interface on top of it.","title":"Computational backend"},{"location":"reference/glossary/#cross-section-files","text":"Input files for D-Flow FM that define the 1D network's cross sections. Two parts: cross section definition file and cross section location files . Not to be confused with observation cross section files !","title":"Cross section files"},{"location":"reference/glossary/#cross-section-definition-file","text":"Input file for D-Flow FM that defines the various cross section shapes in a model with a 1D network. Format is INI-like. More details in the Delft3D FM User Manual .","title":"Cross section definition file"},{"location":"reference/glossary/#cross-section-location-file","text":"Input file for D-Flow FM that defines the location of cross section shapes in a model with a 1D network. Each location refers to a (possible shared) cross section definition . Format is INI-like. More details in the Delft3D FM User Manual .","title":"Cross section location file"},{"location":"reference/glossary/#d","text":"","title":"D"},{"location":"reference/glossary/#deltares-conventions","text":"A proposal for additional NetCDF conventions that build on the existing UGRID conventions , intended to properly describe 1D network topologies as a coordinate space on which 1D computational grids are defined. Also 1D2D grid couplings are included. More details in: the Delft3D FM User Manual .","title":"Deltares conventions"},{"location":"reference/glossary/#d-flow-fm","text":"D-Flow Flexible Mesh. The computational backend that solves 1D/2D/3D hydrodynamics in the Delf3D Flexible Mesh Suite. Toplevel input is the MDU file . More details in the Delft3D FM User Manual .","title":"D-Flow FM"},{"location":"reference/glossary/#d-hydro-suite-1d2d-beta","text":"Integral software suite for hydraulic 1D2D modelling, including rainfall runoff and realtime control. More details on: https://www.deltares.nl/nl/d-hydro-suite-1d2d-beta/.","title":"D-HYDRO Suite 1D2D (Beta)"},{"location":"reference/glossary/#dimr","text":"Deltares Integrated Model Runner. Executable/library that runs integrated models by coupling multiple computational backends in a simulation timeloop. Uses a single DIMR config file as input.","title":"DIMR"},{"location":"reference/glossary/#dimr-config-file","text":"Input file for DIMR (typically dimr_config.xml ) for an integrated model run, describing which models are coupled and which quantities need to be exchanged.","title":"DIMR config file"},{"location":"reference/glossary/#e","text":"","title":"E"},{"location":"reference/glossary/#edge-mesh","text":"A geometrical \"line\" in a 1D, 2D or 3D mesh. Connects two mesh nodes as its end points. Building block of the UGRID-conventions .","title":"Edge (mesh)"},{"location":"reference/glossary/#external-forcings-file","text":"Input file for D-Flow FM describing model forcings such as boundary conditions , laterals and meteo . Format is INI-like. More details in the Delft3D FM User Manual .","title":"External forcings file"},{"location":"reference/glossary/#f","text":"","title":"F"},{"location":"reference/glossary/#face-mesh","text":"A geometrical \"cell\" in a 2D mesh. Formed by 3 or more mesh nodes as its vertices. Building block of the UGRID-conventions .","title":"Face (mesh)"},{"location":"reference/glossary/#flow-link","text":"An open connection/interface between two flow nodes in the staggered D-Flow FM model grid. Is the same as a \"velocity point\", and corresponds with (but is not equal to) an edge , both in 1D and in 2D. In 3D a flow link corresponds with a 3D face between two volumes .","title":"Flow link"},{"location":"reference/glossary/#flow-node","text":"A single finite volume \"cell\" in the staggered D-Flow FM model grid. Is the same as a \"pressure point\", and is in fact a face in 2D/3D or a node in 1D.","title":"Flow node"},{"location":"reference/glossary/#g","text":"","title":"G"},{"location":"reference/glossary/#grid","text":"The computational grid on which a flow simulation is done. The grid for D-Flow FM is defined in an input net file , and also appears (slightly differently) in the output map file .","title":"Grid"},{"location":"reference/glossary/#grid-snapping","text":"The snapping of D-Flow FM model input in x,y-coordinates to discrete locations in the staggered model grid . This process makes most model input independent of the chosen model grid and grid resolution. Snapping is done either to (sets of) flow nodes or (sequence of) flow links , depending on whether pressure-point data or velocity-point data is concerned.","title":"Grid snapping"},{"location":"reference/glossary/#h","text":"","title":"H"},{"location":"reference/glossary/#his-file","text":"Output file of D-Flow FM containing model results as time series on a specific set of discrete locations, which are typically the hydraulic structures, observation stations and more. More details in the Delft3D FM User Manual .","title":"His file"},{"location":"reference/glossary/#i","text":"","title":"I"},{"location":"reference/glossary/#integrated-model","text":"Model consisting of more than one model. Typically used when multiple computational backends are coupled, for example D-Flow FM and Rainfall Runoff or D-Flow FM and Real Time Control . Integrated models can be run using the Deltares Integrated Model Runner (DIMR) .","title":"Integrated model"},{"location":"reference/glossary/#ini-files","text":"Delft3D FM uses several input files that are formatted in an INI-like syntax. The abstract syntax depends on the particular file type, see: cross section files , initial field file , external forcings file , MDU file , observation files , rougness file , structure file .","title":"INI-files"},{"location":"reference/glossary/#initial-field-file","text":"Input file for D-Flow FM describing initial conditions and other spatially varying parameter fields. Format is INI-like. More details in the Delft3D FM User Manual .","title":"Initial field file"},{"location":"reference/glossary/#j","text":"","title":"J"},{"location":"reference/glossary/#k","text":"","title":"K"},{"location":"reference/glossary/#l","text":"","title":"L"},{"location":"reference/glossary/#lateral","text":"Lateral discharge in D-Flow FM , which acts as a source (or sink) of volume. Defined in the external forcings file . The actual forcing data may come from timeseries in a .bc file or from RR a coupled/integrated model. More details in the Delft3D FM User Manual .","title":"Lateral"},{"location":"reference/glossary/#m","text":"","title":"M"},{"location":"reference/glossary/#map-file","text":"Output file of D-Flow FM containing the model results on all grid points. More details in the Delft3D FM User Manual .","title":"Map file"},{"location":"reference/glossary/#mdu-file","text":"Main input file of D-Flow FM . Format is INI-like. More details in the Delft3D FM User Manual .","title":"MDU file"},{"location":"reference/glossary/#meteo","text":"Meteorological forcings of a model. Typically sources (or sinks) of volume via precipitation and evaporation, or forcing via wind. For D-Flow FM defined in the external forcings file . More details in the Delft3D FM User Manual .","title":"meteo"},{"location":"reference/glossary/#mesh","text":"See grid .","title":"mesh"},{"location":"reference/glossary/#n","text":"","title":"N"},{"location":"reference/glossary/#net-file","text":"Or grid file. Input file for D-Flow FM containing the computational model grid. Format is NetCDF, adhering to CF - and UGRID -conventions, and optionally also the Deltares-extension for 1D network topology and geometry.","title":"Net file"},{"location":"reference/glossary/#netcdf","text":"File format used by HYDROLIB-core and Delft3D Flexible Mesh for the model input grid and for model results in output files. These files typically adhere to the CF conventions and sometimes UGRID conventions .","title":"NetCDF"},{"location":"reference/glossary/#node-mesh","text":"A geometrical \"point\" in a 1D, 2D or 3D mesh. Defined by x- and y-coordinate, in 3D also a z-coordinate. Can be connected by mesh edges , and can form the vertices of a mesh face . Building block of the UGRID-conventions .","title":"Node (mesh)"},{"location":"reference/glossary/#o","text":"","title":"O"},{"location":"reference/glossary/#observation-files","text":"Files that define the model locations for which output should be produced in the his file . Two types: observation point file and observation cross section file .","title":"Observation files"},{"location":"reference/glossary/#observation-cross-section-file","text":"Input file for D-Flow FM that describes the model locations for which (cumulative) flow \"flux\" output should be produced in the his file . For example: cumulative discharge, salinity transport. Applies both to 1D, 2D, 1D2D and 3D models. Format is INI-like. More details in the Delft3D FM User Manual .","title":"Observation cross section file"},{"location":"reference/glossary/#observation-point-file","text":"Input file for D-Flow FM that describes the model point locations for which local output should be produced in the his file . For example: waterlevel, velocity vector/magnitude, tracer concentration as instantanous values. Applies both to 1D, 2D, 1D2D and 3D models. Format is INI-like. More details in the Delft3D FM User Manual .","title":"Observation point file"},{"location":"reference/glossary/#p","text":"","title":"P"},{"location":"reference/glossary/#polyline-file","text":"File containing a sequence of polylines in model coordinates. Each polyline has header lines with a label and row+column count, and at least a list of x, y-points. More than 2 columns may be present (z, data1, ...) for particular model inputs, see for example the fixed weir file . More details in the Delft3D FM User Manual .","title":"Polyline file"},{"location":"reference/glossary/#polygon-file","text":"See polyline file . The point sequences are interpreted as closed polygons.","title":"Polygon file"},{"location":"reference/glossary/#q","text":"","title":"Q"},{"location":"reference/glossary/#r","text":"","title":"R"},{"location":"reference/glossary/#rainfall-runoff","text":"RR for short. The computational backend that solves lumped rainfall runoff, offering various runoff concepts. Toplevel input is the sobek_3b.fnm file. Part of the D-Hydrology software module. More details on: https://www.deltares.nl/en/software/module/d-hydrology .","title":"Rainfall Runoff"},{"location":"reference/glossary/#real-time-control","text":"RTC for short. The computational backend for real-time control of hydraulic model components (typically hydraulic structures). Toplevel input is in various rtc*.xml files. Part of the D-Real Time Control software module. More details on: https://www.deltares.nl/en/software/module/d-real-time-control .","title":"Real Time Control"},{"location":"reference/glossary/#roughness-file","text":"Input file for D-Flow FM describing roughness values on the 1D network. Format is INI-like. More details in the Delft3D FM User Manual .","title":"Roughness file"},{"location":"reference/glossary/#s","text":"","title":"S"},{"location":"reference/glossary/#sample-file","text":"File containing an unstructured set of sample point values. Typically used as input file for initial fields or other spatially varying fields in the initial fields file . More details in the Delft3D FM User Manual .","title":"Sample file"},{"location":"reference/glossary/#staggered-grid","text":"Discretization method used in D-Flow FM where the PDE variables are not all defined on the same topological grid locations. Water level, concentrations and other volume-related variables are defined on the pressure points (also: flow nodes ), and the fluxes and other transport-related variables are defined on the velocity points (also: flow links ).","title":"Staggered grid"},{"location":"reference/glossary/#structure-file","text":"Input file for D-Flow FM containing the hydraulic structures. Format is INI-like. More details in the Delft3D FM User Manual .","title":"Structure file"},{"location":"reference/glossary/#t","text":"","title":"T"},{"location":"reference/glossary/#u","text":"","title":"U"},{"location":"reference/glossary/#ugrid-conventions","text":"Metadata conventions for storing unstructured grids in NetCDF files. More details on: http://ugrid-conventions.github.io/ugrid-conventions/ .","title":"UGRID conventions"},{"location":"reference/glossary/#v","text":"","title":"V"},{"location":"reference/glossary/#volume-mesh","text":"A geometrical \"cell\" in a 3D mesh. Formed by 4 or more mesh nodes as its vertices (or: 4 or more mesh faces as its \"sides\"). Building block of the UGRID-conventions .","title":"volume (mesh)"},{"location":"reference/glossary/#w","text":"","title":"W"},{"location":"reference/glossary/#x","text":"","title":"X"},{"location":"reference/glossary/#xyz-file","text":"See sample file .","title":"XYZ file"},{"location":"reference/glossary/#y","text":"","title":"Y"},{"location":"reference/glossary/#z","text":"","title":"Z"},{"location":"reference/gui/","text":"GUI files \u00b6 The GUI module provides the logic to create and validate GUI specific models for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. A .gui file is described by the classes below. GUI models \u00b6 namespace for storing the branches as branches.gui file Branch ( INIBasedModel ) pydantic-model \u00b6 A branch that is included in the branches.gui file. BranchGeneral ( INIGeneral ) pydantic-model \u00b6 The branches.gui file's [General] section with file meta data. BranchModel ( INIModel ) pydantic-model \u00b6 The overall branch model that contains the contents of one branches.gui file. This model is not referenced under a FMModel . Attributes: Name Type Description general BranchGeneral [General] block with file metadata. branch(List[Branch]) List of [Branch] blocks for all branches.","title":"GUI files"},{"location":"reference/gui/#gui-files","text":"The GUI module provides the logic to create and validate GUI specific models for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. A .gui file is described by the classes below.","title":"GUI files"},{"location":"reference/gui/#gui-models","text":"namespace for storing the branches as branches.gui file","title":"GUI models"},{"location":"reference/gui/#hydrolib.core.dflowfm.gui.models.Branch","text":"A branch that is included in the branches.gui file.","title":"Branch"},{"location":"reference/gui/#hydrolib.core.dflowfm.gui.models.BranchGeneral","text":"The branches.gui file's [General] section with file meta data.","title":"BranchGeneral"},{"location":"reference/gui/#hydrolib.core.dflowfm.gui.models.BranchModel","text":"The overall branch model that contains the contents of one branches.gui file. This model is not referenced under a FMModel . Attributes: Name Type Description general BranchGeneral [General] block with file metadata. branch(List[Branch]) List of [Branch] blocks for all branches.","title":"BranchModel"},{"location":"reference/ini/","text":"INI format \u00b6 The ini module provides the generic logic for parsing Deltares ini based files, such as the mdu, structures files, as well as more complex files such as the boundary condition (bc) files. Note that specific attribute files that employ this ini format often have their own dedicated module (and separate API doc page). These include: MDU file ( hydrolib.core.dflowfm.mdu ) External forcing file ( hydrolib.core.dflowfm.ext ) Initial fields and parameter file ( hydrolib.core.dflowfm.inifield ) Structure file ( hydrolib.core.dflowfm.structure ) 1D roughness ( hydrolib.core.dflowfm.friction ) Cross section files ( hydrolib.core.dflowfm.crosssection ) Storage node file ( hydrolib.core.dflowfm.storagenode ) Following below is the documentation for the INI format base classes. Model \u00b6 DataBlockINIBasedModel ( INIBasedModel ) pydantic-model \u00b6 DataBlockINIBasedModel defines the base model for ini models with datablocks. Attributes: Name Type Description datablock Datablock (class attribute) the actual data columns. INIBasedModel ( BaseModel , ABC ) pydantic-model \u00b6 INIBasedModel defines the base model for blocks/chapters inside an INIModel (*.ini file). INIBasedModel instances can be created from Section instances obtained through parsing ini documents. It further supports adding arbitrary fields to it, which will be written to file. Lastly, no arbitrary types are allowed for the defined fields. Attributes: Name Type Description comments Optional[Comments] Optional Comments if defined by the user, containing descriptions for all data fields. Comments ( BaseModel , ABC ) pydantic-model \u00b6 Comments defines the comments of an INIBasedModel get_list_delimiter () -> str classmethod \u00b6 List delimiter string that will be used for serializing list field values for any IniBasedModel, if that field has no custom list delimiter. This function should be overridden by any subclass for a particular filetype that needs a specific/different list separator. Source code in hydrolib/core/dflowfm/ini/models.py @classmethod def get_list_delimiter ( cls ) -> str : \"\"\"List delimiter string that will be used for serializing list field values for any IniBasedModel, **if** that field has no custom list delimiter. This function should be overridden by any subclass for a particular filetype that needs a specific/different list separator. \"\"\" return \" \" get_list_field_delimiter ( field_key : str ) -> str classmethod \u00b6 List delimiter string that will be used for serializing the given field's value. The returned delimiter is either the field's custom list delimiter if that was specified using Field(.., delimiter=\"..\"), or the default list delimiter for the model class that this field belongs to. Parameters: Name Type Description Default field_key str the original field key (not its alias). required Source code in hydrolib/core/dflowfm/ini/models.py @classmethod def get_list_field_delimiter ( cls , field_key : str ) -> str : \"\"\"List delimiter string that will be used for serializing the given field's value. The returned delimiter is either the field's custom list delimiter if that was specified using Field(.., delimiter=\"..\"), or the default list delimiter for the model class that this field belongs to. Args: field_key (str): the original field key (not its alias). \"\"\" delimiter = None if ( field := cls . __fields__ . get ( field_key )) and isinstance ( field , ModelField ): delimiter = field . field_info . extra . get ( \"delimiter\" ) if not delimiter : delimiter = cls . get_list_delimiter () return delimiter INIModel ( ParsableFileModel ) pydantic-model \u00b6 INI Model representation of a *.ini file. Typically subclasses will implement the various sorts of ini files, specifically for their fileType/contents. Child elements of this class associated with chapters/blocks in the ini file will be (sub)class of INIBasedModel. Parser \u00b6 Parser \u00b6 Parser defines a generic Parser for Deltares ini files. The Parser can be configured with a ParserConfig object. __init__ ( self , config : ParserConfig ) -> None special \u00b6 Creates a new Parser configured with the provided config Parameters: Name Type Description Default config ParserConfig The configuration of this Parser required Source code in hydrolib/core/dflowfm/ini/parser.py def __init__ ( self , config : ParserConfig ) -> None : \"\"\"Creates a new Parser configured with the provided config Args: config (ParserConfig): The configuration of this Parser \"\"\" self . _config = config self . _document = Document () self . _current_section : Optional [ _IntermediateSection ] = None self . _current_header_block : Optional [ _IntermediateCommentBlock ] = None self . _state = self . _StateType . NO_SECTION_FOUND self . _line_index = 0 # TODO add invalid blocks self . _feed_line : Dict [ Parser . _StateType , List [ Tuple [ Callable [[ str ], bool ], Callable [[ str ], None ]]] ] = { Parser . _StateType . NO_SECTION_FOUND : [ ( self . _is_comment , self . _handle_header_comment ), ( self . _is_section_header , self . _handle_next_section_header ), ], Parser . _StateType . PARSING_PROPERTIES : [ ( self . _is_comment , self . _handle_section_comment ), ( self . _is_section_header , self . _handle_next_section_header ), ( self . _is_property , self . _handle_property ), ( self . _is_datarow , self . _handle_new_datarow ), ], Parser . _StateType . PARSING_DATABLOCK : [ ( self . _is_section_header , self . _handle_next_section_header ), ( self . _is_datarow , self . _handle_datarow ), ], } self . _handle_emptyline : Dict [ Parser . _StateType , Callable [[], None ]] = { self . _StateType . NO_SECTION_FOUND : self . _finish_current_header_block , self . _StateType . PARSING_PROPERTIES : self . _noop , self . _StateType . PARSING_DATABLOCK : self . _noop , } feed_line ( self , line : str ) -> None \u00b6 Parse the next line with this Parser. Parameters: Name Type Description Default line str The line to parse required Source code in hydrolib/core/dflowfm/ini/parser.py def feed_line ( self , line : str ) -> None : \"\"\"Parse the next line with this Parser. Args: line (str): The line to parse \"\"\" if not self . _is_empty_line ( line ): for ( is_line_type , handle_line_type ) in self . _feed_line [ self . _state ]: if is_line_type ( line ): handle_line_type ( line ) break else : # handle exception pass else : self . _handle_emptyline [ self . _state ]() self . _increment_line () finalize ( self ) -> Document \u00b6 Finalize parsing and return the constructed Document. Returns: Type Description Document A Document describing the parsed ini file. Source code in hydrolib/core/dflowfm/ini/parser.py def finalize ( self ) -> Document : \"\"\"Finalize parsing and return the constructed Document. Returns: Document: A Document describing the parsed ini file. \"\"\" # TODO handle invalid block self . _finish_current_header_block () self . _finalise_current_section () return self . _document parse ( filepath : Path , config : ParserConfig = None ) -> Document classmethod \u00b6 Parses an INI file without a specific model type and returns it as a Document. Parameters: Name Type Description Default filepath Path File path to the INI-format file. required config ParserConfig Parser configuration to use. Defaults to None. None Returns: Type Description Document Representation of the parsed INI-file. Source code in hydrolib/core/dflowfm/ini/parser.py @classmethod def parse ( cls , filepath : Path , config : ParserConfig = None ) -> Document : \"\"\" Parses an INI file without a specific model type and returns it as a Document. Args: filepath (Path): File path to the INI-format file. config (ParserConfig, optional): Parser configuration to use. Defaults to None. Returns: Document: Representation of the parsed INI-file. \"\"\" if not config : config = ParserConfig () parser = cls ( config ) progline = re . compile ( r \"^([^#]*=\\s*)([^#]*)(#.*)?\" ) # matches whole line: \"Field = Value Maybe more # optional comment\" progfloat = re . compile ( r \"([\\d.]+)([dD])([+\\-]?\\d{1,3})\" ) # matches a float value: 1d9, 1D-3, 1.D+4, etc. with filepath . open ( encoding = \"utf8\" ) as f : for line in f : # Replace Fortran scientific notation for doubles # Match number d/D +/- number (e.g. 1d-05 or 1.23D+01 or 1.d-4) match = progline . match ( line ) if match : # Only process value line = ( match . group ( 1 ) + progfloat . sub ( r \"\\1e\\3\" , match . group ( 2 )) + str ( match . group ( 3 ) or \"\" ) ) else : # Process full line line = progfloat . sub ( r \"\\1e\\3\" , line ) parser . feed_line ( line ) return parser . finalize () parse_as_dict ( filepath : Path , config : ParserConfig = None ) -> dict classmethod \u00b6 Parses an INI file without a specific model type and returns it as a dictionary. Parameters: Name Type Description Default filepath Path File path to the INI-format file. required config ParserConfig Parser configuration to use. Defaults to None. None Returns: Type Description dict Representation of the parsed INI-file. Source code in hydrolib/core/dflowfm/ini/parser.py @classmethod def parse_as_dict ( cls , filepath : Path , config : ParserConfig = None ) -> dict : \"\"\" Parses an INI file without a specific model type and returns it as a dictionary. Args: filepath (Path): File path to the INI-format file. config (ParserConfig, optional): Parser configuration to use. Defaults to None. Returns: dict: Representation of the parsed INI-file. \"\"\" return cls . parse ( filepath , config ) . flatten () ParserConfig ( BaseModel ) pydantic-model \u00b6 ParserConfig defines the configuration options of the Parser Note that we cannot set both allow_only_keywords and parse_datablocks to True because we cannot distinguish between datablocks and key only properties. As such this will lead to a validation error. Attributes: Name Type Description allow_only_keywords bool Whether to allow properties with only keys (no '=' or value). Defaults to False. parse_datablocks bool Whether to allow parsing of datablocks at the bottom of sections. Defaults to False. parse_comments bool Whether we allow parsing of comments defined with the comment_delimeter. Defaults to True. comment_delimiter str The character or sequence of character used to define a comment. Defaults to '#'. Serializer \u00b6 DataBlockINIBasedSerializerConfig ( INISerializerConfig ) pydantic-model \u00b6 Class that holds the configuration settings for INI files with data blocks serialization. INISerializerConfig ( SerializerConfig ) pydantic-model \u00b6 SerializerConfig defines the configuration options of the Serializer Attributes: Name Type Description section_indent int The number of spaces with which whole sections should be indented. Defaults to 0. property_indent int The number of spaces with which properties should be indented relative to the section header (i.e. the full indent equals the section_indent plus property_indent). Defaults to 4. datablock_indent int The number of spaces with which datablock rows are indented relative to the section header (i.e. the full indent equals the section_indent plus datablock_indent). Defaults to 8. datablock_spacing int The number of spaces between datablock columns. Note that there might be additional offset to ensure . is lined out. Defaults to 2. comment_delimiter str The character used to delimit comments. Defaults to '#'. skip_empty_properties bool Whether or not to skip properties with a value that is empty or None. Defaults to True. total_datablock_indent : int property readonly \u00b6 The combined datablock indentation, i.e. section_indent + datablock_indent total_property_indent : int property readonly \u00b6 The combined property indentation, i.e. section_indent + property_indent MaxLengths ( BaseModel ) pydantic-model \u00b6 MaxLengths defines the maxmimum lengths of the parts of a section Attributes: Name Type Description key int The maximum length of all the keys of the properties within a section. If no properties are present it should be 0. value int The maximum length of all the non None values of the properties within a section. If no properties are present, or all values are None, it should be 0. datablock Optional[Sequence[int]] The maximum length of the values of each column of the Datablock. If no datablock is present it defaults to None. from_section ( section : Section ) -> MaxLengths classmethod \u00b6 Generate a MaxLengths instance from the given Section Parameters: Name Type Description Default section Section The section of which the MaxLengths are calculated required Returns: Type Description MaxLengths The MaxLengths corresponding with the provided section Source code in hydrolib/core/dflowfm/ini/serializer.py @classmethod def from_section ( cls , section : Section ) -> \"MaxLengths\" : \"\"\"Generate a MaxLengths instance from the given Section Args: section (Section): The section of which the MaxLengths are calculated Returns: MaxLengths: The MaxLengths corresponding with the provided section \"\"\" properties = list ( p for p in section . content if isinstance ( p , Property )) keys = ( prop . key for prop in properties ) values = ( prop . value for prop in properties if prop . value is not None ) max_key_length = max (( len ( k ) for k in keys ), default = 0 ) max_value_length = max (( len ( v ) for v in values ), default = 0 ) max_datablock_lengths = MaxLengths . _of_datablock ( section . datablock ) return cls ( key = max_key_length , value = max_value_length , datablock = max_datablock_lengths , ) SectionSerializer \u00b6 SectionSerializer provides the serialize method to serialize a Section The entrypoint of this method is the serialize method, which will construct an actual instance and serializes the Section with it. __init__ ( self , config : INISerializerConfig , max_length : MaxLengths ) special \u00b6 Create a new SectionSerializer Parameters: Name Type Description Default config SerializerConfig The config describing the serialization options required max_length MaxLengths The max lengths of the section being serialized required Source code in hydrolib/core/dflowfm/ini/serializer.py def __init__ ( self , config : INISerializerConfig , max_length : MaxLengths ): \"\"\"Create a new SectionSerializer Args: config (SerializerConfig): The config describing the serialization options max_length (MaxLengths): The max lengths of the section being serialized \"\"\" self . _config = config self . _max_length = max_length config : INISerializerConfig property readonly \u00b6 The SerializerConfig used while serializing the section. max_length : MaxLengths property readonly \u00b6 The MaxLengths of the Section being serialized by this SectionSerializer. serialize ( section : Section , config : INISerializerConfig ) -> Iterable [ str ] classmethod \u00b6 Serialize the provided section with the given config Parameters: Name Type Description Default section Section The section to serialize required config SerializerConfig The config describing the serialization options required Returns: Type Description Lines The iterable lines of the serialized section Source code in hydrolib/core/dflowfm/ini/serializer.py @classmethod def serialize ( cls , section : Section , config : INISerializerConfig ) -> Lines : \"\"\"Serialize the provided section with the given config Args: section (Section): The section to serialize config (SerializerConfig): The config describing the serialization options Returns: Lines: The iterable lines of the serialized section \"\"\" serializer = cls ( config , MaxLengths . from_section ( section )) return serializer . _serialize_section ( section ) Serializer \u00b6 Serializer serializes Document to its corresponding lines. __init__ ( self , config : INISerializerConfig ) special \u00b6 Creates a new Serializer with the provided configuration. Parameters: Name Type Description Default config SerializerConfig The configuration of this Serializer. required Source code in hydrolib/core/dflowfm/ini/serializer.py def __init__ ( self , config : INISerializerConfig ): \"\"\"Creates a new Serializer with the provided configuration. Args: config (SerializerConfig): The configuration of this Serializer. \"\"\" self . _config = config serialize ( self , document : Document ) -> Iterable [ str ] \u00b6 Serialize the provided document into an iterable of lines. Parameters: Name Type Description Default document Document The Document to serialize. required Returns: Type Description Lines An iterable returning each line of the serialized Document. Source code in hydrolib/core/dflowfm/ini/serializer.py def serialize ( self , document : Document ) -> Lines : \"\"\"Serialize the provided document into an iterable of lines. Args: document (Document): The Document to serialize. Returns: Lines: An iterable returning each line of the serialized Document. \"\"\" header_iterable = self . _serialize_document_header ( document . header_comment ) serialize_section = lambda s : SectionSerializer . serialize ( s , self . _config ) sections = ( serialize_section ( section ) for section in document . sections ) sections_with_spacing = Serializer . _interweave ( sections , [ \"\" ]) sections_iterable = chain . from_iterable ( sections_with_spacing ) return chain ( header_iterable , sections_iterable ) write_ini ( path : Path , document : Document , config : INISerializerConfig ) -> None \u00b6 Write the provided document to the specified path If the provided path already exists, it will be overwritten. If the parent folder do not exist, they will be created. Parameters: Name Type Description Default path Path The path to which the document should be written. required document Document The document to serialize to the specified path. required config INISerializerConfig The configuration settings for the serializer. required Source code in hydrolib/core/dflowfm/ini/serializer.py def write_ini ( path : Path , document : Document , config : INISerializerConfig ) -> None : \"\"\"Write the provided document to the specified path If the provided path already exists, it will be overwritten. If the parent folder do not exist, they will be created. Args: path (Path): The path to which the document should be written. document (Document): The document to serialize to the specified path. config (INISerializerConfig): The configuration settings for the serializer. \"\"\" serializer = Serializer ( config ) path . parent . mkdir ( parents = True , exist_ok = True ) with path . open ( \"w\" , encoding = \"utf8\" ) as f : for line in serializer . serialize ( document ): f . write ( line + \" \\n \" )","title":"INI format"},{"location":"reference/ini/#ini-format","text":"The ini module provides the generic logic for parsing Deltares ini based files, such as the mdu, structures files, as well as more complex files such as the boundary condition (bc) files. Note that specific attribute files that employ this ini format often have their own dedicated module (and separate API doc page). These include: MDU file ( hydrolib.core.dflowfm.mdu ) External forcing file ( hydrolib.core.dflowfm.ext ) Initial fields and parameter file ( hydrolib.core.dflowfm.inifield ) Structure file ( hydrolib.core.dflowfm.structure ) 1D roughness ( hydrolib.core.dflowfm.friction ) Cross section files ( hydrolib.core.dflowfm.crosssection ) Storage node file ( hydrolib.core.dflowfm.storagenode ) Following below is the documentation for the INI format base classes.","title":"INI format"},{"location":"reference/ini/#model","text":"","title":"Model"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.models.DataBlockINIBasedModel","text":"DataBlockINIBasedModel defines the base model for ini models with datablocks. Attributes: Name Type Description datablock Datablock (class attribute) the actual data columns.","title":"DataBlockINIBasedModel"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.models.INIBasedModel","text":"INIBasedModel defines the base model for blocks/chapters inside an INIModel (*.ini file). INIBasedModel instances can be created from Section instances obtained through parsing ini documents. It further supports adding arbitrary fields to it, which will be written to file. Lastly, no arbitrary types are allowed for the defined fields. Attributes: Name Type Description comments Optional[Comments] Optional Comments if defined by the user, containing descriptions for all data fields.","title":"INIBasedModel"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.models.INIBasedModel.Comments","text":"Comments defines the comments of an INIBasedModel","title":"Comments"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.models.INIBasedModel.get_list_delimiter","text":"List delimiter string that will be used for serializing list field values for any IniBasedModel, if that field has no custom list delimiter. This function should be overridden by any subclass for a particular filetype that needs a specific/different list separator. Source code in hydrolib/core/dflowfm/ini/models.py @classmethod def get_list_delimiter ( cls ) -> str : \"\"\"List delimiter string that will be used for serializing list field values for any IniBasedModel, **if** that field has no custom list delimiter. This function should be overridden by any subclass for a particular filetype that needs a specific/different list separator. \"\"\" return \" \"","title":"get_list_delimiter()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.models.INIBasedModel.get_list_field_delimiter","text":"List delimiter string that will be used for serializing the given field's value. The returned delimiter is either the field's custom list delimiter if that was specified using Field(.., delimiter=\"..\"), or the default list delimiter for the model class that this field belongs to. Parameters: Name Type Description Default field_key str the original field key (not its alias). required Source code in hydrolib/core/dflowfm/ini/models.py @classmethod def get_list_field_delimiter ( cls , field_key : str ) -> str : \"\"\"List delimiter string that will be used for serializing the given field's value. The returned delimiter is either the field's custom list delimiter if that was specified using Field(.., delimiter=\"..\"), or the default list delimiter for the model class that this field belongs to. Args: field_key (str): the original field key (not its alias). \"\"\" delimiter = None if ( field := cls . __fields__ . get ( field_key )) and isinstance ( field , ModelField ): delimiter = field . field_info . extra . get ( \"delimiter\" ) if not delimiter : delimiter = cls . get_list_delimiter () return delimiter","title":"get_list_field_delimiter()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.models.INIModel","text":"INI Model representation of a *.ini file. Typically subclasses will implement the various sorts of ini files, specifically for their fileType/contents. Child elements of this class associated with chapters/blocks in the ini file will be (sub)class of INIBasedModel.","title":"INIModel"},{"location":"reference/ini/#parser","text":"","title":"Parser"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.parser.Parser","text":"Parser defines a generic Parser for Deltares ini files. The Parser can be configured with a ParserConfig object.","title":"Parser"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.parser.Parser.__init__","text":"Creates a new Parser configured with the provided config Parameters: Name Type Description Default config ParserConfig The configuration of this Parser required Source code in hydrolib/core/dflowfm/ini/parser.py def __init__ ( self , config : ParserConfig ) -> None : \"\"\"Creates a new Parser configured with the provided config Args: config (ParserConfig): The configuration of this Parser \"\"\" self . _config = config self . _document = Document () self . _current_section : Optional [ _IntermediateSection ] = None self . _current_header_block : Optional [ _IntermediateCommentBlock ] = None self . _state = self . _StateType . NO_SECTION_FOUND self . _line_index = 0 # TODO add invalid blocks self . _feed_line : Dict [ Parser . _StateType , List [ Tuple [ Callable [[ str ], bool ], Callable [[ str ], None ]]] ] = { Parser . _StateType . NO_SECTION_FOUND : [ ( self . _is_comment , self . _handle_header_comment ), ( self . _is_section_header , self . _handle_next_section_header ), ], Parser . _StateType . PARSING_PROPERTIES : [ ( self . _is_comment , self . _handle_section_comment ), ( self . _is_section_header , self . _handle_next_section_header ), ( self . _is_property , self . _handle_property ), ( self . _is_datarow , self . _handle_new_datarow ), ], Parser . _StateType . PARSING_DATABLOCK : [ ( self . _is_section_header , self . _handle_next_section_header ), ( self . _is_datarow , self . _handle_datarow ), ], } self . _handle_emptyline : Dict [ Parser . _StateType , Callable [[], None ]] = { self . _StateType . NO_SECTION_FOUND : self . _finish_current_header_block , self . _StateType . PARSING_PROPERTIES : self . _noop , self . _StateType . PARSING_DATABLOCK : self . _noop , }","title":"__init__()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.parser.Parser.feed_line","text":"Parse the next line with this Parser. Parameters: Name Type Description Default line str The line to parse required Source code in hydrolib/core/dflowfm/ini/parser.py def feed_line ( self , line : str ) -> None : \"\"\"Parse the next line with this Parser. Args: line (str): The line to parse \"\"\" if not self . _is_empty_line ( line ): for ( is_line_type , handle_line_type ) in self . _feed_line [ self . _state ]: if is_line_type ( line ): handle_line_type ( line ) break else : # handle exception pass else : self . _handle_emptyline [ self . _state ]() self . _increment_line ()","title":"feed_line()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.parser.Parser.finalize","text":"Finalize parsing and return the constructed Document. Returns: Type Description Document A Document describing the parsed ini file. Source code in hydrolib/core/dflowfm/ini/parser.py def finalize ( self ) -> Document : \"\"\"Finalize parsing and return the constructed Document. Returns: Document: A Document describing the parsed ini file. \"\"\" # TODO handle invalid block self . _finish_current_header_block () self . _finalise_current_section () return self . _document","title":"finalize()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.parser.Parser.parse","text":"Parses an INI file without a specific model type and returns it as a Document. Parameters: Name Type Description Default filepath Path File path to the INI-format file. required config ParserConfig Parser configuration to use. Defaults to None. None Returns: Type Description Document Representation of the parsed INI-file. Source code in hydrolib/core/dflowfm/ini/parser.py @classmethod def parse ( cls , filepath : Path , config : ParserConfig = None ) -> Document : \"\"\" Parses an INI file without a specific model type and returns it as a Document. Args: filepath (Path): File path to the INI-format file. config (ParserConfig, optional): Parser configuration to use. Defaults to None. Returns: Document: Representation of the parsed INI-file. \"\"\" if not config : config = ParserConfig () parser = cls ( config ) progline = re . compile ( r \"^([^#]*=\\s*)([^#]*)(#.*)?\" ) # matches whole line: \"Field = Value Maybe more # optional comment\" progfloat = re . compile ( r \"([\\d.]+)([dD])([+\\-]?\\d{1,3})\" ) # matches a float value: 1d9, 1D-3, 1.D+4, etc. with filepath . open ( encoding = \"utf8\" ) as f : for line in f : # Replace Fortran scientific notation for doubles # Match number d/D +/- number (e.g. 1d-05 or 1.23D+01 or 1.d-4) match = progline . match ( line ) if match : # Only process value line = ( match . group ( 1 ) + progfloat . sub ( r \"\\1e\\3\" , match . group ( 2 )) + str ( match . group ( 3 ) or \"\" ) ) else : # Process full line line = progfloat . sub ( r \"\\1e\\3\" , line ) parser . feed_line ( line ) return parser . finalize ()","title":"parse()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.parser.Parser.parse_as_dict","text":"Parses an INI file without a specific model type and returns it as a dictionary. Parameters: Name Type Description Default filepath Path File path to the INI-format file. required config ParserConfig Parser configuration to use. Defaults to None. None Returns: Type Description dict Representation of the parsed INI-file. Source code in hydrolib/core/dflowfm/ini/parser.py @classmethod def parse_as_dict ( cls , filepath : Path , config : ParserConfig = None ) -> dict : \"\"\" Parses an INI file without a specific model type and returns it as a dictionary. Args: filepath (Path): File path to the INI-format file. config (ParserConfig, optional): Parser configuration to use. Defaults to None. Returns: dict: Representation of the parsed INI-file. \"\"\" return cls . parse ( filepath , config ) . flatten ()","title":"parse_as_dict()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.parser.ParserConfig","text":"ParserConfig defines the configuration options of the Parser Note that we cannot set both allow_only_keywords and parse_datablocks to True because we cannot distinguish between datablocks and key only properties. As such this will lead to a validation error. Attributes: Name Type Description allow_only_keywords bool Whether to allow properties with only keys (no '=' or value). Defaults to False. parse_datablocks bool Whether to allow parsing of datablocks at the bottom of sections. Defaults to False. parse_comments bool Whether we allow parsing of comments defined with the comment_delimeter. Defaults to True. comment_delimiter str The character or sequence of character used to define a comment. Defaults to '#'.","title":"ParserConfig"},{"location":"reference/ini/#serializer","text":"","title":"Serializer"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.DataBlockINIBasedSerializerConfig","text":"Class that holds the configuration settings for INI files with data blocks serialization.","title":"DataBlockINIBasedSerializerConfig"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.INISerializerConfig","text":"SerializerConfig defines the configuration options of the Serializer Attributes: Name Type Description section_indent int The number of spaces with which whole sections should be indented. Defaults to 0. property_indent int The number of spaces with which properties should be indented relative to the section header (i.e. the full indent equals the section_indent plus property_indent). Defaults to 4. datablock_indent int The number of spaces with which datablock rows are indented relative to the section header (i.e. the full indent equals the section_indent plus datablock_indent). Defaults to 8. datablock_spacing int The number of spaces between datablock columns. Note that there might be additional offset to ensure . is lined out. Defaults to 2. comment_delimiter str The character used to delimit comments. Defaults to '#'. skip_empty_properties bool Whether or not to skip properties with a value that is empty or None. Defaults to True.","title":"INISerializerConfig"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.INISerializerConfig.total_datablock_indent","text":"The combined datablock indentation, i.e. section_indent + datablock_indent","title":"total_datablock_indent"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.INISerializerConfig.total_property_indent","text":"The combined property indentation, i.e. section_indent + property_indent","title":"total_property_indent"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.MaxLengths","text":"MaxLengths defines the maxmimum lengths of the parts of a section Attributes: Name Type Description key int The maximum length of all the keys of the properties within a section. If no properties are present it should be 0. value int The maximum length of all the non None values of the properties within a section. If no properties are present, or all values are None, it should be 0. datablock Optional[Sequence[int]] The maximum length of the values of each column of the Datablock. If no datablock is present it defaults to None.","title":"MaxLengths"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.MaxLengths.from_section","text":"Generate a MaxLengths instance from the given Section Parameters: Name Type Description Default section Section The section of which the MaxLengths are calculated required Returns: Type Description MaxLengths The MaxLengths corresponding with the provided section Source code in hydrolib/core/dflowfm/ini/serializer.py @classmethod def from_section ( cls , section : Section ) -> \"MaxLengths\" : \"\"\"Generate a MaxLengths instance from the given Section Args: section (Section): The section of which the MaxLengths are calculated Returns: MaxLengths: The MaxLengths corresponding with the provided section \"\"\" properties = list ( p for p in section . content if isinstance ( p , Property )) keys = ( prop . key for prop in properties ) values = ( prop . value for prop in properties if prop . value is not None ) max_key_length = max (( len ( k ) for k in keys ), default = 0 ) max_value_length = max (( len ( v ) for v in values ), default = 0 ) max_datablock_lengths = MaxLengths . _of_datablock ( section . datablock ) return cls ( key = max_key_length , value = max_value_length , datablock = max_datablock_lengths , )","title":"from_section()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.SectionSerializer","text":"SectionSerializer provides the serialize method to serialize a Section The entrypoint of this method is the serialize method, which will construct an actual instance and serializes the Section with it.","title":"SectionSerializer"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.SectionSerializer.__init__","text":"Create a new SectionSerializer Parameters: Name Type Description Default config SerializerConfig The config describing the serialization options required max_length MaxLengths The max lengths of the section being serialized required Source code in hydrolib/core/dflowfm/ini/serializer.py def __init__ ( self , config : INISerializerConfig , max_length : MaxLengths ): \"\"\"Create a new SectionSerializer Args: config (SerializerConfig): The config describing the serialization options max_length (MaxLengths): The max lengths of the section being serialized \"\"\" self . _config = config self . _max_length = max_length","title":"__init__()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.SectionSerializer.config","text":"The SerializerConfig used while serializing the section.","title":"config"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.SectionSerializer.max_length","text":"The MaxLengths of the Section being serialized by this SectionSerializer.","title":"max_length"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.SectionSerializer.serialize","text":"Serialize the provided section with the given config Parameters: Name Type Description Default section Section The section to serialize required config SerializerConfig The config describing the serialization options required Returns: Type Description Lines The iterable lines of the serialized section Source code in hydrolib/core/dflowfm/ini/serializer.py @classmethod def serialize ( cls , section : Section , config : INISerializerConfig ) -> Lines : \"\"\"Serialize the provided section with the given config Args: section (Section): The section to serialize config (SerializerConfig): The config describing the serialization options Returns: Lines: The iterable lines of the serialized section \"\"\" serializer = cls ( config , MaxLengths . from_section ( section )) return serializer . _serialize_section ( section )","title":"serialize()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.Serializer","text":"Serializer serializes Document to its corresponding lines.","title":"Serializer"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.Serializer.__init__","text":"Creates a new Serializer with the provided configuration. Parameters: Name Type Description Default config SerializerConfig The configuration of this Serializer. required Source code in hydrolib/core/dflowfm/ini/serializer.py def __init__ ( self , config : INISerializerConfig ): \"\"\"Creates a new Serializer with the provided configuration. Args: config (SerializerConfig): The configuration of this Serializer. \"\"\" self . _config = config","title":"__init__()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.Serializer.serialize","text":"Serialize the provided document into an iterable of lines. Parameters: Name Type Description Default document Document The Document to serialize. required Returns: Type Description Lines An iterable returning each line of the serialized Document. Source code in hydrolib/core/dflowfm/ini/serializer.py def serialize ( self , document : Document ) -> Lines : \"\"\"Serialize the provided document into an iterable of lines. Args: document (Document): The Document to serialize. Returns: Lines: An iterable returning each line of the serialized Document. \"\"\" header_iterable = self . _serialize_document_header ( document . header_comment ) serialize_section = lambda s : SectionSerializer . serialize ( s , self . _config ) sections = ( serialize_section ( section ) for section in document . sections ) sections_with_spacing = Serializer . _interweave ( sections , [ \"\" ]) sections_iterable = chain . from_iterable ( sections_with_spacing ) return chain ( header_iterable , sections_iterable )","title":"serialize()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.write_ini","text":"Write the provided document to the specified path If the provided path already exists, it will be overwritten. If the parent folder do not exist, they will be created. Parameters: Name Type Description Default path Path The path to which the document should be written. required document Document The document to serialize to the specified path. required config INISerializerConfig The configuration settings for the serializer. required Source code in hydrolib/core/dflowfm/ini/serializer.py def write_ini ( path : Path , document : Document , config : INISerializerConfig ) -> None : \"\"\"Write the provided document to the specified path If the provided path already exists, it will be overwritten. If the parent folder do not exist, they will be created. Args: path (Path): The path to which the document should be written. document (Document): The document to serialize to the specified path. config (INISerializerConfig): The configuration settings for the serializer. \"\"\" serializer = Serializer ( config ) path . parent . mkdir ( parents = True , exist_ok = True ) with path . open ( \"w\" , encoding = \"utf8\" ) as f : for line in serializer . serialize ( document ): f . write ( line + \" \\n \" )","title":"write_ini()"},{"location":"reference/inifield/","text":"Initial and parameter field files \u00b6 The inifield file contains the initial conditions and spatial parameter input fields for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. The inifield file is represented by the classes below. Model \u00b6 AbstractSpatialField ( INIBasedModel , ABC ) pydantic-model \u00b6 Abstract base class for [Initial] and [Parameter] block data in inifield files. Defines all common fields. Used via subclasses InitialField and ParameterField. validate_that_value_is_present_for_polygons ( values : Dict ) -> Dict classmethod \u00b6 Validates that the value is provided when dealing with polygons. Source code in hydrolib/core/dflowfm/inifield/models.py @root_validator ( allow_reuse = True ) def validate_that_value_is_present_for_polygons ( cls , values : Dict ) -> Dict : \"\"\"Validates that the value is provided when dealing with polygons.\"\"\" return validate_required_fields ( values , \"value\" , conditional_field_name = \"datafiletype\" , conditional_value = DataFileType . polygon , ) AveragingType ( str , Enum ) \u00b6 Enum class containing the valid values for the averagingType attribute in several subclasses of AbstractIniField. DataFileType ( str , Enum ) \u00b6 Enum class containing the valid values for the dataFileType attribute in several subclasses of AbstractIniField. IniFieldGeneral ( INIGeneral ) pydantic-model \u00b6 The initial field file's [General] section with file meta data. IniFieldModel ( INIModel ) pydantic-model \u00b6 The overall inifield model that contains the contents of one initial field and parameter file. This model is typically referenced under a FMModel .geometry.inifieldfile[..] . Attributes: Name Type Description general IniFieldGeneral [General] block with file metadata. initial List[InitialField] List of [Initial] blocks with initial condition definitions. parameter List[ParameterField] List of [Parameter] blocks with spatial parameter definitions. InitialField ( AbstractSpatialField ) pydantic-model \u00b6 Initial condition field definition, represents an [Initial] block in an inifield file. Typically inside the definition list of a FMModel .geometry.inifieldfile.initial[..] InterpolationMethod ( str , Enum ) \u00b6 Enum class containing the valid values for the interpolationMethod attribute in several subclasses of AbstractIniField. ParameterField ( AbstractSpatialField ) pydantic-model \u00b6 Parameter field definition, represents a [Parameter] block in an inifield file. Typically inside the definition list of a FMModel .geometry.inifieldfile.parameter[..]","title":"Initial and parameter field files"},{"location":"reference/inifield/#initial-and-parameter-field-files","text":"The inifield file contains the initial conditions and spatial parameter input fields for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. The inifield file is represented by the classes below.","title":"Initial and parameter field files"},{"location":"reference/inifield/#model","text":"","title":"Model"},{"location":"reference/inifield/#hydrolib.core.dflowfm.inifield.models.AbstractSpatialField","text":"Abstract base class for [Initial] and [Parameter] block data in inifield files. Defines all common fields. Used via subclasses InitialField and ParameterField.","title":"AbstractSpatialField"},{"location":"reference/inifield/#hydrolib.core.dflowfm.inifield.models.AbstractSpatialField.validate_that_value_is_present_for_polygons","text":"Validates that the value is provided when dealing with polygons. Source code in hydrolib/core/dflowfm/inifield/models.py @root_validator ( allow_reuse = True ) def validate_that_value_is_present_for_polygons ( cls , values : Dict ) -> Dict : \"\"\"Validates that the value is provided when dealing with polygons.\"\"\" return validate_required_fields ( values , \"value\" , conditional_field_name = \"datafiletype\" , conditional_value = DataFileType . polygon , )","title":"validate_that_value_is_present_for_polygons()"},{"location":"reference/inifield/#hydrolib.core.dflowfm.inifield.models.AveragingType","text":"Enum class containing the valid values for the averagingType attribute in several subclasses of AbstractIniField.","title":"AveragingType"},{"location":"reference/inifield/#hydrolib.core.dflowfm.inifield.models.DataFileType","text":"Enum class containing the valid values for the dataFileType attribute in several subclasses of AbstractIniField.","title":"DataFileType"},{"location":"reference/inifield/#hydrolib.core.dflowfm.inifield.models.IniFieldGeneral","text":"The initial field file's [General] section with file meta data.","title":"IniFieldGeneral"},{"location":"reference/inifield/#hydrolib.core.dflowfm.inifield.models.IniFieldModel","text":"The overall inifield model that contains the contents of one initial field and parameter file. This model is typically referenced under a FMModel .geometry.inifieldfile[..] . Attributes: Name Type Description general IniFieldGeneral [General] block with file metadata. initial List[InitialField] List of [Initial] blocks with initial condition definitions. parameter List[ParameterField] List of [Parameter] blocks with spatial parameter definitions.","title":"IniFieldModel"},{"location":"reference/inifield/#hydrolib.core.dflowfm.inifield.models.InitialField","text":"Initial condition field definition, represents an [Initial] block in an inifield file. Typically inside the definition list of a FMModel .geometry.inifieldfile.initial[..]","title":"InitialField"},{"location":"reference/inifield/#hydrolib.core.dflowfm.inifield.models.InterpolationMethod","text":"Enum class containing the valid values for the interpolationMethod attribute in several subclasses of AbstractIniField.","title":"InterpolationMethod"},{"location":"reference/inifield/#hydrolib.core.dflowfm.inifield.models.ParameterField","text":"Parameter field definition, represents a [Parameter] block in an inifield file. Typically inside the definition list of a FMModel .geometry.inifieldfile.parameter[..]","title":"ParameterField"},{"location":"reference/mdu/","text":"MDU file \u00b6 The MDU file is the main input file for D-Flow FM . It is represented by the classes below. Model \u00b6 AutoStartOption ( IntEnum ) \u00b6 Enum class containing the valid values for the AutoStart attribute in the General class. Calibration ( INIBasedModel ) pydantic-model \u00b6 The [Calibration] section in an MDU file. This model is typically referenced under FMModel .calibration . All lowercased attributes match with the [Calibration] input as described in UM Sec.A.3 . ExternalForcing ( INIBasedModel ) pydantic-model \u00b6 The [External Forcing] section in an MDU file. This model is typically referenced under FMModel .external_forcing . All lowercased attributes match with the [External Forcing] input as described in UM Sec.A.1 . is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/mdu/models.py def is_intermediate_link ( self ) -> bool : return True FMModel ( INIModel ) pydantic-model \u00b6 The overall FM model that contains the contents of the toplevel MDU file. All lowercased attributes match with the supported \"[section]\"s as described in UM Sec.A . Each of these class attributes refers to an underlying model class for that particular section. General ( INIGeneral ) pydantic-model \u00b6 The MDU file's [General] section with file meta data. Geometry ( INIBasedModel ) pydantic-model \u00b6 The [Geometry] section in an MDU file. This model is typically referenced under FMModel .geometry . All lowercased attributes match with the [Geometry] input as described in UM Sec.A.1 . is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/mdu/models.py def is_intermediate_link ( self ) -> bool : return True GroundWater ( INIBasedModel ) pydantic-model \u00b6 The [Grw] section in an MDU file. This model is typically referenced under FMModel .grw . All lowercased attributes match with the [Grw] input as described in UM Sec.A.3 . Hydrology ( INIBasedModel ) pydantic-model \u00b6 The [Hydrology] section in an MDU file. This model is typically referenced under FMModel .hydrology . All lowercased attributes match with the [Hydrology] input as described in UM Sec.A.1 . InfiltrationMethod ( IntEnum ) \u00b6 Enum class containing the valid values for the Infiltrationmodel attribute in the GroundWater class. Numerics ( INIBasedModel ) pydantic-model \u00b6 The [Numerics] section in an MDU file. This model is typically referenced under FMModel .numerics . All lowercased attributes match with the [Numerics] input as described in UM Sec.A.1 . Output ( INIBasedModel ) pydantic-model \u00b6 The [Output] section in an MDU file. This model is typically referenced under FMModel .output . All lowercased attributes match with the [Output] input as described in UM Sec.A.1 . is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/mdu/models.py def is_intermediate_link ( self ) -> bool : return True Particles ( INIBasedModel ) pydantic-model \u00b6 The [Particles] section in an MDU file. This model is typically referenced under FMModel .particles . All lowercased attributes match with the [Particles] input as described in UM Sec.A.3 . ParticlesThreeDType ( IntEnum ) \u00b6 Enum class containing the valid values for the 3Dtype attribute in the Particles class. Physics ( INIBasedModel ) pydantic-model \u00b6 The [Physics] section in an MDU file. This model is typically referenced under FMModel .physics . All lowercased attributes match with the [Physics] input as described in UM Sec.A.1 . ProcessFluxIntegration ( IntEnum ) \u00b6 Enum class containing the valid values for the ProcessFluxIntegration attribute in the Processes class. Processes ( INIBasedModel ) pydantic-model \u00b6 The [Processes] section in an MDU file. This model is typically referenced under FMModel .processes . All lowercased attributes match with the [Processes] input as described in UM Sec.A.3 . Restart ( INIBasedModel ) pydantic-model \u00b6 The [Restart] section in an MDU file. This model is typically referenced under FMModel .restart . All lowercased attributes match with the [Restart] input as described in UM Sec.A.1 . Time ( INIBasedModel ) pydantic-model \u00b6 The [Time] section in an MDU file. This model is typically referenced under FMModel .time . All lowercased attributes match with the [Time] input as described in UM Sec.A.1 . Trachytopes ( INIBasedModel ) pydantic-model \u00b6 The [Trachytopes] section in an MDU file. This model is typically referenced under FMModel .trachytopes . All lowercased attributes match with the [Trachytopes] input as described in UM Sec.A.1 . Vegetation ( INIBasedModel ) pydantic-model \u00b6 The [Veg] section in an MDU file. This model is typically referenced under FMModel .veg . All lowercased attributes match with the [Veg] input as described in UM Sec.A.3 . VegetationModelNr ( IntEnum ) \u00b6 Enum class containing the valid values for the VegetationModelNr attribute in the Vegetation class. VolumeTables ( INIBasedModel ) pydantic-model \u00b6 The [VolumeTables] section in an MDU file. This model is typically referenced under FMModel .volumetables . All lowercased attributes match with the [VolumeTables] input as described in UM Sec.A.1 . Waves ( INIBasedModel ) pydantic-model \u00b6 The [Waves] section in an MDU file. This model is typically referenced under FMModel .waves . All lowercased attributes match with the [Waves] input as described in UM Sec.A.1 . Wind ( INIBasedModel ) pydantic-model \u00b6 The [Wind] section in an MDU file. This model is typically referenced under FMModel .wind . All lowercased attributes match with the [Wind] input as described in UM Sec.A.1 .","title":"MDU file"},{"location":"reference/mdu/#mdu-file","text":"The MDU file is the main input file for D-Flow FM . It is represented by the classes below.","title":"MDU file"},{"location":"reference/mdu/#model","text":"","title":"Model"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.AutoStartOption","text":"Enum class containing the valid values for the AutoStart attribute in the General class.","title":"AutoStartOption"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Calibration","text":"The [Calibration] section in an MDU file. This model is typically referenced under FMModel .calibration . All lowercased attributes match with the [Calibration] input as described in UM Sec.A.3 .","title":"Calibration"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.ExternalForcing","text":"The [External Forcing] section in an MDU file. This model is typically referenced under FMModel .external_forcing . All lowercased attributes match with the [External Forcing] input as described in UM Sec.A.1 .","title":"ExternalForcing"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.ExternalForcing.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/mdu/models.py def is_intermediate_link ( self ) -> bool : return True","title":"is_intermediate_link()"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.FMModel","text":"The overall FM model that contains the contents of the toplevel MDU file. All lowercased attributes match with the supported \"[section]\"s as described in UM Sec.A . Each of these class attributes refers to an underlying model class for that particular section.","title":"FMModel"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.General","text":"The MDU file's [General] section with file meta data.","title":"General"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Geometry","text":"The [Geometry] section in an MDU file. This model is typically referenced under FMModel .geometry . All lowercased attributes match with the [Geometry] input as described in UM Sec.A.1 .","title":"Geometry"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Geometry.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/mdu/models.py def is_intermediate_link ( self ) -> bool : return True","title":"is_intermediate_link()"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.GroundWater","text":"The [Grw] section in an MDU file. This model is typically referenced under FMModel .grw . All lowercased attributes match with the [Grw] input as described in UM Sec.A.3 .","title":"GroundWater"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Hydrology","text":"The [Hydrology] section in an MDU file. This model is typically referenced under FMModel .hydrology . All lowercased attributes match with the [Hydrology] input as described in UM Sec.A.1 .","title":"Hydrology"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.InfiltrationMethod","text":"Enum class containing the valid values for the Infiltrationmodel attribute in the GroundWater class.","title":"InfiltrationMethod"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Numerics","text":"The [Numerics] section in an MDU file. This model is typically referenced under FMModel .numerics . All lowercased attributes match with the [Numerics] input as described in UM Sec.A.1 .","title":"Numerics"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Output","text":"The [Output] section in an MDU file. This model is typically referenced under FMModel .output . All lowercased attributes match with the [Output] input as described in UM Sec.A.1 .","title":"Output"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Output.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/mdu/models.py def is_intermediate_link ( self ) -> bool : return True","title":"is_intermediate_link()"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Particles","text":"The [Particles] section in an MDU file. This model is typically referenced under FMModel .particles . All lowercased attributes match with the [Particles] input as described in UM Sec.A.3 .","title":"Particles"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.ParticlesThreeDType","text":"Enum class containing the valid values for the 3Dtype attribute in the Particles class.","title":"ParticlesThreeDType"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Physics","text":"The [Physics] section in an MDU file. This model is typically referenced under FMModel .physics . All lowercased attributes match with the [Physics] input as described in UM Sec.A.1 .","title":"Physics"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.ProcessFluxIntegration","text":"Enum class containing the valid values for the ProcessFluxIntegration attribute in the Processes class.","title":"ProcessFluxIntegration"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Processes","text":"The [Processes] section in an MDU file. This model is typically referenced under FMModel .processes . All lowercased attributes match with the [Processes] input as described in UM Sec.A.3 .","title":"Processes"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Restart","text":"The [Restart] section in an MDU file. This model is typically referenced under FMModel .restart . All lowercased attributes match with the [Restart] input as described in UM Sec.A.1 .","title":"Restart"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Time","text":"The [Time] section in an MDU file. This model is typically referenced under FMModel .time . All lowercased attributes match with the [Time] input as described in UM Sec.A.1 .","title":"Time"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Trachytopes","text":"The [Trachytopes] section in an MDU file. This model is typically referenced under FMModel .trachytopes . All lowercased attributes match with the [Trachytopes] input as described in UM Sec.A.1 .","title":"Trachytopes"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Vegetation","text":"The [Veg] section in an MDU file. This model is typically referenced under FMModel .veg . All lowercased attributes match with the [Veg] input as described in UM Sec.A.3 .","title":"Vegetation"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.VegetationModelNr","text":"Enum class containing the valid values for the VegetationModelNr attribute in the Vegetation class.","title":"VegetationModelNr"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.VolumeTables","text":"The [VolumeTables] section in an MDU file. This model is typically referenced under FMModel .volumetables . All lowercased attributes match with the [VolumeTables] input as described in UM Sec.A.1 .","title":"VolumeTables"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Waves","text":"The [Waves] section in an MDU file. This model is typically referenced under FMModel .waves . All lowercased attributes match with the [Waves] input as described in UM Sec.A.1 .","title":"Waves"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Wind","text":"The [Wind] section in an MDU file. This model is typically referenced under FMModel .wind . All lowercased attributes match with the [Wind] input as described in UM Sec.A.1 .","title":"Wind"},{"location":"reference/net/","text":"Net/grid file \u00b6 The computational grid for D-Flow FM is stored in the net file. It is an unstructured grid, where 1D and 2D can be combined. The file format is NetCDF , using the CF -, UGRID - and Deltares -conventions. The net file is represented by the classes below. Model \u00b6 Branch \u00b6 generate_nodes ( self , mesh1d_edge_length : float , structure_chainage : Optional [ List [ float ]] = None , max_dist_to_struc : Optional [ float ] = None ) \u00b6 Generate the branch offsets and the nodes. Parameters: Name Type Description Default mesh1d_edge_length float The edge length of the 1d mesh. required structure_chainage Optional[List[float]] A list with the structure chainages. If not specified, calculation will not take it into account. Defaults to None. None max_dist_to_struc Optional[float] The maximum distance from a node to a structure. If not specified, calculation will not take it into account. Defaults to None. None Exceptions: Type Description ValueError Raised when any of the structure offsets, if specified, is smaller than zero. ValueError Raised when any of the structure offsets, if specified, is greater than the branch length. Source code in hydrolib/core/dflowfm/net/models.py def generate_nodes ( self , mesh1d_edge_length : float , structure_chainage : Optional [ List [ float ]] = None , max_dist_to_struc : Optional [ float ] = None , ): \"\"\"Generate the branch offsets and the nodes. Args: mesh1d_edge_length (float): The edge length of the 1d mesh. structure_chainage (Optional[List[float]], optional): A list with the structure chainages. If not specified, calculation will not take it into account. Defaults to None. max_dist_to_struc (Optional[float], optional): The maximum distance from a node to a structure. If not specified, calculation will not take it into account. Defaults to None. Raises: ValueError: Raised when any of the structure offsets, if specified, is smaller than zero. ValueError: Raised when any of the structure offsets, if specified, is greater than the branch length. \"\"\" # Generate offsets self . branch_offsets = self . _generate_offsets ( mesh1d_edge_length , structure_chainage , max_dist_to_struc ) # Calculate node positions self . node_xy = self . interpolate ( self . branch_offsets ) # Add mask (all False) self . mask = np . full ( self . branch_offsets . shape , False ) interpolate ( self , distance : npt . ArrayLike ) -> np . ndarray \u00b6 Interpolate coordinates along branch by length Parameters: Name Type Description Default distance npt.ArrayLike Length required Source code in hydrolib/core/dflowfm/net/models.py def interpolate ( self , distance : npt . ArrayLike ) -> np . ndarray : \"\"\"Interpolate coordinates along branch by length Args: distance (npt.ArrayLike): Length \"\"\" intpcoords = np . stack ( [ np . interp ( distance , self . _distance , self . _x_coordinates ), np . interp ( distance , self . _distance , self . _y_coordinates ), ], axis = 1 , ) return intpcoords Link1d2d ( BaseModel ) pydantic-model \u00b6 Link1d2d defines the 1D2D Links of a model network. Attributes: Name Type Description meshkernel Optional[mk.MeshKernel] The MeshKernel used to interact with this Link1d2d link1d2d_id np.ndarray The id of this Link1d2d link1d2d_long_name np.ndarray The long name of this Link1d2d link1d2d_contact_type np.ndarray The contact type of this Link1d2d link1d2d np.ndarray The underlying data object of this Link1d2d clear ( self ) -> None \u00b6 Remove all saved links from the links administration Source code in hydrolib/core/dflowfm/net/models.py def clear ( self ) -> None : \"\"\"Remove all saved links from the links administration\"\"\" self . link1d2d_id = np . empty ( 0 , object ) self . link1d2d_long_name = np . empty ( 0 , object ) self . link1d2d_contact_type = np . empty ( 0 , np . int32 ) self . link1d2d = np . empty (( 0 , 2 ), np . int32 ) # The meshkernel object needs to be resetted self . meshkernel . _deallocate_state () self . meshkernel . _allocate_state ( self . meshkernel . get_projection ()) self . meshkernel . contacts_get () is_empty ( self ) -> bool \u00b6 Whether this Link1d2d is currently empty. Returns: Type Description bool True if the Link1d2d is currently empty; False otherwise. Source code in hydrolib/core/dflowfm/net/models.py def is_empty ( self ) -> bool : \"\"\"Whether this Link1d2d is currently empty. Returns: bool: True if the Link1d2d is currently empty; False otherwise. \"\"\" return self . link1d2d . size == 0 read_file ( self , file_path : Path ) -> None \u00b6 Read the Link1d2d data from the specified netCDF file at file_path into this Parameters: Name Type Description Default file_path Path Path to the netCDF file. required Source code in hydrolib/core/dflowfm/net/models.py def read_file ( self , file_path : Path ) -> None : \"\"\"Read the Link1d2d data from the specified netCDF file at file_path into this Args: file_path (Path): Path to the netCDF file. \"\"\" reader = UgridReader ( file_path ) reader . read_link1d2d ( self ) Mesh1d ( BaseModel ) pydantic-model \u00b6 get_node_mask ( self , branchids : List [ str ] = None ) \u00b6 Get node mask, give a mask with True for each node that is in the given branchid list Source code in hydrolib/core/dflowfm/net/models.py def get_node_mask ( self , branchids : List [ str ] = None ): \"\"\"Get node mask, give a mask with True for each node that is in the given branchid list\"\"\" mask = np . full ( self . mesh1d_node_id . shape , False , dtype = bool ) if branchids is None : mask [:] = True return mask # Get number (index) of given branches idx = np . where ( np . isin ( self . network1d_branch_id , branchids ))[ 0 ] if idx . size == 0 : raise KeyError ( \"No branches corresponding to the given keys were found.\" ) mask [ np . isin ( self . mesh1d_node_branch_id , idx )] = True return mask Mesh2d ( BaseModel ) pydantic-model \u00b6 Mesh2d defines a single two dimensional grid. Attributes: Name Type Description meshkernel mk.MeshKernel The meshkernel used to manimpulate this Mesh2d. mesh2d_node_z np.ndarray The node positions on the z-axis. Defaults to np.empty(0, dtype=np.double). mesh2d_face_z np.ndarray The face positions on the z-axis. Defaults to np.empty(0, dtype=np.double). clip ( self , geometrylist : mk . GeometryList , deletemeshoption : mk . DeleteMeshOption = < DeleteMeshOption . INSIDE_NOT_INTERSECTED : 0 > , inside = False ) -> None \u00b6 Clip the 2D mesh by a polygon. Both outside the exterior and inside the interiors is clipped Parameters: Name Type Description Default geometrylist GeometryList Polygon stored as GeometryList required deletemeshoption int [description]. Defaults to 1. Source code in hydrolib/core/dflowfm/net/models.py def clip ( self , geometrylist : mk . GeometryList , deletemeshoption : mk . DeleteMeshOption = mk . DeleteMeshOption . INSIDE_NOT_INTERSECTED , inside = False , ) -> None : \"\"\"Clip the 2D mesh by a polygon. Both outside the exterior and inside the interiors is clipped Args: geometrylist (GeometryList): Polygon stored as GeometryList deletemeshoption (int, optional): [description]. Defaults to 1. \"\"\" # For clipping outside if not inside : # Check if a multipolygon was provided when clipping outside if geometrylist . geometry_separator in geometrylist . x_coordinates : raise NotImplementedError ( \"Deleting outside more than a single exterior (MultiPolygon) is not implemented.\" ) # Get exterior and interiors parts = split_by ( geometrylist , geometrylist . inner_outer_separator ) exteriors = [ parts [ 0 ]] interiors = parts [ 1 :] # Inside else : # Check if any polygon contains holes, when clipping inside if geometrylist . inner_outer_separator in geometrylist . x_coordinates : raise NotImplementedError ( \"Deleting inside a (Multi)Polygon with holes is not implemented.\" ) # Get exterior and interiors parts = split_by ( geometrylist , geometrylist . geometry_separator ) exteriors = parts [:] interiors = [] # Check if parts are closed for part in exteriors + interiors : if ( part . x_coordinates [ 0 ], part . y_coordinates [ 0 ]) != ( part . x_coordinates [ - 1 ], part . y_coordinates [ - 1 ], ): raise ValueError ( \"First and last coordinate of each GeometryList part should match.\" ) # Delete everything outside the (Multi)Polygon for exterior in exteriors : self . meshkernel . mesh2d_delete ( geometry_list = exterior , delete_option = deletemeshoption , invert_deletion = not inside , ) # Delete all holes. for interior in interiors : self . meshkernel . mesh2d_delete ( geometry_list = interior , delete_option = deletemeshoption , invert_deletion = inside , ) create_rectilinear ( self , extent : tuple , dx : float , dy : float ) -> None \u00b6 Create a rectilinear mesh within a polygon. A rectangular grid is generated within the polygon bounds Parameters: Name Type Description Default extent tuple Bounding box of mesh (left, bottom, right, top) required dx float Horizontal distance required dy float Vertical distance required Exceptions: Type Description NotImplementedError MultiPolygons Source code in hydrolib/core/dflowfm/net/models.py def create_rectilinear ( self , extent : tuple , dx : float , dy : float ) -> None : \"\"\"Create a rectilinear mesh within a polygon. A rectangular grid is generated within the polygon bounds Args: extent (tuple): Bounding box of mesh (left, bottom, right, top) dx (float): Horizontal distance dy (float): Vertical distance Raises: NotImplementedError: MultiPolygons \"\"\" xmin , ymin , xmax , ymax = extent rows = int (( ymax - ymin ) / dy ) columns = int (( xmax - xmin ) / dx ) params = mk . MakeGridParameters ( num_columns = columns , num_rows = rows , origin_x = xmin , origin_y = ymin , block_size_x = dx , block_size_y = dy , ) mesh2d_input = self . meshkernel # mk.MeshKernel() mesh2d_input . curvilinear_compute_rectangular_grid ( params ) mesh2d_input . curvilinear_convert_to_mesh2d () # convert to ugrid/mesh2d create_triangular ( self , geometry_list : mk . GeometryList ) -> None \u00b6 Create triangular grid within GeometryList object Parameters: Name Type Description Default geometry_list mk.GeometryList GeometryList represeting a polygon within which the mesh is generated. required Source code in hydrolib/core/dflowfm/net/models.py def create_triangular ( self , geometry_list : mk . GeometryList ) -> None : \"\"\"Create triangular grid within GeometryList object Args: geometry_list (mk.GeometryList): GeometryList represeting a polygon within which the mesh is generated. \"\"\" # Call meshkernel self . meshkernel . mesh2d_make_triangular_mesh_from_polygon ( geometry_list ) get_mesh2d ( self ) -> mk . Mesh2d \u00b6 Get the mesh2d as represented in the MeshKernel Returns: Type Description (mk.Mesh2d) The mesh2d as represented in the MeshKernel Source code in hydrolib/core/dflowfm/net/models.py def get_mesh2d ( self ) -> mk . Mesh2d : \"\"\"Get the mesh2d as represented in the MeshKernel Returns: (mk.Mesh2d): The mesh2d as represented in the MeshKernel \"\"\" return self . meshkernel . mesh2d_get () is_empty ( self ) -> bool \u00b6 Determine whether this Mesh2d is empty. Returns: Type Description (bool) Whether this Mesh2d is empty. Source code in hydrolib/core/dflowfm/net/models.py def is_empty ( self ) -> bool : \"\"\"Determine whether this Mesh2d is empty. Returns: (bool): Whether this Mesh2d is empty. \"\"\" return self . mesh2d_node_x . size == 0 mesh2d_edge_nodes : np . ndarray [ int , int ] property readonly \u00b6 The node indices of the mesh edges. Returns: Type Description np.ndarray[int, int] A 2D integer array (nEdges, 2) containg the two node indices for each edge. mesh2d_edge_x : np . ndarray [ float ] property readonly \u00b6 The x-coordinates of the mesh edges' middle points. Returns: Type Description ndarray[float] A 1D double array describing x-coordinates of the mesh edges' middle points. mesh2d_edge_y : np . ndarray [ float ] property readonly \u00b6 The y-coordinates of the mesh edges' middle points. Returns: Type Description ndarray[float] A 1D double array describing y-coordinates of the mesh edges' middle points. mesh2d_face_nodes : np . ndarray [ int , int ] property readonly \u00b6 The node indices of the mesh faces Returns: Type Description np.ndarray[int, int] A 2D integer array describing the nodes composing each mesh 2d face. A 2D integer array (nFaces, maxNodesPerFace) containg the node indices for each face. mesh2d_face_x : np . ndarray [ float ] property readonly \u00b6 The x-coordinates of the mesh faces' mass centers. Returns: Type Description ndarray[float] A 1D double array describing x-coordinates of the mesh faces' mass centers. mesh2d_face_y : np . ndarray [ float ] property readonly \u00b6 The y-coordinates of the mesh faces' mass centers. Returns: Type Description ndarray[float] A 1D double array describing y-coordinates of the mesh faces' mass centers. mesh2d_node_x : np . ndarray [ float ] property readonly \u00b6 The x-coordinates of the nodes in the mesh. Returns: Type Description ndarray[float] A 1D double array describing the x-coordinates of the nodes. mesh2d_node_y : np . ndarray [ float ] property readonly \u00b6 The y-coordinates of the nodes in the mesh. Returns: Type Description ndarray[float] A 1D double array describing the y-coordinates of the nodes. read_file ( self , file_path : Path ) -> None \u00b6 Read the Mesh2d from the file at file_path. Parameters: Name Type Description Default file_path Path Path to the file to be read. required Source code in hydrolib/core/dflowfm/net/models.py def read_file ( self , file_path : Path ) -> None : \"\"\"Read the Mesh2d from the file at file_path. Args: file_path (Path): Path to the file to be read. \"\"\" reader = UgridReader ( file_path ) reader . read_mesh2d ( self ) refine ( self , polygon : mk . GeometryList , level : int , min_edge_size = 10.0 ) \u00b6 Refine the mesh within a polygon, by a number of steps (level) Parameters: Name Type Description Default polygon GeometryList Polygon in which to refine required level int Number of refinement steps required Source code in hydrolib/core/dflowfm/net/models.py def refine ( self , polygon : mk . GeometryList , level : int , min_edge_size = 10.0 ): \"\"\"Refine the mesh within a polygon, by a number of steps (level) Args: polygon (GeometryList): Polygon in which to refine level (int): Number of refinement steps \"\"\" # Check if parts are closed # if not (polygon.x_coordinates[0], polygon.y_coordinates[0]) == ( # polygon.x_coordinates[-1], # polygon.y_coordinates[-1], # ): # raise ValueError(\"First and last coordinate of each GeometryList part should match.\") parameters = mk . MeshRefinementParameters ( refine_intersected = True , use_mass_center_when_refining = False , min_edge_size = min_edge_size , # Does nothing? refinement_type = 1 , # No effect? connect_hanging_nodes = True , account_for_samples_outside_face = False , max_refinement_iterations = level , ) self . meshkernel . mesh2d_refine_based_on_polygon ( polygon , parameters ) Network \u00b6 from_file ( file_path : Path ) -> Network classmethod \u00b6 Read network from file. This classmethod checks what mesh components (mesh1d & network1d, mesh2d, link1d2d) are present, and loads them one by one. Parameters: Name Type Description Default file_path Path path to netcdf file with network data required Returns: Type Description Network The instance of the class itself that is returned Source code in hydrolib/core/dflowfm/net/models.py @classmethod def from_file ( cls , file_path : Path ) -> Network : \"\"\"Read network from file. This classmethod checks what mesh components (mesh1d & network1d, mesh2d, link1d2d) are present, and loads them one by one. Args: file_path (Path): path to netcdf file with network data Returns: Network: The instance of the class itself that is returned \"\"\" network = cls () ds = nc . Dataset ( file_path ) # type: ignore[import] reader = UgridReader ( file_path ) reader . read_mesh1d_network1d ( network . _mesh1d ) reader . read_mesh2d ( network . _mesh2d ) reader . read_link1d2d ( network . _link1d2d ) ds . close () return network is_geographic : bool property readonly \u00b6 Whether or not this network has a geographic projection. Returns: Type Description bool True if this network is geographic; otherwise, False. mesh2d_create_triangular_within_polygon ( self , polygon : mk . GeometryList ) -> None \u00b6 Create triangular grid within GeometryList object. Calls _mesh2d.create_triangular directly, but is easier accessible for users. Parameters: Name Type Description Default polygon mk.GeometryList GeometryList representing a polygon within which the mesh is generated. required Source code in hydrolib/core/dflowfm/net/models.py def mesh2d_create_triangular_within_polygon ( self , polygon : mk . GeometryList ) -> None : \"\"\"Create triangular grid within GeometryList object. Calls _mesh2d.create_triangular directly, but is easier accessible for users. Args: polygon (mk.GeometryList): GeometryList representing a polygon within which the mesh is generated. \"\"\" self . _mesh2d . create_triangular ( geometry_list = polygon ) plot ( self , ax = None ) \u00b6 Create a plot of the 1d2d links and edges within this network. Parameters: Name Type Description Default ax matplotlib.pyplot.Axes The axes where to plot the edges. Defaults to None. None Source code in hydrolib/core/dflowfm/net/models.py def plot ( self , ax = None ): \"\"\"Create a plot of the 1d2d links and edges within this network. Args: ax (matplotlib.pyplot.Axes, optional): The axes where to plot the edges. Defaults to None. \"\"\" import matplotlib.pyplot as plt if ax is None : _ , ax = plt . subplots () mesh2d_output = self . _mesh2d . get_mesh2d () mesh1d_output = self . _mesh1d . _get_mesh1d () links_output = self . _link1d2d . meshkernel . contacts_get () mesh2d_output . plot_edges ( ax = ax , color = \"r\" ) mesh1d_output . plot_edges ( ax = ax , color = \"g\" ) links_output . plot_edges ( ax = ax , mesh1d = mesh1d_output , mesh2d = mesh2d_output , color = \"k\" ) to_file ( self , file : Path ) -> None \u00b6 Write network to file Parameters: Name Type Description Default file Path File where _net.nc is written to. required Source code in hydrolib/core/dflowfm/net/models.py def to_file ( self , file : Path ) -> None : \"\"\"Write network to file Args: file (Path): File where _net.nc is written to. \"\"\" writer = UgridWriter () writer . write ( self , file ) NetworkModel ( ParsableFileModel ) pydantic-model \u00b6 Network model representation. split_by ( gl : mk . GeometryList , by : float ) -> list \u00b6 Function to split mk.GeometryList by seperator. Parameters: Name Type Description Default gl mk.GeometryList The geometry list to split. required by float The value by which to split the gl. required Returns: Type Description list The split lists. Source code in hydrolib/core/dflowfm/net/models.py def split_by ( gl : mk . GeometryList , by : float ) -> list : \"\"\"Function to split mk.GeometryList by seperator. Args: gl (mk.GeometryList): The geometry list to split. by (float): The value by which to split the gl. Returns: list: The split lists. \"\"\" x , y = gl . x_coordinates . copy (), gl . y_coordinates . copy () idx = np . where ( x == by )[ 0 ] xparts = np . split ( x , idx ) yparts = np . split ( y , idx ) lists = [ mk . GeometryList ( xp [ min ( i , 1 ) :], yp [ min ( i , 1 ) :]) for i , ( xp , yp ) in enumerate ( zip ( xparts , yparts )) ] return lists","title":"Net/grid file"},{"location":"reference/net/#netgrid-file","text":"The computational grid for D-Flow FM is stored in the net file. It is an unstructured grid, where 1D and 2D can be combined. The file format is NetCDF , using the CF -, UGRID - and Deltares -conventions. The net file is represented by the classes below.","title":"Net/grid file"},{"location":"reference/net/#model","text":"","title":"Model"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Branch","text":"","title":"Branch"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Branch.generate_nodes","text":"Generate the branch offsets and the nodes. Parameters: Name Type Description Default mesh1d_edge_length float The edge length of the 1d mesh. required structure_chainage Optional[List[float]] A list with the structure chainages. If not specified, calculation will not take it into account. Defaults to None. None max_dist_to_struc Optional[float] The maximum distance from a node to a structure. If not specified, calculation will not take it into account. Defaults to None. None Exceptions: Type Description ValueError Raised when any of the structure offsets, if specified, is smaller than zero. ValueError Raised when any of the structure offsets, if specified, is greater than the branch length. Source code in hydrolib/core/dflowfm/net/models.py def generate_nodes ( self , mesh1d_edge_length : float , structure_chainage : Optional [ List [ float ]] = None , max_dist_to_struc : Optional [ float ] = None , ): \"\"\"Generate the branch offsets and the nodes. Args: mesh1d_edge_length (float): The edge length of the 1d mesh. structure_chainage (Optional[List[float]], optional): A list with the structure chainages. If not specified, calculation will not take it into account. Defaults to None. max_dist_to_struc (Optional[float], optional): The maximum distance from a node to a structure. If not specified, calculation will not take it into account. Defaults to None. Raises: ValueError: Raised when any of the structure offsets, if specified, is smaller than zero. ValueError: Raised when any of the structure offsets, if specified, is greater than the branch length. \"\"\" # Generate offsets self . branch_offsets = self . _generate_offsets ( mesh1d_edge_length , structure_chainage , max_dist_to_struc ) # Calculate node positions self . node_xy = self . interpolate ( self . branch_offsets ) # Add mask (all False) self . mask = np . full ( self . branch_offsets . shape , False )","title":"generate_nodes()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Branch.interpolate","text":"Interpolate coordinates along branch by length Parameters: Name Type Description Default distance npt.ArrayLike Length required Source code in hydrolib/core/dflowfm/net/models.py def interpolate ( self , distance : npt . ArrayLike ) -> np . ndarray : \"\"\"Interpolate coordinates along branch by length Args: distance (npt.ArrayLike): Length \"\"\" intpcoords = np . stack ( [ np . interp ( distance , self . _distance , self . _x_coordinates ), np . interp ( distance , self . _distance , self . _y_coordinates ), ], axis = 1 , ) return intpcoords","title":"interpolate()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Link1d2d","text":"Link1d2d defines the 1D2D Links of a model network. Attributes: Name Type Description meshkernel Optional[mk.MeshKernel] The MeshKernel used to interact with this Link1d2d link1d2d_id np.ndarray The id of this Link1d2d link1d2d_long_name np.ndarray The long name of this Link1d2d link1d2d_contact_type np.ndarray The contact type of this Link1d2d link1d2d np.ndarray The underlying data object of this Link1d2d","title":"Link1d2d"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Link1d2d.clear","text":"Remove all saved links from the links administration Source code in hydrolib/core/dflowfm/net/models.py def clear ( self ) -> None : \"\"\"Remove all saved links from the links administration\"\"\" self . link1d2d_id = np . empty ( 0 , object ) self . link1d2d_long_name = np . empty ( 0 , object ) self . link1d2d_contact_type = np . empty ( 0 , np . int32 ) self . link1d2d = np . empty (( 0 , 2 ), np . int32 ) # The meshkernel object needs to be resetted self . meshkernel . _deallocate_state () self . meshkernel . _allocate_state ( self . meshkernel . get_projection ()) self . meshkernel . contacts_get ()","title":"clear()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Link1d2d.is_empty","text":"Whether this Link1d2d is currently empty. Returns: Type Description bool True if the Link1d2d is currently empty; False otherwise. Source code in hydrolib/core/dflowfm/net/models.py def is_empty ( self ) -> bool : \"\"\"Whether this Link1d2d is currently empty. Returns: bool: True if the Link1d2d is currently empty; False otherwise. \"\"\" return self . link1d2d . size == 0","title":"is_empty()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Link1d2d.read_file","text":"Read the Link1d2d data from the specified netCDF file at file_path into this Parameters: Name Type Description Default file_path Path Path to the netCDF file. required Source code in hydrolib/core/dflowfm/net/models.py def read_file ( self , file_path : Path ) -> None : \"\"\"Read the Link1d2d data from the specified netCDF file at file_path into this Args: file_path (Path): Path to the netCDF file. \"\"\" reader = UgridReader ( file_path ) reader . read_link1d2d ( self )","title":"read_file()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh1d","text":"","title":"Mesh1d"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh1d.get_node_mask","text":"Get node mask, give a mask with True for each node that is in the given branchid list Source code in hydrolib/core/dflowfm/net/models.py def get_node_mask ( self , branchids : List [ str ] = None ): \"\"\"Get node mask, give a mask with True for each node that is in the given branchid list\"\"\" mask = np . full ( self . mesh1d_node_id . shape , False , dtype = bool ) if branchids is None : mask [:] = True return mask # Get number (index) of given branches idx = np . where ( np . isin ( self . network1d_branch_id , branchids ))[ 0 ] if idx . size == 0 : raise KeyError ( \"No branches corresponding to the given keys were found.\" ) mask [ np . isin ( self . mesh1d_node_branch_id , idx )] = True return mask","title":"get_node_mask()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d","text":"Mesh2d defines a single two dimensional grid. Attributes: Name Type Description meshkernel mk.MeshKernel The meshkernel used to manimpulate this Mesh2d. mesh2d_node_z np.ndarray The node positions on the z-axis. Defaults to np.empty(0, dtype=np.double). mesh2d_face_z np.ndarray The face positions on the z-axis. Defaults to np.empty(0, dtype=np.double).","title":"Mesh2d"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.clip","text":"Clip the 2D mesh by a polygon. Both outside the exterior and inside the interiors is clipped Parameters: Name Type Description Default geometrylist GeometryList Polygon stored as GeometryList required deletemeshoption int [description]. Defaults to 1. Source code in hydrolib/core/dflowfm/net/models.py def clip ( self , geometrylist : mk . GeometryList , deletemeshoption : mk . DeleteMeshOption = mk . DeleteMeshOption . INSIDE_NOT_INTERSECTED , inside = False , ) -> None : \"\"\"Clip the 2D mesh by a polygon. Both outside the exterior and inside the interiors is clipped Args: geometrylist (GeometryList): Polygon stored as GeometryList deletemeshoption (int, optional): [description]. Defaults to 1. \"\"\" # For clipping outside if not inside : # Check if a multipolygon was provided when clipping outside if geometrylist . geometry_separator in geometrylist . x_coordinates : raise NotImplementedError ( \"Deleting outside more than a single exterior (MultiPolygon) is not implemented.\" ) # Get exterior and interiors parts = split_by ( geometrylist , geometrylist . inner_outer_separator ) exteriors = [ parts [ 0 ]] interiors = parts [ 1 :] # Inside else : # Check if any polygon contains holes, when clipping inside if geometrylist . inner_outer_separator in geometrylist . x_coordinates : raise NotImplementedError ( \"Deleting inside a (Multi)Polygon with holes is not implemented.\" ) # Get exterior and interiors parts = split_by ( geometrylist , geometrylist . geometry_separator ) exteriors = parts [:] interiors = [] # Check if parts are closed for part in exteriors + interiors : if ( part . x_coordinates [ 0 ], part . y_coordinates [ 0 ]) != ( part . x_coordinates [ - 1 ], part . y_coordinates [ - 1 ], ): raise ValueError ( \"First and last coordinate of each GeometryList part should match.\" ) # Delete everything outside the (Multi)Polygon for exterior in exteriors : self . meshkernel . mesh2d_delete ( geometry_list = exterior , delete_option = deletemeshoption , invert_deletion = not inside , ) # Delete all holes. for interior in interiors : self . meshkernel . mesh2d_delete ( geometry_list = interior , delete_option = deletemeshoption , invert_deletion = inside , )","title":"clip()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.create_rectilinear","text":"Create a rectilinear mesh within a polygon. A rectangular grid is generated within the polygon bounds Parameters: Name Type Description Default extent tuple Bounding box of mesh (left, bottom, right, top) required dx float Horizontal distance required dy float Vertical distance required Exceptions: Type Description NotImplementedError MultiPolygons Source code in hydrolib/core/dflowfm/net/models.py def create_rectilinear ( self , extent : tuple , dx : float , dy : float ) -> None : \"\"\"Create a rectilinear mesh within a polygon. A rectangular grid is generated within the polygon bounds Args: extent (tuple): Bounding box of mesh (left, bottom, right, top) dx (float): Horizontal distance dy (float): Vertical distance Raises: NotImplementedError: MultiPolygons \"\"\" xmin , ymin , xmax , ymax = extent rows = int (( ymax - ymin ) / dy ) columns = int (( xmax - xmin ) / dx ) params = mk . MakeGridParameters ( num_columns = columns , num_rows = rows , origin_x = xmin , origin_y = ymin , block_size_x = dx , block_size_y = dy , ) mesh2d_input = self . meshkernel # mk.MeshKernel() mesh2d_input . curvilinear_compute_rectangular_grid ( params ) mesh2d_input . curvilinear_convert_to_mesh2d () # convert to ugrid/mesh2d","title":"create_rectilinear()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.create_triangular","text":"Create triangular grid within GeometryList object Parameters: Name Type Description Default geometry_list mk.GeometryList GeometryList represeting a polygon within which the mesh is generated. required Source code in hydrolib/core/dflowfm/net/models.py def create_triangular ( self , geometry_list : mk . GeometryList ) -> None : \"\"\"Create triangular grid within GeometryList object Args: geometry_list (mk.GeometryList): GeometryList represeting a polygon within which the mesh is generated. \"\"\" # Call meshkernel self . meshkernel . mesh2d_make_triangular_mesh_from_polygon ( geometry_list )","title":"create_triangular()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.get_mesh2d","text":"Get the mesh2d as represented in the MeshKernel Returns: Type Description (mk.Mesh2d) The mesh2d as represented in the MeshKernel Source code in hydrolib/core/dflowfm/net/models.py def get_mesh2d ( self ) -> mk . Mesh2d : \"\"\"Get the mesh2d as represented in the MeshKernel Returns: (mk.Mesh2d): The mesh2d as represented in the MeshKernel \"\"\" return self . meshkernel . mesh2d_get ()","title":"get_mesh2d()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.is_empty","text":"Determine whether this Mesh2d is empty. Returns: Type Description (bool) Whether this Mesh2d is empty. Source code in hydrolib/core/dflowfm/net/models.py def is_empty ( self ) -> bool : \"\"\"Determine whether this Mesh2d is empty. Returns: (bool): Whether this Mesh2d is empty. \"\"\" return self . mesh2d_node_x . size == 0","title":"is_empty()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.mesh2d_edge_nodes","text":"The node indices of the mesh edges. Returns: Type Description np.ndarray[int, int] A 2D integer array (nEdges, 2) containg the two node indices for each edge.","title":"mesh2d_edge_nodes"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.mesh2d_edge_x","text":"The x-coordinates of the mesh edges' middle points. Returns: Type Description ndarray[float] A 1D double array describing x-coordinates of the mesh edges' middle points.","title":"mesh2d_edge_x"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.mesh2d_edge_y","text":"The y-coordinates of the mesh edges' middle points. Returns: Type Description ndarray[float] A 1D double array describing y-coordinates of the mesh edges' middle points.","title":"mesh2d_edge_y"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.mesh2d_face_nodes","text":"The node indices of the mesh faces Returns: Type Description np.ndarray[int, int] A 2D integer array describing the nodes composing each mesh 2d face. A 2D integer array (nFaces, maxNodesPerFace) containg the node indices for each face.","title":"mesh2d_face_nodes"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.mesh2d_face_x","text":"The x-coordinates of the mesh faces' mass centers. Returns: Type Description ndarray[float] A 1D double array describing x-coordinates of the mesh faces' mass centers.","title":"mesh2d_face_x"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.mesh2d_face_y","text":"The y-coordinates of the mesh faces' mass centers. Returns: Type Description ndarray[float] A 1D double array describing y-coordinates of the mesh faces' mass centers.","title":"mesh2d_face_y"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.mesh2d_node_x","text":"The x-coordinates of the nodes in the mesh. Returns: Type Description ndarray[float] A 1D double array describing the x-coordinates of the nodes.","title":"mesh2d_node_x"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.mesh2d_node_y","text":"The y-coordinates of the nodes in the mesh. Returns: Type Description ndarray[float] A 1D double array describing the y-coordinates of the nodes.","title":"mesh2d_node_y"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.read_file","text":"Read the Mesh2d from the file at file_path. Parameters: Name Type Description Default file_path Path Path to the file to be read. required Source code in hydrolib/core/dflowfm/net/models.py def read_file ( self , file_path : Path ) -> None : \"\"\"Read the Mesh2d from the file at file_path. Args: file_path (Path): Path to the file to be read. \"\"\" reader = UgridReader ( file_path ) reader . read_mesh2d ( self )","title":"read_file()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.refine","text":"Refine the mesh within a polygon, by a number of steps (level) Parameters: Name Type Description Default polygon GeometryList Polygon in which to refine required level int Number of refinement steps required Source code in hydrolib/core/dflowfm/net/models.py def refine ( self , polygon : mk . GeometryList , level : int , min_edge_size = 10.0 ): \"\"\"Refine the mesh within a polygon, by a number of steps (level) Args: polygon (GeometryList): Polygon in which to refine level (int): Number of refinement steps \"\"\" # Check if parts are closed # if not (polygon.x_coordinates[0], polygon.y_coordinates[0]) == ( # polygon.x_coordinates[-1], # polygon.y_coordinates[-1], # ): # raise ValueError(\"First and last coordinate of each GeometryList part should match.\") parameters = mk . MeshRefinementParameters ( refine_intersected = True , use_mass_center_when_refining = False , min_edge_size = min_edge_size , # Does nothing? refinement_type = 1 , # No effect? connect_hanging_nodes = True , account_for_samples_outside_face = False , max_refinement_iterations = level , ) self . meshkernel . mesh2d_refine_based_on_polygon ( polygon , parameters )","title":"refine()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Network","text":"","title":"Network"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Network.from_file","text":"Read network from file. This classmethod checks what mesh components (mesh1d & network1d, mesh2d, link1d2d) are present, and loads them one by one. Parameters: Name Type Description Default file_path Path path to netcdf file with network data required Returns: Type Description Network The instance of the class itself that is returned Source code in hydrolib/core/dflowfm/net/models.py @classmethod def from_file ( cls , file_path : Path ) -> Network : \"\"\"Read network from file. This classmethod checks what mesh components (mesh1d & network1d, mesh2d, link1d2d) are present, and loads them one by one. Args: file_path (Path): path to netcdf file with network data Returns: Network: The instance of the class itself that is returned \"\"\" network = cls () ds = nc . Dataset ( file_path ) # type: ignore[import] reader = UgridReader ( file_path ) reader . read_mesh1d_network1d ( network . _mesh1d ) reader . read_mesh2d ( network . _mesh2d ) reader . read_link1d2d ( network . _link1d2d ) ds . close () return network","title":"from_file()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Network.is_geographic","text":"Whether or not this network has a geographic projection. Returns: Type Description bool True if this network is geographic; otherwise, False.","title":"is_geographic"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Network.mesh2d_create_triangular_within_polygon","text":"Create triangular grid within GeometryList object. Calls _mesh2d.create_triangular directly, but is easier accessible for users. Parameters: Name Type Description Default polygon mk.GeometryList GeometryList representing a polygon within which the mesh is generated. required Source code in hydrolib/core/dflowfm/net/models.py def mesh2d_create_triangular_within_polygon ( self , polygon : mk . GeometryList ) -> None : \"\"\"Create triangular grid within GeometryList object. Calls _mesh2d.create_triangular directly, but is easier accessible for users. Args: polygon (mk.GeometryList): GeometryList representing a polygon within which the mesh is generated. \"\"\" self . _mesh2d . create_triangular ( geometry_list = polygon )","title":"mesh2d_create_triangular_within_polygon()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Network.plot","text":"Create a plot of the 1d2d links and edges within this network. Parameters: Name Type Description Default ax matplotlib.pyplot.Axes The axes where to plot the edges. Defaults to None. None Source code in hydrolib/core/dflowfm/net/models.py def plot ( self , ax = None ): \"\"\"Create a plot of the 1d2d links and edges within this network. Args: ax (matplotlib.pyplot.Axes, optional): The axes where to plot the edges. Defaults to None. \"\"\" import matplotlib.pyplot as plt if ax is None : _ , ax = plt . subplots () mesh2d_output = self . _mesh2d . get_mesh2d () mesh1d_output = self . _mesh1d . _get_mesh1d () links_output = self . _link1d2d . meshkernel . contacts_get () mesh2d_output . plot_edges ( ax = ax , color = \"r\" ) mesh1d_output . plot_edges ( ax = ax , color = \"g\" ) links_output . plot_edges ( ax = ax , mesh1d = mesh1d_output , mesh2d = mesh2d_output , color = \"k\" )","title":"plot()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Network.to_file","text":"Write network to file Parameters: Name Type Description Default file Path File where _net.nc is written to. required Source code in hydrolib/core/dflowfm/net/models.py def to_file ( self , file : Path ) -> None : \"\"\"Write network to file Args: file (Path): File where _net.nc is written to. \"\"\" writer = UgridWriter () writer . write ( self , file )","title":"to_file()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.NetworkModel","text":"Network model representation.","title":"NetworkModel"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.split_by","text":"Function to split mk.GeometryList by seperator. Parameters: Name Type Description Default gl mk.GeometryList The geometry list to split. required by float The value by which to split the gl. required Returns: Type Description list The split lists. Source code in hydrolib/core/dflowfm/net/models.py def split_by ( gl : mk . GeometryList , by : float ) -> list : \"\"\"Function to split mk.GeometryList by seperator. Args: gl (mk.GeometryList): The geometry list to split. by (float): The value by which to split the gl. Returns: list: The split lists. \"\"\" x , y = gl . x_coordinates . copy (), gl . y_coordinates . copy () idx = np . where ( x == by )[ 0 ] xparts = np . split ( x , idx ) yparts = np . split ( y , idx ) lists = [ mk . GeometryList ( xp [ min ( i , 1 ) :], yp [ min ( i , 1 ) :]) for i , ( xp , yp ) in enumerate ( zip ( xparts , yparts )) ] return lists","title":"split_by()"},{"location":"reference/observationcrosssection/","text":"Observation cross section files \u00b6 Observation cross section files come in two flavours: the official *_crs.ini format see below the legacy *.pli format see below Observation cross section .ini files \u00b6 The obscrosssection module provides the specific logic for accessing observation cross section .ini files. for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. An observation cross section .ini file is described by the classes below. Model \u00b6 ObservationCrossSection ( INIBasedModel ) pydantic-model \u00b6 The observation cross section that is included in the observation cross section file. All lowercased attributes match with the observation cross section output as described in [UM Sec.F2.4.1] (https://content.oss.deltares.nl/delft3dfm1d2d/D-Flow_FM_User_Manual_1D2D.pdf#subsubsection.F.2.4.1) validate_that_location_specification_is_correct ( values : Dict ) -> Dict classmethod \u00b6 Validates that the correct location specification is given. Source code in hydrolib/core/dflowfm/obscrosssection/models.py @root_validator ( allow_reuse = True ) def validate_that_location_specification_is_correct ( cls , values : Dict ) -> Dict : \"\"\"Validates that the correct location specification is given.\"\"\" return validate_location_specification ( values , config = LocationValidationConfiguration ( validate_node = False , minimum_num_coordinates = 2 ), ) ObservationCrossSectionGeneral ( INIGeneral ) pydantic-model \u00b6 The observation cross section file's [General] section with file meta data. ObservationCrossSectionModel ( INIModel ) pydantic-model \u00b6 The overall observation cross section model that contains the contents of one observation cross section file. Legacy observation cross section .pli files \u00b6 Legacy .pli files for observation points are supported via the generic polyfile module. A polyfile (hence also an observation cross section .pli file) is described by the classes below. Model \u00b6 models.py defines all classes and functions related to representing pol/pli(z) files. Description ( BaseModel ) pydantic-model \u00b6 Description of a single PolyObject. The Description will be prepended to a block. Each line will start with a '*'. Attributes: Name Type Description content str The content of this Description. Metadata ( BaseModel ) pydantic-model \u00b6 Metadata of a single PolyObject. Attributes: Name Type Description name str The name of the PolyObject n_rows int The number of rows (i.e. Point instances) of the PolyObject n_columns int The total number of values in a Point, including x, y, and z. Point ( BaseModel ) pydantic-model \u00b6 Point consisting of a x and y coordinate, an optional z coordinate and data. Attributes: Name Type Description x float The x-coordinate of this Point y float The y-coordinate of this Point z Optional[float] An optional z-coordinate of this Point. data Sequence[float] The additional data variables of this Point. PolyFile ( ParsableFileModel ) pydantic-model \u00b6 Poly-file (.pol/.pli/.pliz) representation. PolyObject ( BaseModel ) pydantic-model \u00b6 PolyObject describing a single block in a poly file. The metadata should be consistent with the points: - The number of points should be equal to number of rows defined in the metadata - The data of each point should be equal to the number of columns defined in the metadata. Attributes: Name Type Description description Optional[Description] An optional description of this PolyObject metadata Metadata The Metadata of this PolObject, describing the structure points List[Point] The points describing this PolyObject, structured according to the Metadata","title":"Observation cross section files"},{"location":"reference/observationcrosssection/#observation-cross-section-files","text":"Observation cross section files come in two flavours: the official *_crs.ini format see below the legacy *.pli format see below","title":"Observation cross section files"},{"location":"reference/observationcrosssection/#observation-cross-section-ini-files","text":"The obscrosssection module provides the specific logic for accessing observation cross section .ini files. for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. An observation cross section .ini file is described by the classes below.","title":"Observation cross section .ini files"},{"location":"reference/observationcrosssection/#model","text":"","title":"Model"},{"location":"reference/observationcrosssection/#hydrolib.core.dflowfm.obscrosssection.models.ObservationCrossSection","text":"The observation cross section that is included in the observation cross section file. All lowercased attributes match with the observation cross section output as described in [UM Sec.F2.4.1] (https://content.oss.deltares.nl/delft3dfm1d2d/D-Flow_FM_User_Manual_1D2D.pdf#subsubsection.F.2.4.1)","title":"ObservationCrossSection"},{"location":"reference/observationcrosssection/#hydrolib.core.dflowfm.obscrosssection.models.ObservationCrossSection.validate_that_location_specification_is_correct","text":"Validates that the correct location specification is given. Source code in hydrolib/core/dflowfm/obscrosssection/models.py @root_validator ( allow_reuse = True ) def validate_that_location_specification_is_correct ( cls , values : Dict ) -> Dict : \"\"\"Validates that the correct location specification is given.\"\"\" return validate_location_specification ( values , config = LocationValidationConfiguration ( validate_node = False , minimum_num_coordinates = 2 ), )","title":"validate_that_location_specification_is_correct()"},{"location":"reference/observationcrosssection/#hydrolib.core.dflowfm.obscrosssection.models.ObservationCrossSectionGeneral","text":"The observation cross section file's [General] section with file meta data.","title":"ObservationCrossSectionGeneral"},{"location":"reference/observationcrosssection/#hydrolib.core.dflowfm.obscrosssection.models.ObservationCrossSectionModel","text":"The overall observation cross section model that contains the contents of one observation cross section file.","title":"ObservationCrossSectionModel"},{"location":"reference/observationcrosssection/#legacy-observation-cross-section-pli-files","text":"Legacy .pli files for observation points are supported via the generic polyfile module. A polyfile (hence also an observation cross section .pli file) is described by the classes below.","title":"Legacy observation cross section .pli files"},{"location":"reference/observationcrosssection/#model_1","text":"models.py defines all classes and functions related to representing pol/pli(z) files.","title":"Model"},{"location":"reference/observationcrosssection/#hydrolib.core.dflowfm.polyfile.models.Description","text":"Description of a single PolyObject. The Description will be prepended to a block. Each line will start with a '*'. Attributes: Name Type Description content str The content of this Description.","title":"Description"},{"location":"reference/observationcrosssection/#hydrolib.core.dflowfm.polyfile.models.Metadata","text":"Metadata of a single PolyObject. Attributes: Name Type Description name str The name of the PolyObject n_rows int The number of rows (i.e. Point instances) of the PolyObject n_columns int The total number of values in a Point, including x, y, and z.","title":"Metadata"},{"location":"reference/observationcrosssection/#hydrolib.core.dflowfm.polyfile.models.Point","text":"Point consisting of a x and y coordinate, an optional z coordinate and data. Attributes: Name Type Description x float The x-coordinate of this Point y float The y-coordinate of this Point z Optional[float] An optional z-coordinate of this Point. data Sequence[float] The additional data variables of this Point.","title":"Point"},{"location":"reference/observationcrosssection/#hydrolib.core.dflowfm.polyfile.models.PolyFile","text":"Poly-file (.pol/.pli/.pliz) representation.","title":"PolyFile"},{"location":"reference/observationcrosssection/#hydrolib.core.dflowfm.polyfile.models.PolyObject","text":"PolyObject describing a single block in a poly file. The metadata should be consistent with the points: - The number of points should be equal to number of rows defined in the metadata - The data of each point should be equal to the number of columns defined in the metadata. Attributes: Name Type Description description Optional[Description] An optional description of this PolyObject metadata Metadata The Metadata of this PolObject, describing the structure points List[Point] The points describing this PolyObject, structured according to the Metadata","title":"PolyObject"},{"location":"reference/observationpoint/","text":"Observation point files \u00b6 Observation point files come in two flavours: the official *_obs.ini format see below the legacy *.xyn format see below Observation point .ini files \u00b6 The obs module provides the specific logic for accessing observation point .ini files for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. An observation point .ini file is described by the classes below. Model \u00b6 ObservationPoint ( INIBasedModel ) pydantic-model \u00b6 An observation point that is included in the observation point file. All lowercased attributes match with the observation point input as described in UM Sec.F.2.2.1 . validate_that_location_specification_is_correct ( values : Dict ) -> Dict classmethod \u00b6 Validates that the correct location specification is given. Source code in hydrolib/core/dflowfm/obs/models.py @root_validator ( allow_reuse = True ) def validate_that_location_specification_is_correct ( cls , values : Dict ) -> Dict : \"\"\"Validates that the correct location specification is given.\"\"\" return validate_location_specification ( values , config = LocationValidationConfiguration ( validate_node = False , validate_num_coordinates = False ), fields = LocationValidationFieldNames ( x_coordinates = \"x\" , y_coordinates = \"y\" ), ) ObservationPointGeneral ( INIGeneral ) pydantic-model \u00b6 The observation point file's [General] section with file meta data. ObservationPointModel ( INIModel ) pydantic-model \u00b6 The overall observation point model that contains the contents of one observation point file. This model is typically referenced under a FMModel .output.obsfile[..] . Attributes: Name Type Description general ObservationPointGeneral [General] block with file metadata. observationpoint List[ObservationPoint] List of [ObservationPoint] blocks for all observation points. Legacy observation point .xyn files \u00b6 The xyn module provides the specific logic for accessing legacy observation point files for a D-Flow FM model. An observation point .xyn file is described by the classes below. Model \u00b6 XYNModel ( ParsableFileModel ) pydantic-model \u00b6 Observation station (.xyn) file. dict ( self , * args , ** kwargs ) \u00b6 Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dflowfm/xyn/models.py def dict ( self , * args , ** kwargs ): # speed up serializing by not converting these lowest models to dict return dict ( points = self . points ) XYNPoint ( BaseModel ) pydantic-model \u00b6 Single XYN point, representing a named station location.","title":"Observation point files"},{"location":"reference/observationpoint/#observation-point-files","text":"Observation point files come in two flavours: the official *_obs.ini format see below the legacy *.xyn format see below","title":"Observation point files"},{"location":"reference/observationpoint/#observation-point-ini-files","text":"The obs module provides the specific logic for accessing observation point .ini files for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. An observation point .ini file is described by the classes below.","title":"Observation point .ini files"},{"location":"reference/observationpoint/#model","text":"","title":"Model"},{"location":"reference/observationpoint/#hydrolib.core.dflowfm.obs.models.ObservationPoint","text":"An observation point that is included in the observation point file. All lowercased attributes match with the observation point input as described in UM Sec.F.2.2.1 .","title":"ObservationPoint"},{"location":"reference/observationpoint/#hydrolib.core.dflowfm.obs.models.ObservationPoint.validate_that_location_specification_is_correct","text":"Validates that the correct location specification is given. Source code in hydrolib/core/dflowfm/obs/models.py @root_validator ( allow_reuse = True ) def validate_that_location_specification_is_correct ( cls , values : Dict ) -> Dict : \"\"\"Validates that the correct location specification is given.\"\"\" return validate_location_specification ( values , config = LocationValidationConfiguration ( validate_node = False , validate_num_coordinates = False ), fields = LocationValidationFieldNames ( x_coordinates = \"x\" , y_coordinates = \"y\" ), )","title":"validate_that_location_specification_is_correct()"},{"location":"reference/observationpoint/#hydrolib.core.dflowfm.obs.models.ObservationPointGeneral","text":"The observation point file's [General] section with file meta data.","title":"ObservationPointGeneral"},{"location":"reference/observationpoint/#hydrolib.core.dflowfm.obs.models.ObservationPointModel","text":"The overall observation point model that contains the contents of one observation point file. This model is typically referenced under a FMModel .output.obsfile[..] . Attributes: Name Type Description general ObservationPointGeneral [General] block with file metadata. observationpoint List[ObservationPoint] List of [ObservationPoint] blocks for all observation points.","title":"ObservationPointModel"},{"location":"reference/observationpoint/#legacy-observation-point-xyn-files","text":"The xyn module provides the specific logic for accessing legacy observation point files for a D-Flow FM model. An observation point .xyn file is described by the classes below.","title":"Legacy observation point .xyn files"},{"location":"reference/observationpoint/#model_1","text":"","title":"Model"},{"location":"reference/observationpoint/#hydrolib.core.dflowfm.xyn.models.XYNModel","text":"Observation station (.xyn) file.","title":"XYNModel"},{"location":"reference/observationpoint/#hydrolib.core.dflowfm.xyn.models.XYNModel.dict","text":"Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dflowfm/xyn/models.py def dict ( self , * args , ** kwargs ): # speed up serializing by not converting these lowest models to dict return dict ( points = self . points )","title":"dict()"},{"location":"reference/observationpoint/#hydrolib.core.dflowfm.xyn.models.XYNPoint","text":"Single XYN point, representing a named station location.","title":"XYNPoint"},{"location":"reference/onedfield/","text":"1D field INI files \u00b6 The 1D field INI files contain the spatial input data for 1D network initial conditions for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. The 1D field INI file is represented by the classes below. Model \u00b6 OneDFieldBranch ( INIBasedModel ) pydantic-model \u00b6 A [Branch] block for use inside a 1D field file. Each block can define value(s) on a particular branch. check_list_length_chainage ( values ) classmethod \u00b6 Validates that the length of the chainage field is as expected. Source code in hydrolib/core/dflowfm/onedfield/models.py @root_validator ( allow_reuse = True ) def check_list_length_chainage ( cls , values ): \"\"\"Validates that the length of the chainage field is as expected.\"\"\" return validate_correct_length ( values , \"chainage\" , length_name = \"numlocations\" , list_required_with_length = True , ) check_list_length_values ( values ) classmethod \u00b6 Validates that the length of the values field is as expected. Source code in hydrolib/core/dflowfm/onedfield/models.py @root_validator ( allow_reuse = True ) def check_list_length_values ( cls , values ): \"\"\"Validates that the length of the values field is as expected.\"\"\" return validate_correct_length ( values , \"values\" , length_name = \"numlocations\" , list_required_with_length = True , min_length = 1 , ) OneDFieldGeneral ( INIGeneral ) pydantic-model \u00b6 The 1D field file's [General] section with file meta data. OneDFieldGlobal ( INIBasedModel ) pydantic-model \u00b6 The [Global] block with a uniform value for use inside a 1D field file. OneDFieldModel ( INIModel ) pydantic-model \u00b6 The overall 1D field model that contains the contents of a 1D field file. This model is typically used when a FMModel .geometry.inifieldfile[..].initial[..].datafiletype==DataFileType.onedfield . Attributes: Name Type Description general OneDFieldGeneral [General] block with file metadata. global_ Optional[OneDFieldGlobal] Optional [Global] block with uniform value. branch List[OneDFieldBranch] Definitions of [Branch] field values.","title":"1D field INI files"},{"location":"reference/onedfield/#1d-field-ini-files","text":"The 1D field INI files contain the spatial input data for 1D network initial conditions for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. The 1D field INI file is represented by the classes below.","title":"1D field INI files"},{"location":"reference/onedfield/#model","text":"","title":"Model"},{"location":"reference/onedfield/#hydrolib.core.dflowfm.onedfield.models.OneDFieldBranch","text":"A [Branch] block for use inside a 1D field file. Each block can define value(s) on a particular branch.","title":"OneDFieldBranch"},{"location":"reference/onedfield/#hydrolib.core.dflowfm.onedfield.models.OneDFieldBranch.check_list_length_chainage","text":"Validates that the length of the chainage field is as expected. Source code in hydrolib/core/dflowfm/onedfield/models.py @root_validator ( allow_reuse = True ) def check_list_length_chainage ( cls , values ): \"\"\"Validates that the length of the chainage field is as expected.\"\"\" return validate_correct_length ( values , \"chainage\" , length_name = \"numlocations\" , list_required_with_length = True , )","title":"check_list_length_chainage()"},{"location":"reference/onedfield/#hydrolib.core.dflowfm.onedfield.models.OneDFieldBranch.check_list_length_values","text":"Validates that the length of the values field is as expected. Source code in hydrolib/core/dflowfm/onedfield/models.py @root_validator ( allow_reuse = True ) def check_list_length_values ( cls , values ): \"\"\"Validates that the length of the values field is as expected.\"\"\" return validate_correct_length ( values , \"values\" , length_name = \"numlocations\" , list_required_with_length = True , min_length = 1 , )","title":"check_list_length_values()"},{"location":"reference/onedfield/#hydrolib.core.dflowfm.onedfield.models.OneDFieldGeneral","text":"The 1D field file's [General] section with file meta data.","title":"OneDFieldGeneral"},{"location":"reference/onedfield/#hydrolib.core.dflowfm.onedfield.models.OneDFieldGlobal","text":"The [Global] block with a uniform value for use inside a 1D field file.","title":"OneDFieldGlobal"},{"location":"reference/onedfield/#hydrolib.core.dflowfm.onedfield.models.OneDFieldModel","text":"The overall 1D field model that contains the contents of a 1D field file. This model is typically used when a FMModel .geometry.inifieldfile[..].initial[..].datafiletype==DataFileType.onedfield . Attributes: Name Type Description general OneDFieldGeneral [General] block with file metadata. global_ Optional[OneDFieldGlobal] Optional [Global] block with uniform value. branch List[OneDFieldBranch] Definitions of [Branch] field values.","title":"OneDFieldModel"},{"location":"reference/polyfile/","text":"Polyline/polygon files \u00b6 Polyline .pli(z) and polygon .pol files are basic spatial input files for a D-Flow FM model to select particular locations, and are used in various other input files. They are represented by the classes below. Model \u00b6 models.py defines all classes and functions related to representing pol/pli(z) files. Description ( BaseModel ) pydantic-model \u00b6 Description of a single PolyObject. The Description will be prepended to a block. Each line will start with a '*'. Attributes: Name Type Description content str The content of this Description. Metadata ( BaseModel ) pydantic-model \u00b6 Metadata of a single PolyObject. Attributes: Name Type Description name str The name of the PolyObject n_rows int The number of rows (i.e. Point instances) of the PolyObject n_columns int The total number of values in a Point, including x, y, and z. Point ( BaseModel ) pydantic-model \u00b6 Point consisting of a x and y coordinate, an optional z coordinate and data. Attributes: Name Type Description x float The x-coordinate of this Point y float The y-coordinate of this Point z Optional[float] An optional z-coordinate of this Point. data Sequence[float] The additional data variables of this Point. PolyFile ( ParsableFileModel ) pydantic-model \u00b6 Poly-file (.pol/.pli/.pliz) representation. PolyObject ( BaseModel ) pydantic-model \u00b6 PolyObject describing a single block in a poly file. The metadata should be consistent with the points: - The number of points should be equal to number of rows defined in the metadata - The data of each point should be equal to the number of columns defined in the metadata. Attributes: Name Type Description description Optional[Description] An optional description of this PolyObject metadata Metadata The Metadata of this PolObject, describing the structure points List[Point] The points describing this PolyObject, structured according to the Metadata Parser \u00b6 parser.py defines all classes and functions related to parsing pol/pli(z) files. Block ( BaseModel ) pydantic-model \u00b6 Block is a temporary object which will be converted into a PolyObject. The fields are supposed to be set during the lifetime of this object. When all fields are set, finalize can be called. Attributes: Name Type Description start_line int The starting line of this current block. name Optional[str] The name of this block. Defaults to None. dimensions Optional[Tuple[int, int]] The dimensions (n_rows, n_columns) of this Block. Defaults to None. points Optional[List[Point]] The points of this block. Defaults to None. ws_warnings List[ParseMsg] The whitespace warnings associated with this block. Defaults to an empty list. empty_lines List[int] The line numbers of the empty lines. Defaults to an empty list. finalize ( self ) -> Optional [ Tuple [ hydrolib . core . dflowfm . polyfile . models . PolyObject , List [ hydrolib . core . dflowfm . polyfile . parser . ParseMsg ]]] \u00b6 Finalise this Block and return the constructed PolyObject and warnings If the metadata or the points are None, then None is returned. Returns: Type Description Optional[Tuple[PolyObject, List[ParseMsg]]] The constructed PolyObject and warnings encountered while parsing it. Source code in hydrolib/core/dflowfm/polyfile/parser.py def finalize ( self ) -> Optional [ Tuple [ PolyObject , List [ ParseMsg ]]]: \"\"\"Finalise this Block and return the constructed PolyObject and warnings If the metadata or the points are None, then None is returned. Returns: Optional[Tuple[PolyObject, List[ParseMsg]]]: The constructed PolyObject and warnings encountered while parsing it. \"\"\" metadata = self . _get_metadata () if metadata is None or self . points is None : return None obj = PolyObject ( description = self . _get_description (), metadata = metadata , points = self . points ) return obj , self . ws_warnings + self . _get_empty_line_warnings () ErrorBuilder \u00b6 ErrorBuilder provides the functionality to the Parser to keep track of errors. __init__ ( self ) -> None special \u00b6 Create a new ErorrorBuilder Source code in hydrolib/core/dflowfm/polyfile/parser.py def __init__ ( self ) -> None : \"\"\"Create a new ErorrorBuilder\"\"\" self . _current_block : Optional [ InvalidBlock ] = None end_invalid_block ( self , line : int ) -> None \u00b6 Store the end line of the current block If no invalid block currently exists, nothing will be done. Parameters: Name Type Description Default line int the final line of this invalid block required Source code in hydrolib/core/dflowfm/polyfile/parser.py def end_invalid_block ( self , line : int ) -> None : \"\"\"Store the end line of the current block If no invalid block currently exists, nothing will be done. Args: line (int): the final line of this invalid block \"\"\" if self . _current_block is not None : self . _current_block . end_line = line finalize_previous_error ( self ) -> Optional [ hydrolib . core . dflowfm . polyfile . parser . ParseMsg ] \u00b6 Finalize the current invalid block if it exists If no current invalid block exists, None will be returned, and nothing will change. If a current block exists, it will be converted into a ParseMsg and returned. The current invalid block will be reset. Returns: Type Description Optional[ParseMsg] The corresponding ParseMsg if an InvalidBlock exists. Source code in hydrolib/core/dflowfm/polyfile/parser.py def finalize_previous_error ( self ) -> Optional [ ParseMsg ]: \"\"\"Finalize the current invalid block if it exists If no current invalid block exists, None will be returned, and nothing will change. If a current block exists, it will be converted into a ParseMsg and returned. The current invalid block will be reset. Returns: Optional[ParseMsg]: The corresponding ParseMsg if an InvalidBlock exists. \"\"\" if self . _current_block is not None : msg = self . _current_block . to_msg () self . _current_block = None return msg else : return None start_invalid_block ( self , block_start : int , invalid_line : int , reason : str ) -> None \u00b6 Start a new invalid block if none exists at the moment If we are already in an invalid block, or the previous one was never finalised, we will not log the reason, and assume it is one long invalid block. Parameters: Name Type Description Default block_start int The start of the invalid block. required invalid_line int The actual offending line number. required reason str The reason why this block is invalid. required Source code in hydrolib/core/dflowfm/polyfile/parser.py def start_invalid_block ( self , block_start : int , invalid_line : int , reason : str ) -> None : \"\"\"Start a new invalid block if none exists at the moment If we are already in an invalid block, or the previous one was never finalised, we will not log the reason, and assume it is one long invalid block. Args: block_start (int): The start of the invalid block. invalid_line (int): The actual offending line number. reason (str): The reason why this block is invalid. \"\"\" if self . _current_block is None : self . _current_block = InvalidBlock ( start_line = block_start , invalid_line = invalid_line , reason = reason ) InvalidBlock ( BaseModel ) pydantic-model \u00b6 InvalidBlock is a temporary object which will be converted into a ParseMsg. Attributes: Name Type Description start_line int The start line of this InvalidBlock end_line Optional[int] The end line of this InvalidBlock if it is set. Defaults to None. invalid_line int The line which is causing this block to be invalid. reason str A human-readable string detailing the reason of the ParseMsg. to_msg ( self ) -> ParseMsg \u00b6 Convert this InvalidBlock to the corresponding ParseMsg Returns: Type Description ParseMsg The ParseMsg corresponding with this InvalidBlock Source code in hydrolib/core/dflowfm/polyfile/parser.py def to_msg ( self ) -> ParseMsg : \"\"\"Convert this InvalidBlock to the corresponding ParseMsg Returns: ParseMsg: The ParseMsg corresponding with this InvalidBlock \"\"\" return ParseMsg ( line_start = self . start_line , line_end = self . end_line , reason = f \" { self . reason } at line { self . invalid_line } .\" , ) ParseMsg ( BaseModel ) pydantic-model \u00b6 ParseMsg defines a single message indicating a significant parse event. Attributes: Name Type Description line_start int The start line of the block to which this ParseMsg refers. line_end int The end line of the block to which this ParseMsg refers. column Optional[Tuple[int, int]] An optional begin and end column to which this ParseMsg refers. reason str A human-readable string detailing the reason of the ParseMsg. format_parsemsg_to_string ( self , file_path : Optional [ pathlib . Path ] = None ) -> str \u00b6 Format string describing this ParseMsg Parameters: Name Type Description Default file_path Optional[Path] The file path mentioned in the message if specified. Defaults to None. None Source code in hydrolib/core/dflowfm/polyfile/parser.py def format_parsemsg_to_string ( self , file_path : Optional [ Path ] = None ) -> str : \"\"\"Format string describing this ParseMsg Args: file_path (Optional[Path], optional): The file path mentioned in the message if specified. Defaults to None. \"\"\" if self . line_start != self . line_end : block_suffix = f \" \\n Invalid block { self . line_start } : { self . line_end } \" else : block_suffix = f \" \\n Invalid line { self . line_start } \" col_suffix = ( f \" \\n Columns { self . column [ 0 ] } : { self . column [ 1 ] } \" if self . column is not None else \"\" ) file_suffix = f \" \\n File: { file_path } \" if file_path is not None else \"\" message = f \" { self . reason }{ block_suffix }{ col_suffix }{ file_suffix } \" return message Parser \u00b6 Parser provides the functionality to parse a polyfile line by line. The Parser parses blocks describing PolyObject instances by relying on a rudimentary state machine. The states are encoded with the StateType. New lines are fed through the feed_line method. After each line the internal state will be updated. When a complete block is read, it will be converted into a PolyObject and stored internally. When finalise is called, the constructed objects, as well as any warnings and errors describing invalid blocks, will be returned. Each state defines a feed_line method, stored in the _feed_line dict, which consumes a line and potentially transitions the state into the next. Each state further defines a finalise method, stored in the _finalise dict, which is called upon finalising the parser. Invalid states are encoded with INVALID_STATE. In this state the Parser attempts to find a new block, and thus looks for a new description or name. Unexpected whitespace before comments, names, and dimensions, as well as empty lines will generate a warning, and will be ignored by the parser. __init__ ( self , file_path : Path , has_z_value : bool = False ) -> None special \u00b6 Create a new Parser Parameters: Name Type Description Default file_path Path Name of the file being parsed, only used for providing proper warnings. required has_z_value bool Whether to interpret the third column as z-coordinates. Defaults to False. False Source code in hydrolib/core/dflowfm/polyfile/parser.py def __init__ ( self , file_path : Path , has_z_value : bool = False ) -> None : \"\"\"Create a new Parser Args: file_path (Path): Name of the file being parsed, only used for providing proper warnings. has_z_value (bool, optional): Whether to interpret the third column as z-coordinates. Defaults to False. \"\"\" self . _has_z_value = has_z_value self . _file_path = file_path self . _line = 0 self . _new_block () self . _error_builder = ErrorBuilder () self . _poly_objects : List [ PolyObject ] = [] self . _current_point : int = 0 self . _feed_line : Dict [ StateType , Callable [[ str ], None ]] = { StateType . NEW_BLOCK : self . _parse_name_or_new_description , StateType . PARSED_DESCRIPTION : self . _parse_name_or_next_description , StateType . PARSED_NAME : self . _parse_dimensions , StateType . PARSING_POINTS : self . _parse_next_point , StateType . INVALID_STATE : self . _parse_name_or_new_description , } self . _finalise : Dict [ StateType , Callable [[], None ]] = { StateType . NEW_BLOCK : self . _noop , StateType . PARSED_DESCRIPTION : self . _add_current_block_as_incomplete_error , StateType . PARSED_NAME : self . _add_current_block_as_incomplete_error , StateType . PARSING_POINTS : self . _add_current_block_as_incomplete_error , StateType . INVALID_STATE : self . _noop , } feed_line ( self , line : str ) -> None \u00b6 Parse the next line with this Parser. Parameters: Name Type Description Default line str The line to parse required Source code in hydrolib/core/dflowfm/polyfile/parser.py def feed_line ( self , line : str ) -> None : \"\"\"Parse the next line with this Parser. Args: line (str): The line to parse \"\"\" if not Parser . _is_empty_line ( line ): self . _feed_line [ self . _state ]( line ) else : self . _handle_empty_line () self . _increment_line () finalize ( self ) -> Sequence [ hydrolib . core . dflowfm . polyfile . models . PolyObject ] \u00b6 Finalize parsing and return the constructed PolyObject. Exceptions: Type Description ValueError When the plifile is invalid. Returns: Type Description PolyObject A PolyObject containing the constructed PolyObject instances. Source code in hydrolib/core/dflowfm/polyfile/parser.py def finalize ( self ) -> Sequence [ PolyObject ]: \"\"\"Finalize parsing and return the constructed PolyObject. Raises: ValueError: When the plifile is invalid. Returns: PolyObject: A PolyObject containing the constructed PolyObject instances. \"\"\" self . _error_builder . end_invalid_block ( self . _line ) last_error_msg = self . _error_builder . finalize_previous_error () if last_error_msg is not None : self . _notify_as_error ( last_error_msg ) self . _finalise [ self . _state ]() return self . _poly_objects StateType ( IntEnum ) \u00b6 The types of state of a Parser. read_polyfile ( filepath : Path , has_z_values : Optional [ bool ] = None ) -> Dict \u00b6 Read the specified file and return the corresponding data. The file is expected to follow the .pli(z) / .pol convention. A .pli(z) or .pol file is defined as consisting of a number of blocks of lines adhering to the following format: Optional description record consisting of one or more lines starting with '*'. These will be ignored. Name consisting of a non-blank character string Two integers, Nr and Nc, representing the numbers of rows and columns respectively Nr number of data points, consisting of Nc floats separated by whitespace For example: ... * * Polyline L008 * L008 4 2 131595.0 549685.0 131750.0 549865.0 131595.0 550025.0 131415.0 550175.0 ... Note that the points can be arbitrarily indented, and the comments are optional. if no has_z_value has been defined, it will be based on the file path extensions of the filepath: - .pliz will default to True - .pli and .pol will default to False Empty lines and unexpected whitespace will be flagged as warnings, and ignored. If invalid syntax is detected within a block, an error will be created. This block will be ignored for the purpose of creating PolyObject instances. Once an error is encountered, any following lines will be marked as part of the invalid block, until a new valid block is found. Note that this means that sequential invalid blocks will be reported as a single invalid block. Such invalid blocks will be reported as warnings. Parameters: Name Type Description Default filepath Path Path to the pli(z)/pol convention structured file. required has_z_values Optional[bool] Whether to create points containing a z-value. Defaults to None. None Exceptions: Type Description ValueError When the plifile is invalid. Returns: Type Description Dict The dictionary describing the data of a PolyObject. Source code in hydrolib/core/dflowfm/polyfile/parser.py def read_polyfile ( filepath : Path , has_z_values : Optional [ bool ] = None ) -> Dict : \"\"\"Read the specified file and return the corresponding data. The file is expected to follow the .pli(z) / .pol convention. A .pli(z) or .pol file is defined as consisting of a number of blocks of lines adhering to the following format: - Optional description record consisting of one or more lines starting with '*'. These will be ignored. - Name consisting of a non-blank character string - Two integers, Nr and Nc, representing the numbers of rows and columns respectively - Nr number of data points, consisting of Nc floats separated by whitespace For example: ``` ... * * Polyline L008 * L008 4 2 131595.0 549685.0 131750.0 549865.0 131595.0 550025.0 131415.0 550175.0 ... ``` Note that the points can be arbitrarily indented, and the comments are optional. if no has_z_value has been defined, it will be based on the file path extensions of the filepath: - .pliz will default to True - .pli and .pol will default to False Empty lines and unexpected whitespace will be flagged as warnings, and ignored. If invalid syntax is detected within a block, an error will be created. This block will be ignored for the purpose of creating PolyObject instances. Once an error is encountered, any following lines will be marked as part of the invalid block, until a new valid block is found. Note that this means that sequential invalid blocks will be reported as a single invalid block. Such invalid blocks will be reported as warnings. Args: filepath: Path to the pli(z)/pol convention structured file. has_z_values: Whether to create points containing a z-value. Defaults to None. Raises: ValueError: When the plifile is invalid. Returns: Dict: The dictionary describing the data of a PolyObject. \"\"\" if has_z_values is None : has_z_values = _determine_has_z_value ( filepath ) parser = Parser ( filepath , has_z_value = has_z_values ) with filepath . open ( \"r\" , encoding = \"utf8\" ) as f : for line in f : parser . feed_line ( line ) objs = parser . finalize () return { \"has_z_values\" : has_z_values , \"objects\" : objs } Serializer \u00b6 Serializer \u00b6 Serializer provides several static serialize methods for the models. serialize_description ( description : Optional [ hydrolib . core . dflowfm . polyfile . models . Description ]) -> Iterable [ str ] staticmethod \u00b6 Serialize the Description to a string which can be used within a polyfile. Returns: Type Description str The serialised equivalent of this Description Source code in hydrolib/core/dflowfm/polyfile/serializer.py @staticmethod def serialize_description ( description : Optional [ Description ]) -> Iterable [ str ]: \"\"\"Serialize the Description to a string which can be used within a polyfile. Returns: str: The serialised equivalent of this Description \"\"\" if description is None : return [] if description . content == \"\" : return [ \"*\" , ] return ( f \"* { v . rstrip () } \" for v in ( description . content + \" \\n \" ) . splitlines ()) serialize_metadata ( metadata : Metadata ) -> Iterable [ str ] staticmethod \u00b6 Serialize this Metadata to a string which can be used within a polyfile. The number of rows and number of columns are separated by four spaces. Returns: Type Description str The serialised equivalent of this Metadata Source code in hydrolib/core/dflowfm/polyfile/serializer.py @staticmethod def serialize_metadata ( metadata : Metadata ) -> Iterable [ str ]: \"\"\"Serialize this Metadata to a string which can be used within a polyfile. The number of rows and number of columns are separated by four spaces. Returns: str: The serialised equivalent of this Metadata \"\"\" return [ metadata . name , f \" { metadata . n_rows } { metadata . n_columns } \" ] serialize_point ( point : Point , config : SerializerConfig ) -> str staticmethod \u00b6 Serialize this Point to a string which can be used within a polyfile. the point data is indented with 4 spaces, and the individual values are separated by 4 spaces as well. Parameters: Name Type Description Default point Point The point to serialize. required config SerializerConfig The serialization configuration. required Returns: Type Description str The serialised equivalent of this Point Source code in hydrolib/core/dflowfm/polyfile/serializer.py @staticmethod def serialize_point ( point : Point , config : SerializerConfig ) -> str : \"\"\"Serialize this Point to a string which can be used within a polyfile. the point data is indented with 4 spaces, and the individual values are separated by 4 spaces as well. Args: point (Point): The point to serialize. config (SerializerConfig): The serialization configuration. Returns: str: The serialised equivalent of this Point \"\"\" space = 4 * \" \" float_format = lambda v : f \" { v :{ config . float_format }} \" return space + space . join ( float_format ( v ) for v in Serializer . _get_point_values ( point ) ) serialize_poly_object ( obj : PolyObject , config : SerializerConfig ) -> Iterable [ str ] staticmethod \u00b6 Serialize this PolyObject to a string which can be used within a polyfile. Parameters: Name Type Description Default obj PolyObject The poly object to serializer. required config SerializerConfig The serialization configuration. required Returns: Type Description str The serialised equivalent of this PolyObject Source code in hydrolib/core/dflowfm/polyfile/serializer.py @staticmethod def serialize_poly_object ( obj : PolyObject , config : SerializerConfig ) -> Iterable [ str ]: \"\"\"Serialize this PolyObject to a string which can be used within a polyfile. Args: obj (PolyObject): The poly object to serializer. config (SerializerConfig): The serialization configuration. Returns: str: The serialised equivalent of this PolyObject \"\"\" description = Serializer . serialize_description ( obj . description ) metadata = Serializer . serialize_metadata ( obj . metadata ) points = [ Serializer . serialize_point ( obj , config ) for obj in obj . points ] return chain ( description , metadata , points ) write_polyfile ( path : Path , data : Sequence [ hydrolib . core . dflowfm . polyfile . models . PolyObject ], config : SerializerConfig ) -> None \u00b6 Write the data to a new file at path Parameters: Name Type Description Default path Path The path to write the data to required data Sequence[PolyObject] The poly objects to write required config SerializerConfig The serialization configuration. required Source code in hydrolib/core/dflowfm/polyfile/serializer.py def write_polyfile ( path : Path , data : Sequence [ PolyObject ], config : SerializerConfig ) -> None : \"\"\"Write the data to a new file at path Args: path (Path): The path to write the data to data (Sequence[PolyObject]): The poly objects to write config (SerializerConfig): The serialization configuration. \"\"\" serialized_poly_objects = [ Serializer . serialize_poly_object ( poly_object , config ) for poly_object in data ] serialized_data = chain . from_iterable ( serialized_poly_objects ) path . parent . mkdir ( parents = True , exist_ok = True ) with path . open ( \"w\" , encoding = \"utf8\" ) as f : for line in serialized_data : f . write ( line ) f . write ( \" \\n \" )","title":"Polyline/polygon files"},{"location":"reference/polyfile/#polylinepolygon-files","text":"Polyline .pli(z) and polygon .pol files are basic spatial input files for a D-Flow FM model to select particular locations, and are used in various other input files. They are represented by the classes below.","title":"Polyline/polygon files"},{"location":"reference/polyfile/#model","text":"models.py defines all classes and functions related to representing pol/pli(z) files.","title":"Model"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.models.Description","text":"Description of a single PolyObject. The Description will be prepended to a block. Each line will start with a '*'. Attributes: Name Type Description content str The content of this Description.","title":"Description"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.models.Metadata","text":"Metadata of a single PolyObject. Attributes: Name Type Description name str The name of the PolyObject n_rows int The number of rows (i.e. Point instances) of the PolyObject n_columns int The total number of values in a Point, including x, y, and z.","title":"Metadata"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.models.Point","text":"Point consisting of a x and y coordinate, an optional z coordinate and data. Attributes: Name Type Description x float The x-coordinate of this Point y float The y-coordinate of this Point z Optional[float] An optional z-coordinate of this Point. data Sequence[float] The additional data variables of this Point.","title":"Point"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.models.PolyFile","text":"Poly-file (.pol/.pli/.pliz) representation.","title":"PolyFile"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.models.PolyObject","text":"PolyObject describing a single block in a poly file. The metadata should be consistent with the points: - The number of points should be equal to number of rows defined in the metadata - The data of each point should be equal to the number of columns defined in the metadata. Attributes: Name Type Description description Optional[Description] An optional description of this PolyObject metadata Metadata The Metadata of this PolObject, describing the structure points List[Point] The points describing this PolyObject, structured according to the Metadata","title":"PolyObject"},{"location":"reference/polyfile/#parser","text":"parser.py defines all classes and functions related to parsing pol/pli(z) files.","title":"Parser"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.Block","text":"Block is a temporary object which will be converted into a PolyObject. The fields are supposed to be set during the lifetime of this object. When all fields are set, finalize can be called. Attributes: Name Type Description start_line int The starting line of this current block. name Optional[str] The name of this block. Defaults to None. dimensions Optional[Tuple[int, int]] The dimensions (n_rows, n_columns) of this Block. Defaults to None. points Optional[List[Point]] The points of this block. Defaults to None. ws_warnings List[ParseMsg] The whitespace warnings associated with this block. Defaults to an empty list. empty_lines List[int] The line numbers of the empty lines. Defaults to an empty list.","title":"Block"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.Block.finalize","text":"Finalise this Block and return the constructed PolyObject and warnings If the metadata or the points are None, then None is returned. Returns: Type Description Optional[Tuple[PolyObject, List[ParseMsg]]] The constructed PolyObject and warnings encountered while parsing it. Source code in hydrolib/core/dflowfm/polyfile/parser.py def finalize ( self ) -> Optional [ Tuple [ PolyObject , List [ ParseMsg ]]]: \"\"\"Finalise this Block and return the constructed PolyObject and warnings If the metadata or the points are None, then None is returned. Returns: Optional[Tuple[PolyObject, List[ParseMsg]]]: The constructed PolyObject and warnings encountered while parsing it. \"\"\" metadata = self . _get_metadata () if metadata is None or self . points is None : return None obj = PolyObject ( description = self . _get_description (), metadata = metadata , points = self . points ) return obj , self . ws_warnings + self . _get_empty_line_warnings ()","title":"finalize()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.ErrorBuilder","text":"ErrorBuilder provides the functionality to the Parser to keep track of errors.","title":"ErrorBuilder"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.ErrorBuilder.__init__","text":"Create a new ErorrorBuilder Source code in hydrolib/core/dflowfm/polyfile/parser.py def __init__ ( self ) -> None : \"\"\"Create a new ErorrorBuilder\"\"\" self . _current_block : Optional [ InvalidBlock ] = None","title":"__init__()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.ErrorBuilder.end_invalid_block","text":"Store the end line of the current block If no invalid block currently exists, nothing will be done. Parameters: Name Type Description Default line int the final line of this invalid block required Source code in hydrolib/core/dflowfm/polyfile/parser.py def end_invalid_block ( self , line : int ) -> None : \"\"\"Store the end line of the current block If no invalid block currently exists, nothing will be done. Args: line (int): the final line of this invalid block \"\"\" if self . _current_block is not None : self . _current_block . end_line = line","title":"end_invalid_block()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.ErrorBuilder.finalize_previous_error","text":"Finalize the current invalid block if it exists If no current invalid block exists, None will be returned, and nothing will change. If a current block exists, it will be converted into a ParseMsg and returned. The current invalid block will be reset. Returns: Type Description Optional[ParseMsg] The corresponding ParseMsg if an InvalidBlock exists. Source code in hydrolib/core/dflowfm/polyfile/parser.py def finalize_previous_error ( self ) -> Optional [ ParseMsg ]: \"\"\"Finalize the current invalid block if it exists If no current invalid block exists, None will be returned, and nothing will change. If a current block exists, it will be converted into a ParseMsg and returned. The current invalid block will be reset. Returns: Optional[ParseMsg]: The corresponding ParseMsg if an InvalidBlock exists. \"\"\" if self . _current_block is not None : msg = self . _current_block . to_msg () self . _current_block = None return msg else : return None","title":"finalize_previous_error()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.ErrorBuilder.start_invalid_block","text":"Start a new invalid block if none exists at the moment If we are already in an invalid block, or the previous one was never finalised, we will not log the reason, and assume it is one long invalid block. Parameters: Name Type Description Default block_start int The start of the invalid block. required invalid_line int The actual offending line number. required reason str The reason why this block is invalid. required Source code in hydrolib/core/dflowfm/polyfile/parser.py def start_invalid_block ( self , block_start : int , invalid_line : int , reason : str ) -> None : \"\"\"Start a new invalid block if none exists at the moment If we are already in an invalid block, or the previous one was never finalised, we will not log the reason, and assume it is one long invalid block. Args: block_start (int): The start of the invalid block. invalid_line (int): The actual offending line number. reason (str): The reason why this block is invalid. \"\"\" if self . _current_block is None : self . _current_block = InvalidBlock ( start_line = block_start , invalid_line = invalid_line , reason = reason )","title":"start_invalid_block()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.InvalidBlock","text":"InvalidBlock is a temporary object which will be converted into a ParseMsg. Attributes: Name Type Description start_line int The start line of this InvalidBlock end_line Optional[int] The end line of this InvalidBlock if it is set. Defaults to None. invalid_line int The line which is causing this block to be invalid. reason str A human-readable string detailing the reason of the ParseMsg.","title":"InvalidBlock"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.InvalidBlock.to_msg","text":"Convert this InvalidBlock to the corresponding ParseMsg Returns: Type Description ParseMsg The ParseMsg corresponding with this InvalidBlock Source code in hydrolib/core/dflowfm/polyfile/parser.py def to_msg ( self ) -> ParseMsg : \"\"\"Convert this InvalidBlock to the corresponding ParseMsg Returns: ParseMsg: The ParseMsg corresponding with this InvalidBlock \"\"\" return ParseMsg ( line_start = self . start_line , line_end = self . end_line , reason = f \" { self . reason } at line { self . invalid_line } .\" , )","title":"to_msg()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.ParseMsg","text":"ParseMsg defines a single message indicating a significant parse event. Attributes: Name Type Description line_start int The start line of the block to which this ParseMsg refers. line_end int The end line of the block to which this ParseMsg refers. column Optional[Tuple[int, int]] An optional begin and end column to which this ParseMsg refers. reason str A human-readable string detailing the reason of the ParseMsg.","title":"ParseMsg"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.ParseMsg.format_parsemsg_to_string","text":"Format string describing this ParseMsg Parameters: Name Type Description Default file_path Optional[Path] The file path mentioned in the message if specified. Defaults to None. None Source code in hydrolib/core/dflowfm/polyfile/parser.py def format_parsemsg_to_string ( self , file_path : Optional [ Path ] = None ) -> str : \"\"\"Format string describing this ParseMsg Args: file_path (Optional[Path], optional): The file path mentioned in the message if specified. Defaults to None. \"\"\" if self . line_start != self . line_end : block_suffix = f \" \\n Invalid block { self . line_start } : { self . line_end } \" else : block_suffix = f \" \\n Invalid line { self . line_start } \" col_suffix = ( f \" \\n Columns { self . column [ 0 ] } : { self . column [ 1 ] } \" if self . column is not None else \"\" ) file_suffix = f \" \\n File: { file_path } \" if file_path is not None else \"\" message = f \" { self . reason }{ block_suffix }{ col_suffix }{ file_suffix } \" return message","title":"format_parsemsg_to_string()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.Parser","text":"Parser provides the functionality to parse a polyfile line by line. The Parser parses blocks describing PolyObject instances by relying on a rudimentary state machine. The states are encoded with the StateType. New lines are fed through the feed_line method. After each line the internal state will be updated. When a complete block is read, it will be converted into a PolyObject and stored internally. When finalise is called, the constructed objects, as well as any warnings and errors describing invalid blocks, will be returned. Each state defines a feed_line method, stored in the _feed_line dict, which consumes a line and potentially transitions the state into the next. Each state further defines a finalise method, stored in the _finalise dict, which is called upon finalising the parser. Invalid states are encoded with INVALID_STATE. In this state the Parser attempts to find a new block, and thus looks for a new description or name. Unexpected whitespace before comments, names, and dimensions, as well as empty lines will generate a warning, and will be ignored by the parser.","title":"Parser"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.Parser.__init__","text":"Create a new Parser Parameters: Name Type Description Default file_path Path Name of the file being parsed, only used for providing proper warnings. required has_z_value bool Whether to interpret the third column as z-coordinates. Defaults to False. False Source code in hydrolib/core/dflowfm/polyfile/parser.py def __init__ ( self , file_path : Path , has_z_value : bool = False ) -> None : \"\"\"Create a new Parser Args: file_path (Path): Name of the file being parsed, only used for providing proper warnings. has_z_value (bool, optional): Whether to interpret the third column as z-coordinates. Defaults to False. \"\"\" self . _has_z_value = has_z_value self . _file_path = file_path self . _line = 0 self . _new_block () self . _error_builder = ErrorBuilder () self . _poly_objects : List [ PolyObject ] = [] self . _current_point : int = 0 self . _feed_line : Dict [ StateType , Callable [[ str ], None ]] = { StateType . NEW_BLOCK : self . _parse_name_or_new_description , StateType . PARSED_DESCRIPTION : self . _parse_name_or_next_description , StateType . PARSED_NAME : self . _parse_dimensions , StateType . PARSING_POINTS : self . _parse_next_point , StateType . INVALID_STATE : self . _parse_name_or_new_description , } self . _finalise : Dict [ StateType , Callable [[], None ]] = { StateType . NEW_BLOCK : self . _noop , StateType . PARSED_DESCRIPTION : self . _add_current_block_as_incomplete_error , StateType . PARSED_NAME : self . _add_current_block_as_incomplete_error , StateType . PARSING_POINTS : self . _add_current_block_as_incomplete_error , StateType . INVALID_STATE : self . _noop , }","title":"__init__()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.Parser.feed_line","text":"Parse the next line with this Parser. Parameters: Name Type Description Default line str The line to parse required Source code in hydrolib/core/dflowfm/polyfile/parser.py def feed_line ( self , line : str ) -> None : \"\"\"Parse the next line with this Parser. Args: line (str): The line to parse \"\"\" if not Parser . _is_empty_line ( line ): self . _feed_line [ self . _state ]( line ) else : self . _handle_empty_line () self . _increment_line ()","title":"feed_line()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.Parser.finalize","text":"Finalize parsing and return the constructed PolyObject. Exceptions: Type Description ValueError When the plifile is invalid. Returns: Type Description PolyObject A PolyObject containing the constructed PolyObject instances. Source code in hydrolib/core/dflowfm/polyfile/parser.py def finalize ( self ) -> Sequence [ PolyObject ]: \"\"\"Finalize parsing and return the constructed PolyObject. Raises: ValueError: When the plifile is invalid. Returns: PolyObject: A PolyObject containing the constructed PolyObject instances. \"\"\" self . _error_builder . end_invalid_block ( self . _line ) last_error_msg = self . _error_builder . finalize_previous_error () if last_error_msg is not None : self . _notify_as_error ( last_error_msg ) self . _finalise [ self . _state ]() return self . _poly_objects","title":"finalize()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.StateType","text":"The types of state of a Parser.","title":"StateType"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.read_polyfile","text":"Read the specified file and return the corresponding data. The file is expected to follow the .pli(z) / .pol convention. A .pli(z) or .pol file is defined as consisting of a number of blocks of lines adhering to the following format: Optional description record consisting of one or more lines starting with '*'. These will be ignored. Name consisting of a non-blank character string Two integers, Nr and Nc, representing the numbers of rows and columns respectively Nr number of data points, consisting of Nc floats separated by whitespace For example: ... * * Polyline L008 * L008 4 2 131595.0 549685.0 131750.0 549865.0 131595.0 550025.0 131415.0 550175.0 ... Note that the points can be arbitrarily indented, and the comments are optional. if no has_z_value has been defined, it will be based on the file path extensions of the filepath: - .pliz will default to True - .pli and .pol will default to False Empty lines and unexpected whitespace will be flagged as warnings, and ignored. If invalid syntax is detected within a block, an error will be created. This block will be ignored for the purpose of creating PolyObject instances. Once an error is encountered, any following lines will be marked as part of the invalid block, until a new valid block is found. Note that this means that sequential invalid blocks will be reported as a single invalid block. Such invalid blocks will be reported as warnings. Parameters: Name Type Description Default filepath Path Path to the pli(z)/pol convention structured file. required has_z_values Optional[bool] Whether to create points containing a z-value. Defaults to None. None Exceptions: Type Description ValueError When the plifile is invalid. Returns: Type Description Dict The dictionary describing the data of a PolyObject. Source code in hydrolib/core/dflowfm/polyfile/parser.py def read_polyfile ( filepath : Path , has_z_values : Optional [ bool ] = None ) -> Dict : \"\"\"Read the specified file and return the corresponding data. The file is expected to follow the .pli(z) / .pol convention. A .pli(z) or .pol file is defined as consisting of a number of blocks of lines adhering to the following format: - Optional description record consisting of one or more lines starting with '*'. These will be ignored. - Name consisting of a non-blank character string - Two integers, Nr and Nc, representing the numbers of rows and columns respectively - Nr number of data points, consisting of Nc floats separated by whitespace For example: ``` ... * * Polyline L008 * L008 4 2 131595.0 549685.0 131750.0 549865.0 131595.0 550025.0 131415.0 550175.0 ... ``` Note that the points can be arbitrarily indented, and the comments are optional. if no has_z_value has been defined, it will be based on the file path extensions of the filepath: - .pliz will default to True - .pli and .pol will default to False Empty lines and unexpected whitespace will be flagged as warnings, and ignored. If invalid syntax is detected within a block, an error will be created. This block will be ignored for the purpose of creating PolyObject instances. Once an error is encountered, any following lines will be marked as part of the invalid block, until a new valid block is found. Note that this means that sequential invalid blocks will be reported as a single invalid block. Such invalid blocks will be reported as warnings. Args: filepath: Path to the pli(z)/pol convention structured file. has_z_values: Whether to create points containing a z-value. Defaults to None. Raises: ValueError: When the plifile is invalid. Returns: Dict: The dictionary describing the data of a PolyObject. \"\"\" if has_z_values is None : has_z_values = _determine_has_z_value ( filepath ) parser = Parser ( filepath , has_z_value = has_z_values ) with filepath . open ( \"r\" , encoding = \"utf8\" ) as f : for line in f : parser . feed_line ( line ) objs = parser . finalize () return { \"has_z_values\" : has_z_values , \"objects\" : objs }","title":"read_polyfile()"},{"location":"reference/polyfile/#serializer","text":"","title":"Serializer"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.serializer.Serializer","text":"Serializer provides several static serialize methods for the models.","title":"Serializer"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.serializer.Serializer.serialize_description","text":"Serialize the Description to a string which can be used within a polyfile. Returns: Type Description str The serialised equivalent of this Description Source code in hydrolib/core/dflowfm/polyfile/serializer.py @staticmethod def serialize_description ( description : Optional [ Description ]) -> Iterable [ str ]: \"\"\"Serialize the Description to a string which can be used within a polyfile. Returns: str: The serialised equivalent of this Description \"\"\" if description is None : return [] if description . content == \"\" : return [ \"*\" , ] return ( f \"* { v . rstrip () } \" for v in ( description . content + \" \\n \" ) . splitlines ())","title":"serialize_description()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.serializer.Serializer.serialize_metadata","text":"Serialize this Metadata to a string which can be used within a polyfile. The number of rows and number of columns are separated by four spaces. Returns: Type Description str The serialised equivalent of this Metadata Source code in hydrolib/core/dflowfm/polyfile/serializer.py @staticmethod def serialize_metadata ( metadata : Metadata ) -> Iterable [ str ]: \"\"\"Serialize this Metadata to a string which can be used within a polyfile. The number of rows and number of columns are separated by four spaces. Returns: str: The serialised equivalent of this Metadata \"\"\" return [ metadata . name , f \" { metadata . n_rows } { metadata . n_columns } \" ]","title":"serialize_metadata()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.serializer.Serializer.serialize_point","text":"Serialize this Point to a string which can be used within a polyfile. the point data is indented with 4 spaces, and the individual values are separated by 4 spaces as well. Parameters: Name Type Description Default point Point The point to serialize. required config SerializerConfig The serialization configuration. required Returns: Type Description str The serialised equivalent of this Point Source code in hydrolib/core/dflowfm/polyfile/serializer.py @staticmethod def serialize_point ( point : Point , config : SerializerConfig ) -> str : \"\"\"Serialize this Point to a string which can be used within a polyfile. the point data is indented with 4 spaces, and the individual values are separated by 4 spaces as well. Args: point (Point): The point to serialize. config (SerializerConfig): The serialization configuration. Returns: str: The serialised equivalent of this Point \"\"\" space = 4 * \" \" float_format = lambda v : f \" { v :{ config . float_format }} \" return space + space . join ( float_format ( v ) for v in Serializer . _get_point_values ( point ) )","title":"serialize_point()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.serializer.Serializer.serialize_poly_object","text":"Serialize this PolyObject to a string which can be used within a polyfile. Parameters: Name Type Description Default obj PolyObject The poly object to serializer. required config SerializerConfig The serialization configuration. required Returns: Type Description str The serialised equivalent of this PolyObject Source code in hydrolib/core/dflowfm/polyfile/serializer.py @staticmethod def serialize_poly_object ( obj : PolyObject , config : SerializerConfig ) -> Iterable [ str ]: \"\"\"Serialize this PolyObject to a string which can be used within a polyfile. Args: obj (PolyObject): The poly object to serializer. config (SerializerConfig): The serialization configuration. Returns: str: The serialised equivalent of this PolyObject \"\"\" description = Serializer . serialize_description ( obj . description ) metadata = Serializer . serialize_metadata ( obj . metadata ) points = [ Serializer . serialize_point ( obj , config ) for obj in obj . points ] return chain ( description , metadata , points )","title":"serialize_poly_object()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.serializer.write_polyfile","text":"Write the data to a new file at path Parameters: Name Type Description Default path Path The path to write the data to required data Sequence[PolyObject] The poly objects to write required config SerializerConfig The serialization configuration. required Source code in hydrolib/core/dflowfm/polyfile/serializer.py def write_polyfile ( path : Path , data : Sequence [ PolyObject ], config : SerializerConfig ) -> None : \"\"\"Write the data to a new file at path Args: path (Path): The path to write the data to data (Sequence[PolyObject]): The poly objects to write config (SerializerConfig): The serialization configuration. \"\"\" serialized_poly_objects = [ Serializer . serialize_poly_object ( poly_object , config ) for poly_object in data ] serialized_data = chain . from_iterable ( serialized_poly_objects ) path . parent . mkdir ( parents = True , exist_ok = True ) with path . open ( \"w\" , encoding = \"utf8\" ) as f : for line in serialized_data : f . write ( line ) f . write ( \" \\n \" )","title":"write_polyfile()"},{"location":"reference/storagenode/","text":"Storage node .ini files \u00b6 The storage node module provides the specific logic for accessing storage node files for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. A storage node .ini file is described by the classes below. Model \u00b6 Interpolation ( str , Enum ) \u00b6 Enum class containing the valid values for the interpolation type as used for a storage area table in StorageNode. NodeType ( str , Enum ) \u00b6 Enum class containing the valid values for the node type as used in StorageNode. StorageNode ( INIBasedModel ) pydantic-model \u00b6 A storage node that is included in the storage node file. All lowercased attributes match with the storage node input as described in UM Sec.C.17 . check_list_length_levels ( values ) classmethod \u00b6 Validates that the length of the levels field is as expected. Source code in hydrolib/core/dflowfm/storagenode/models.py @root_validator ( allow_reuse = True ) def check_list_length_levels ( cls , values ): \"\"\"Validates that the length of the levels field is as expected.\"\"\" return validate_correct_length ( values , \"levels\" , \"storagearea\" , length_name = \"numlevels\" , list_required_with_length = True , ) validate_that_required_fields_are_present_when_not_using_tables ( values : Dict ) -> Dict classmethod \u00b6 Validates that the specified fields are present. Source code in hydrolib/core/dflowfm/storagenode/models.py @root_validator ( allow_reuse = True ) def validate_that_required_fields_are_present_when_not_using_tables ( cls , values : Dict ) -> Dict : \"\"\"Validates that the specified fields are present.\"\"\" return validate_required_fields ( values , \"bedlevel\" , \"area\" , \"streetlevel\" , conditional_field_name = \"usetable\" , conditional_value = False , ) validate_that_required_fields_are_present_when_using_tables ( values : Dict ) -> Dict classmethod \u00b6 Validates that the specified fields are present when the usetable field is also present. Source code in hydrolib/core/dflowfm/storagenode/models.py @root_validator ( allow_reuse = True ) def validate_that_required_fields_are_present_when_using_tables ( cls , values : Dict ) -> Dict : \"\"\"Validates that the specified fields are present when the usetable field is also present.\"\"\" return validate_required_fields ( values , \"numlevels\" , \"levels\" , \"storagearea\" , conditional_field_name = \"usetable\" , conditional_value = True , ) StorageNodeGeneral ( INIGeneral ) pydantic-model \u00b6 The storage node file's [General] section with file meta data. StorageNodeModel ( INIModel ) pydantic-model \u00b6 The overall storage node model that contains the contents of one storage node file. This model is typically referenced under a FMModel .geometry.storagenodefile[..] . Attributes: Name Type Description general StorageNodeGeneral [General] block with file metadata. storagenode List[StorageNode] List of [StorageNode] blocks for all storage nodes. StorageType ( str , Enum ) \u00b6 Enum class containing the valid values for the storage type as used in StorageNode.","title":"Storage node .ini files"},{"location":"reference/storagenode/#storage-node-ini-files","text":"The storage node module provides the specific logic for accessing storage node files for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. A storage node .ini file is described by the classes below.","title":"Storage node .ini files"},{"location":"reference/storagenode/#model","text":"","title":"Model"},{"location":"reference/storagenode/#hydrolib.core.dflowfm.storagenode.models.Interpolation","text":"Enum class containing the valid values for the interpolation type as used for a storage area table in StorageNode.","title":"Interpolation"},{"location":"reference/storagenode/#hydrolib.core.dflowfm.storagenode.models.NodeType","text":"Enum class containing the valid values for the node type as used in StorageNode.","title":"NodeType"},{"location":"reference/storagenode/#hydrolib.core.dflowfm.storagenode.models.StorageNode","text":"A storage node that is included in the storage node file. All lowercased attributes match with the storage node input as described in UM Sec.C.17 .","title":"StorageNode"},{"location":"reference/storagenode/#hydrolib.core.dflowfm.storagenode.models.StorageNode.check_list_length_levels","text":"Validates that the length of the levels field is as expected. Source code in hydrolib/core/dflowfm/storagenode/models.py @root_validator ( allow_reuse = True ) def check_list_length_levels ( cls , values ): \"\"\"Validates that the length of the levels field is as expected.\"\"\" return validate_correct_length ( values , \"levels\" , \"storagearea\" , length_name = \"numlevels\" , list_required_with_length = True , )","title":"check_list_length_levels()"},{"location":"reference/storagenode/#hydrolib.core.dflowfm.storagenode.models.StorageNode.validate_that_required_fields_are_present_when_not_using_tables","text":"Validates that the specified fields are present. Source code in hydrolib/core/dflowfm/storagenode/models.py @root_validator ( allow_reuse = True ) def validate_that_required_fields_are_present_when_not_using_tables ( cls , values : Dict ) -> Dict : \"\"\"Validates that the specified fields are present.\"\"\" return validate_required_fields ( values , \"bedlevel\" , \"area\" , \"streetlevel\" , conditional_field_name = \"usetable\" , conditional_value = False , )","title":"validate_that_required_fields_are_present_when_not_using_tables()"},{"location":"reference/storagenode/#hydrolib.core.dflowfm.storagenode.models.StorageNode.validate_that_required_fields_are_present_when_using_tables","text":"Validates that the specified fields are present when the usetable field is also present. Source code in hydrolib/core/dflowfm/storagenode/models.py @root_validator ( allow_reuse = True ) def validate_that_required_fields_are_present_when_using_tables ( cls , values : Dict ) -> Dict : \"\"\"Validates that the specified fields are present when the usetable field is also present.\"\"\" return validate_required_fields ( values , \"numlevels\" , \"levels\" , \"storagearea\" , conditional_field_name = \"usetable\" , conditional_value = True , )","title":"validate_that_required_fields_are_present_when_using_tables()"},{"location":"reference/storagenode/#hydrolib.core.dflowfm.storagenode.models.StorageNodeGeneral","text":"The storage node file's [General] section with file meta data.","title":"StorageNodeGeneral"},{"location":"reference/storagenode/#hydrolib.core.dflowfm.storagenode.models.StorageNodeModel","text":"The overall storage node model that contains the contents of one storage node file. This model is typically referenced under a FMModel .geometry.storagenodefile[..] . Attributes: Name Type Description general StorageNodeGeneral [General] block with file metadata. storagenode List[StorageNode] List of [StorageNode] blocks for all storage nodes.","title":"StorageNodeModel"},{"location":"reference/storagenode/#hydrolib.core.dflowfm.storagenode.models.StorageType","text":"Enum class containing the valid values for the storage type as used in StorageNode.","title":"StorageType"},{"location":"reference/structure/","text":"Structure .ini files \u00b6 Structure .ini files contain the definition of hydraulic structures for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. A structures.ini file is described by the classes below. Models \u00b6 structure namespace for storing the contents of an FMModel 's structure file. Bridge ( Structure ) pydantic-model \u00b6 Hydraulic structure with type=bridge , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the bridge input as described in UM Sec.C.12.5 . Compound ( Structure ) pydantic-model \u00b6 Hydraulic structure with type=compound , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the compound input as described in UM Sec.C.12.11 . Culvert ( Structure ) pydantic-model \u00b6 Hydraulic structure with type=culvert , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the culvert input as described in UM Sec.C.12.3 . check_list_lengths ( values ) classmethod \u00b6 Validates that the length of the relopening and losscoeff fields are as expected. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def check_list_lengths ( cls , values ): \"\"\"Validates that the length of the relopening and losscoeff fields are as expected.\"\"\" return validate_correct_length ( values , \"relopening\" , \"losscoeff\" , length_name = \"numlosscoeff\" , list_required_with_length = True , ) validate_that_bendlosscoeff_field_is_present_for_invertedsyphons ( values : Dict ) -> Dict classmethod \u00b6 Validates that the bendlosscoeff value is present when dealing with inverted syphons. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def validate_that_bendlosscoeff_field_is_present_for_invertedsyphons ( cls , values : Dict ) -> Dict : \"\"\"Validates that the bendlosscoeff value is present when dealing with inverted syphons.\"\"\" return validate_required_fields ( values , \"bendlosscoeff\" , conditional_field_name = \"subtype\" , conditional_value = CulvertSubType . invertedSiphon , ) validate_that_bendlosscoeff_is_not_provided_for_culverts ( values : Dict ) -> Dict classmethod \u00b6 Validates that the bendlosscoeff field is not provided when the subtype is a culvert. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def validate_that_bendlosscoeff_is_not_provided_for_culverts ( cls , values : Dict ) -> Dict : \"\"\"Validates that the bendlosscoeff field is not provided when the subtype is a culvert.\"\"\" return validate_forbidden_fields ( values , \"bendlosscoeff\" , conditional_field_name = \"subtype\" , conditional_value = CulvertSubType . culvert , ) validate_that_valve_related_fields_are_present_for_culverts_with_valves ( values : Dict ) -> Dict classmethod \u00b6 Validates that valve-related fields are present when there is a valve present. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def validate_that_valve_related_fields_are_present_for_culverts_with_valves ( cls , values : Dict ) -> Dict : \"\"\"Validates that valve-related fields are present when there is a valve present.\"\"\" return validate_required_fields ( values , \"valveopeningheight\" , \"numlosscoeff\" , \"relopening\" , \"losscoeff\" , conditional_field_name = \"valveonoff\" , conditional_value = True , ) CulvertSubType ( str , Enum ) \u00b6 Enum class to store a Culvert 's subType. Dambreak ( Structure ) pydantic-model \u00b6 Hydraulic structure with type=dambreak , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the dambreak input as described in UM Sec.C.12.10 . check_location_dambreak ( values : dict ) -> dict classmethod \u00b6 Verifies whether the location for this structure contains valid values for numCoordinates, xCoordinates and yCoordinates or instead is using a polyline file. Verifies whether de water level location specifications are valid. Parameters: Name Type Description Default values dict Dictionary of validated values to create a Dambreak. required Exceptions: Type Description ValueError When the values dictionary does not contain valid coordinates or polyline file or when the water level location specifications are not valid. Returns: Type Description dict Dictionary of validated values. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator @classmethod def check_location_dambreak ( cls , values : dict ) -> dict : \"\"\" Verifies whether the location for this structure contains valid values for numCoordinates, xCoordinates and yCoordinates or instead is using a polyline file. Verifies whether de water level location specifications are valid. Args: values (dict): Dictionary of validated values to create a Dambreak. Raises: ValueError: When the values dictionary does not contain valid coordinates or polyline file or when the water level location specifications are not valid. Returns: dict: Dictionary of validated values. \"\"\" def _validate_waterlevel_location ( x_key : str , y_key : str , node_key : str ): x_is_given = values . get ( x_key . lower ()) is not None y_is_given = values . get ( y_key . lower ()) is not None node_is_given = values . get ( node_key . lower ()) is not None if ( x_is_given and y_is_given and not node_is_given ) or ( node_is_given and not x_is_given and not y_is_given ): return raise ValueError ( f \"Either ` { node_key } ` should be specified or ` { x_key } ` and ` { y_key } `.\" ) _validate_waterlevel_location ( \"waterLevelUpstreamLocationX\" , \"waterLevelUpstreamLocationY\" , \"waterLevelUpstreamNodeId\" , ) _validate_waterlevel_location ( \"waterLevelDownstreamLocationX\" , \"waterLevelDownstreamLocationY\" , \"waterLevelDownstreamNodeId\" , ) return values validate_algorithm ( value : str ) -> DambreakAlgorithm classmethod \u00b6 Validates the algorithm parameter for the dambreak structure. Parameters: Name Type Description Default value int algorithm value read from the user's input. required Exceptions: Type Description ValueError When the value given is not of type int. ValueError When the value given is not in the range [1,3] Returns: Type Description int Validated value. Source code in hydrolib/core/dflowfm/structure/models.py @validator ( \"algorithm\" , pre = True ) @classmethod def validate_algorithm ( cls , value : str ) -> DambreakAlgorithm : \"\"\" Validates the algorithm parameter for the dambreak structure. Args: value (int): algorithm value read from the user's input. Raises: ValueError: When the value given is not of type int. ValueError: When the value given is not in the range [1,3] Returns: int: Validated value. \"\"\" int_value = - 1 try : int_value = int ( value ) except Exception : raise ValueError ( \"Dambreak algorithm value should be of type int.\" ) if 0 < int_value <= 3 : return DambreakAlgorithm ( int_value ) raise ValueError ( \"Dambreak algorithm value should be 1, 2 or 3.\" ) validate_dambreak_levels_and_widths ( field_value : Union [ hydrolib . core . dflowfm . tim . models . TimModel , hydrolib . core . dflowfm . bc . models . ForcingModel ], values : dict ) -> Union [ hydrolib . core . dflowfm . tim . models . TimModel , hydrolib . core . dflowfm . bc . models . ForcingModel ] classmethod \u00b6 Validates whether a dambreak can be created with the given dambreakLevelsAndWidths property. This property should be given when the algorithm value is 3. Parameters: Name Type Description Default field_value Optional[Union[TimModel, ForcingModel]] Value given for dambreakLevelsAndWidths. required values dict Dictionary of values already validated (assuming algorithm is in it). required Exceptions: Type Description ValueError When algorithm value is not 3 and field_value has a value. Returns: Type Description Optional[Union[TimModel, ForcingModel]] The value given for dambreakLevelsAndwidths. Source code in hydrolib/core/dflowfm/structure/models.py @validator ( \"dambreaklevelsandwidths\" ) @classmethod def validate_dambreak_levels_and_widths ( cls , field_value : Optional [ Union [ TimModel , ForcingModel ]], values : dict ) -> Optional [ Union [ TimModel , ForcingModel ]]: \"\"\" Validates whether a dambreak can be created with the given dambreakLevelsAndWidths property. This property should be given when the algorithm value is 3. Args: field_value (Optional[Union[TimModel, ForcingModel]]): Value given for dambreakLevelsAndWidths. values (dict): Dictionary of values already validated (assuming algorithm is in it). Raises: ValueError: When algorithm value is not 3 and field_value has a value. Returns: Optional[Union[TimModel, ForcingModel]]: The value given for dambreakLevelsAndwidths. \"\"\" # Retrieve the algorithm value (if not found use 0). algorithm_value = values . get ( \"algorithm\" , 0 ) if field_value is not None and algorithm_value != 3 : # dambreakLevelsAndWidths can only be set when algorithm = 3 raise ValueError ( f \"Dambreak field dambreakLevelsAndWidths can only be set when algorithm = 3, current value: { algorithm_value } .\" ) return field_value DambreakAlgorithm ( int , Enum ) \u00b6 An enumeration. FlowDirection ( str , Enum ) \u00b6 Enum class containing the valid values for the allowedFlowDirection attribute in several subclasses of Structure. GateOpeningHorizontalDirection ( str , Enum ) \u00b6 Horizontal opening direction of gate door[s]. GeneralStructure ( Structure ) pydantic-model \u00b6 Hydraulic structure with type=generalStructure , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the orifice input as described in UM Sec.C.12.9 . Orientation ( str , Enum ) \u00b6 Enum class containing the valid values for the orientation attribute in several subclasses of Structure. Orifice ( Structure ) pydantic-model \u00b6 Hydraulic structure with type=orifice , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the orifice input as described in UM Sec.C.12.7 . Pump ( Structure ) pydantic-model \u00b6 Hydraulic structure with type=pump , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the pump input as described in UM Sec.C.12.6 . check_list_lengths_head_and_reductionfactor ( values ) classmethod \u00b6 Validates that the lengths of the head and reductionfactor fields are as expected. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def check_list_lengths_head_and_reductionfactor ( cls , values ): \"\"\"Validates that the lengths of the head and reductionfactor fields are as expected.\"\"\" return validate_correct_length ( values , \"head\" , \"reductionfactor\" , length_name = \"numreductionlevels\" , list_required_with_length = True , ) conditionally_check_list_lengths_deliveryside ( values : Dict ) -> Dict classmethod \u00b6 Validates the length of the delivery side fields, but only if there is a controlside value present in the values and the controlside is not equal to the suctionSide. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def conditionally_check_list_lengths_deliveryside ( cls , values : Dict ) -> Dict : \"\"\" Validates the length of the delivery side fields, but only if there is a controlside value present in the values and the controlside is not equal to the suctionSide. \"\"\" return validate_conditionally ( cls , values , Pump . _check_list_lengths_deliveryside , \"controlside\" , \"suctionSide\" , ne , ) conditionally_check_list_lengths_suctionside ( values : Dict ) -> Dict classmethod \u00b6 Validates the length of the suction side fields, but only if there is a controlside value present in the values and the controlside is not equal to the deliverySide. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def conditionally_check_list_lengths_suctionside ( cls , values : Dict ) -> Dict : \"\"\" Validates the length of the suction side fields, but only if there is a controlside value present in the values and the controlside is not equal to the deliverySide. \"\"\" return validate_conditionally ( cls , values , Pump . _check_list_lengths_suctionside , \"controlside\" , \"deliverySide\" , ne , ) Structure ( INIBasedModel ) pydantic-model \u00b6 check_location ( values : dict ) -> dict classmethod \u00b6 Validates the location of the structure based on the given parameters. For instance, if a branchid is given, then it is expected also the chainage, otherwise numcoordinates xcoordinates and ycoordinates shall be expected. Parameters: Name Type Description Default values dict Dictionary of values validated for the new structure. required Exceptions: Type Description ValueError When branchid or chainage values are not valid (empty strings). ValueError When the number of xcoordinates and ycoordinates do not match numcoordinates. Returns: Type Description dict Dictionary of values validated for the new structure. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator @classmethod def check_location ( cls , values : dict ) -> dict : \"\"\" Validates the location of the structure based on the given parameters. For instance, if a branchid is given, then it is expected also the chainage, otherwise numcoordinates xcoordinates and ycoordinates shall be expected. Args: values (dict): Dictionary of values validated for the new structure. Raises: ValueError: When branchid or chainage values are not valid (empty strings). ValueError: When the number of xcoordinates and ycoordinates do not match numcoordinates. Returns: dict: Dictionary of values validated for the new structure. \"\"\" filtered_values = { k : v for k , v in values . items () if v is not None } structype = filtered_values . get ( \"type\" , \"\" ) . lower () if structype == \"compound\" or issubclass ( cls , ( Compound )): # Compound structure does not require a location specification. return values # Backwards compatibility for old-style polylinefile input field (instead of num/x/yCoordinates): polyline_compatible_structures = dict ( pump = \"Pump\" , dambreak = \"Dambreak\" , gate = \"Gate\" , weir = \"Weir\" , generalstructure = \"GeneralStructure\" , ) polylinefile_in_model = ( structype in polyline_compatible_structures . keys () and filtered_values . get ( \"polylinefile\" ) is not None ) # No branchId+chainage for some structures: only_coordinates_structures = dict ( longculvert = \"LongCulvert\" , dambreak = \"Dambreak\" ) coordinates_in_model = Structure . validate_coordinates_in_model ( filtered_values ) # Error: do not allow both x/y and polyline file: assert not ( polylinefile_in_model and coordinates_in_model ), f \"`Specify location either by `num/x/yCoordinates` or `polylinefile`, but not both.\" # Error: require x/y or polyline file: if ( structype in polyline_compatible_structures . keys () and structype in only_coordinates_structures . keys () ): assert ( coordinates_in_model or polylinefile_in_model ), f \"Specify location either by setting `num/x/yCoordinates` or `polylinefile` fields for a { polyline_compatible_structures [ structype ] } structure.\" # Error: Some structures require coordinates_in_model, but not branchId and chainage. if ( not polylinefile_in_model and structype in only_coordinates_structures . keys () ): assert ( coordinates_in_model ), f \"Specify location by setting `num/x/yCoordinates` for a { only_coordinates_structures [ structype ] } structure.\" # Error: final check: at least one of x/y, branchId+chainage or polyline file must be given branch_and_chainage_in_model = Structure . validate_branch_and_chainage_in_model ( filtered_values ) assert ( branch_and_chainage_in_model or coordinates_in_model or polylinefile_in_model ), \"Specify location either by setting `branchId` and `chainage` or `num/x/yCoordinates` or `polylinefile` fields.\" return values validate ( v ) classmethod \u00b6 Try to initialize subclass based on the type field. This field is compared to each type field of the derived models of Structure . The derived model with an equal structure type will be initialized. Exceptions: Type Description ValueError When the given type is not a known structure type. Source code in hydrolib/core/dflowfm/structure/models.py @classmethod def validate ( cls , v ): \"\"\"Try to initialize subclass based on the `type` field. This field is compared to each `type` field of the derived models of `Structure`. The derived model with an equal structure type will be initialized. Raises: ValueError: When the given type is not a known structure type. \"\"\" # should be replaced by discriminated unions once merged # https://github.com/samuelcolvin/pydantic/pull/2336 if isinstance ( v , dict ): for c in cls . __subclasses__ (): if ( c . __fields__ . get ( \"type\" ) . default . lower () == v . get ( \"type\" , \"\" ) . lower () ): v = c ( ** v ) break else : raise ValueError ( f \"Type of { cls . __name__ } with id= { v . get ( 'id' , '' ) } and type= { v . get ( 'type' , '' ) } is not recognized.\" ) return super () . validate ( v ) validate_branch_and_chainage_in_model ( values : dict ) -> bool staticmethod \u00b6 Static method to validate whether the given branchid and chainage values match the expectation of a new structure. Parameters: Name Type Description Default values dict Dictionary of values to be used to generate a structure. required Exceptions: Type Description ValueError When the value for branchid or chainage are not valid. Returns: Type Description bool Result of valid branchid / chainage in dictionary. Source code in hydrolib/core/dflowfm/structure/models.py @staticmethod def validate_branch_and_chainage_in_model ( values : dict ) -> bool : \"\"\" Static method to validate whether the given branchid and chainage values match the expectation of a new structure. Args: values (dict): Dictionary of values to be used to generate a structure. Raises: ValueError: When the value for branchid or chainage are not valid. Returns: bool: Result of valid branchid / chainage in dictionary. \"\"\" branchid = values . get ( \"branchid\" , None ) if branchid is None : return False chainage = values . get ( \"chainage\" , None ) if str_is_empty_or_none ( branchid ) or chainage is None : raise ValueError ( \"A valid value for branchId and chainage is required when branchId key is specified.\" ) return True validate_coordinates_in_model ( values : dict ) -> bool staticmethod \u00b6 Static method to validate whether the given values match the expectations of a structure to define its coordinates. Parameters: Name Type Description Default values dict Dictionary of values to be used to generate a structure. required Exceptions: Type Description ValueError When the given coordinates is less than 2. ValueError When the given coordinates do not match in expected size. Returns: Type Description bool Result of valid coordinates in dictionary. Source code in hydrolib/core/dflowfm/structure/models.py @staticmethod def validate_coordinates_in_model ( values : dict ) -> bool : \"\"\" Static method to validate whether the given values match the expectations of a structure to define its coordinates. Args: values (dict): Dictionary of values to be used to generate a structure. Raises: ValueError: When the given coordinates is less than 2. ValueError: When the given coordinates do not match in expected size. Returns: bool: Result of valid coordinates in dictionary. \"\"\" searched_keys = [ \"numcoordinates\" , \"xcoordinates\" , \"ycoordinates\" ] if any ( values . get ( k , None ) is None for k in searched_keys ): return False n_coords = values [ \"numcoordinates\" ] if n_coords < 2 : raise ValueError ( f \"Expected at least 2 coordinates, but only { n_coords } declared.\" ) def get_coord_len ( coord : str ) -> int : if values [ coord ] is None : return 0 return len ( values [ coord ]) len_x_coords = get_coord_len ( \"xcoordinates\" ) len_y_coords = get_coord_len ( \"ycoordinates\" ) if n_coords == len_x_coords == len_y_coords : return True raise ValueError ( f \"Expected { n_coords } coordinates, given { len_x_coords } for xCoordinates and { len_y_coords } for yCoordinates.\" ) StructureGeneral ( INIGeneral ) pydantic-model \u00b6 [General] section with structure file metadata. StructureModel ( INIModel ) pydantic-model \u00b6 The overall structure model that contains the contents of one structure file. This model is typically referenced under a FMModel .geometry.structurefile[..] . Attributes: Name Type Description general StructureGeneral [General] block with file metadata. branch List[Structure] List of [Structure] blocks for all hydraulic structures. UniversalWeir ( Structure ) pydantic-model \u00b6 Hydraulic structure with type=universalWeir , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the universal weir input as described in UM Sec.C.12.2 . Weir ( Structure ) pydantic-model \u00b6 Hydraulic structure with type=weir , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the weir input as described in UM Sec.C.12.1 .","title":"Structure .ini files"},{"location":"reference/structure/#structure-ini-files","text":"Structure .ini files contain the definition of hydraulic structures for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. A structures.ini file is described by the classes below.","title":"Structure .ini files"},{"location":"reference/structure/#models","text":"structure namespace for storing the contents of an FMModel 's structure file.","title":"Models"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Bridge","text":"Hydraulic structure with type=bridge , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the bridge input as described in UM Sec.C.12.5 .","title":"Bridge"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Compound","text":"Hydraulic structure with type=compound , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the compound input as described in UM Sec.C.12.11 .","title":"Compound"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Culvert","text":"Hydraulic structure with type=culvert , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the culvert input as described in UM Sec.C.12.3 .","title":"Culvert"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Culvert.check_list_lengths","text":"Validates that the length of the relopening and losscoeff fields are as expected. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def check_list_lengths ( cls , values ): \"\"\"Validates that the length of the relopening and losscoeff fields are as expected.\"\"\" return validate_correct_length ( values , \"relopening\" , \"losscoeff\" , length_name = \"numlosscoeff\" , list_required_with_length = True , )","title":"check_list_lengths()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Culvert.validate_that_bendlosscoeff_field_is_present_for_invertedsyphons","text":"Validates that the bendlosscoeff value is present when dealing with inverted syphons. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def validate_that_bendlosscoeff_field_is_present_for_invertedsyphons ( cls , values : Dict ) -> Dict : \"\"\"Validates that the bendlosscoeff value is present when dealing with inverted syphons.\"\"\" return validate_required_fields ( values , \"bendlosscoeff\" , conditional_field_name = \"subtype\" , conditional_value = CulvertSubType . invertedSiphon , )","title":"validate_that_bendlosscoeff_field_is_present_for_invertedsyphons()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Culvert.validate_that_bendlosscoeff_is_not_provided_for_culverts","text":"Validates that the bendlosscoeff field is not provided when the subtype is a culvert. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def validate_that_bendlosscoeff_is_not_provided_for_culverts ( cls , values : Dict ) -> Dict : \"\"\"Validates that the bendlosscoeff field is not provided when the subtype is a culvert.\"\"\" return validate_forbidden_fields ( values , \"bendlosscoeff\" , conditional_field_name = \"subtype\" , conditional_value = CulvertSubType . culvert , )","title":"validate_that_bendlosscoeff_is_not_provided_for_culverts()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Culvert.validate_that_valve_related_fields_are_present_for_culverts_with_valves","text":"Validates that valve-related fields are present when there is a valve present. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def validate_that_valve_related_fields_are_present_for_culverts_with_valves ( cls , values : Dict ) -> Dict : \"\"\"Validates that valve-related fields are present when there is a valve present.\"\"\" return validate_required_fields ( values , \"valveopeningheight\" , \"numlosscoeff\" , \"relopening\" , \"losscoeff\" , conditional_field_name = \"valveonoff\" , conditional_value = True , )","title":"validate_that_valve_related_fields_are_present_for_culverts_with_valves()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.CulvertSubType","text":"Enum class to store a Culvert 's subType.","title":"CulvertSubType"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Dambreak","text":"Hydraulic structure with type=dambreak , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the dambreak input as described in UM Sec.C.12.10 .","title":"Dambreak"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Dambreak.check_location_dambreak","text":"Verifies whether the location for this structure contains valid values for numCoordinates, xCoordinates and yCoordinates or instead is using a polyline file. Verifies whether de water level location specifications are valid. Parameters: Name Type Description Default values dict Dictionary of validated values to create a Dambreak. required Exceptions: Type Description ValueError When the values dictionary does not contain valid coordinates or polyline file or when the water level location specifications are not valid. Returns: Type Description dict Dictionary of validated values. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator @classmethod def check_location_dambreak ( cls , values : dict ) -> dict : \"\"\" Verifies whether the location for this structure contains valid values for numCoordinates, xCoordinates and yCoordinates or instead is using a polyline file. Verifies whether de water level location specifications are valid. Args: values (dict): Dictionary of validated values to create a Dambreak. Raises: ValueError: When the values dictionary does not contain valid coordinates or polyline file or when the water level location specifications are not valid. Returns: dict: Dictionary of validated values. \"\"\" def _validate_waterlevel_location ( x_key : str , y_key : str , node_key : str ): x_is_given = values . get ( x_key . lower ()) is not None y_is_given = values . get ( y_key . lower ()) is not None node_is_given = values . get ( node_key . lower ()) is not None if ( x_is_given and y_is_given and not node_is_given ) or ( node_is_given and not x_is_given and not y_is_given ): return raise ValueError ( f \"Either ` { node_key } ` should be specified or ` { x_key } ` and ` { y_key } `.\" ) _validate_waterlevel_location ( \"waterLevelUpstreamLocationX\" , \"waterLevelUpstreamLocationY\" , \"waterLevelUpstreamNodeId\" , ) _validate_waterlevel_location ( \"waterLevelDownstreamLocationX\" , \"waterLevelDownstreamLocationY\" , \"waterLevelDownstreamNodeId\" , ) return values","title":"check_location_dambreak()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Dambreak.validate_algorithm","text":"Validates the algorithm parameter for the dambreak structure. Parameters: Name Type Description Default value int algorithm value read from the user's input. required Exceptions: Type Description ValueError When the value given is not of type int. ValueError When the value given is not in the range [1,3] Returns: Type Description int Validated value. Source code in hydrolib/core/dflowfm/structure/models.py @validator ( \"algorithm\" , pre = True ) @classmethod def validate_algorithm ( cls , value : str ) -> DambreakAlgorithm : \"\"\" Validates the algorithm parameter for the dambreak structure. Args: value (int): algorithm value read from the user's input. Raises: ValueError: When the value given is not of type int. ValueError: When the value given is not in the range [1,3] Returns: int: Validated value. \"\"\" int_value = - 1 try : int_value = int ( value ) except Exception : raise ValueError ( \"Dambreak algorithm value should be of type int.\" ) if 0 < int_value <= 3 : return DambreakAlgorithm ( int_value ) raise ValueError ( \"Dambreak algorithm value should be 1, 2 or 3.\" )","title":"validate_algorithm()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Dambreak.validate_dambreak_levels_and_widths","text":"Validates whether a dambreak can be created with the given dambreakLevelsAndWidths property. This property should be given when the algorithm value is 3. Parameters: Name Type Description Default field_value Optional[Union[TimModel, ForcingModel]] Value given for dambreakLevelsAndWidths. required values dict Dictionary of values already validated (assuming algorithm is in it). required Exceptions: Type Description ValueError When algorithm value is not 3 and field_value has a value. Returns: Type Description Optional[Union[TimModel, ForcingModel]] The value given for dambreakLevelsAndwidths. Source code in hydrolib/core/dflowfm/structure/models.py @validator ( \"dambreaklevelsandwidths\" ) @classmethod def validate_dambreak_levels_and_widths ( cls , field_value : Optional [ Union [ TimModel , ForcingModel ]], values : dict ) -> Optional [ Union [ TimModel , ForcingModel ]]: \"\"\" Validates whether a dambreak can be created with the given dambreakLevelsAndWidths property. This property should be given when the algorithm value is 3. Args: field_value (Optional[Union[TimModel, ForcingModel]]): Value given for dambreakLevelsAndWidths. values (dict): Dictionary of values already validated (assuming algorithm is in it). Raises: ValueError: When algorithm value is not 3 and field_value has a value. Returns: Optional[Union[TimModel, ForcingModel]]: The value given for dambreakLevelsAndwidths. \"\"\" # Retrieve the algorithm value (if not found use 0). algorithm_value = values . get ( \"algorithm\" , 0 ) if field_value is not None and algorithm_value != 3 : # dambreakLevelsAndWidths can only be set when algorithm = 3 raise ValueError ( f \"Dambreak field dambreakLevelsAndWidths can only be set when algorithm = 3, current value: { algorithm_value } .\" ) return field_value","title":"validate_dambreak_levels_and_widths()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.DambreakAlgorithm","text":"An enumeration.","title":"DambreakAlgorithm"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.FlowDirection","text":"Enum class containing the valid values for the allowedFlowDirection attribute in several subclasses of Structure.","title":"FlowDirection"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.GateOpeningHorizontalDirection","text":"Horizontal opening direction of gate door[s].","title":"GateOpeningHorizontalDirection"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.GeneralStructure","text":"Hydraulic structure with type=generalStructure , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the orifice input as described in UM Sec.C.12.9 .","title":"GeneralStructure"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Orientation","text":"Enum class containing the valid values for the orientation attribute in several subclasses of Structure.","title":"Orientation"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Orifice","text":"Hydraulic structure with type=orifice , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the orifice input as described in UM Sec.C.12.7 .","title":"Orifice"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Pump","text":"Hydraulic structure with type=pump , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the pump input as described in UM Sec.C.12.6 .","title":"Pump"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Pump.check_list_lengths_head_and_reductionfactor","text":"Validates that the lengths of the head and reductionfactor fields are as expected. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def check_list_lengths_head_and_reductionfactor ( cls , values ): \"\"\"Validates that the lengths of the head and reductionfactor fields are as expected.\"\"\" return validate_correct_length ( values , \"head\" , \"reductionfactor\" , length_name = \"numreductionlevels\" , list_required_with_length = True , )","title":"check_list_lengths_head_and_reductionfactor()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Pump.conditionally_check_list_lengths_deliveryside","text":"Validates the length of the delivery side fields, but only if there is a controlside value present in the values and the controlside is not equal to the suctionSide. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def conditionally_check_list_lengths_deliveryside ( cls , values : Dict ) -> Dict : \"\"\" Validates the length of the delivery side fields, but only if there is a controlside value present in the values and the controlside is not equal to the suctionSide. \"\"\" return validate_conditionally ( cls , values , Pump . _check_list_lengths_deliveryside , \"controlside\" , \"suctionSide\" , ne , )","title":"conditionally_check_list_lengths_deliveryside()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Pump.conditionally_check_list_lengths_suctionside","text":"Validates the length of the suction side fields, but only if there is a controlside value present in the values and the controlside is not equal to the deliverySide. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def conditionally_check_list_lengths_suctionside ( cls , values : Dict ) -> Dict : \"\"\" Validates the length of the suction side fields, but only if there is a controlside value present in the values and the controlside is not equal to the deliverySide. \"\"\" return validate_conditionally ( cls , values , Pump . _check_list_lengths_suctionside , \"controlside\" , \"deliverySide\" , ne , )","title":"conditionally_check_list_lengths_suctionside()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Structure","text":"","title":"Structure"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Structure.check_location","text":"Validates the location of the structure based on the given parameters. For instance, if a branchid is given, then it is expected also the chainage, otherwise numcoordinates xcoordinates and ycoordinates shall be expected. Parameters: Name Type Description Default values dict Dictionary of values validated for the new structure. required Exceptions: Type Description ValueError When branchid or chainage values are not valid (empty strings). ValueError When the number of xcoordinates and ycoordinates do not match numcoordinates. Returns: Type Description dict Dictionary of values validated for the new structure. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator @classmethod def check_location ( cls , values : dict ) -> dict : \"\"\" Validates the location of the structure based on the given parameters. For instance, if a branchid is given, then it is expected also the chainage, otherwise numcoordinates xcoordinates and ycoordinates shall be expected. Args: values (dict): Dictionary of values validated for the new structure. Raises: ValueError: When branchid or chainage values are not valid (empty strings). ValueError: When the number of xcoordinates and ycoordinates do not match numcoordinates. Returns: dict: Dictionary of values validated for the new structure. \"\"\" filtered_values = { k : v for k , v in values . items () if v is not None } structype = filtered_values . get ( \"type\" , \"\" ) . lower () if structype == \"compound\" or issubclass ( cls , ( Compound )): # Compound structure does not require a location specification. return values # Backwards compatibility for old-style polylinefile input field (instead of num/x/yCoordinates): polyline_compatible_structures = dict ( pump = \"Pump\" , dambreak = \"Dambreak\" , gate = \"Gate\" , weir = \"Weir\" , generalstructure = \"GeneralStructure\" , ) polylinefile_in_model = ( structype in polyline_compatible_structures . keys () and filtered_values . get ( \"polylinefile\" ) is not None ) # No branchId+chainage for some structures: only_coordinates_structures = dict ( longculvert = \"LongCulvert\" , dambreak = \"Dambreak\" ) coordinates_in_model = Structure . validate_coordinates_in_model ( filtered_values ) # Error: do not allow both x/y and polyline file: assert not ( polylinefile_in_model and coordinates_in_model ), f \"`Specify location either by `num/x/yCoordinates` or `polylinefile`, but not both.\" # Error: require x/y or polyline file: if ( structype in polyline_compatible_structures . keys () and structype in only_coordinates_structures . keys () ): assert ( coordinates_in_model or polylinefile_in_model ), f \"Specify location either by setting `num/x/yCoordinates` or `polylinefile` fields for a { polyline_compatible_structures [ structype ] } structure.\" # Error: Some structures require coordinates_in_model, but not branchId and chainage. if ( not polylinefile_in_model and structype in only_coordinates_structures . keys () ): assert ( coordinates_in_model ), f \"Specify location by setting `num/x/yCoordinates` for a { only_coordinates_structures [ structype ] } structure.\" # Error: final check: at least one of x/y, branchId+chainage or polyline file must be given branch_and_chainage_in_model = Structure . validate_branch_and_chainage_in_model ( filtered_values ) assert ( branch_and_chainage_in_model or coordinates_in_model or polylinefile_in_model ), \"Specify location either by setting `branchId` and `chainage` or `num/x/yCoordinates` or `polylinefile` fields.\" return values","title":"check_location()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Structure.validate","text":"Try to initialize subclass based on the type field. This field is compared to each type field of the derived models of Structure . The derived model with an equal structure type will be initialized. Exceptions: Type Description ValueError When the given type is not a known structure type. Source code in hydrolib/core/dflowfm/structure/models.py @classmethod def validate ( cls , v ): \"\"\"Try to initialize subclass based on the `type` field. This field is compared to each `type` field of the derived models of `Structure`. The derived model with an equal structure type will be initialized. Raises: ValueError: When the given type is not a known structure type. \"\"\" # should be replaced by discriminated unions once merged # https://github.com/samuelcolvin/pydantic/pull/2336 if isinstance ( v , dict ): for c in cls . __subclasses__ (): if ( c . __fields__ . get ( \"type\" ) . default . lower () == v . get ( \"type\" , \"\" ) . lower () ): v = c ( ** v ) break else : raise ValueError ( f \"Type of { cls . __name__ } with id= { v . get ( 'id' , '' ) } and type= { v . get ( 'type' , '' ) } is not recognized.\" ) return super () . validate ( v )","title":"validate()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Structure.validate_branch_and_chainage_in_model","text":"Static method to validate whether the given branchid and chainage values match the expectation of a new structure. Parameters: Name Type Description Default values dict Dictionary of values to be used to generate a structure. required Exceptions: Type Description ValueError When the value for branchid or chainage are not valid. Returns: Type Description bool Result of valid branchid / chainage in dictionary. Source code in hydrolib/core/dflowfm/structure/models.py @staticmethod def validate_branch_and_chainage_in_model ( values : dict ) -> bool : \"\"\" Static method to validate whether the given branchid and chainage values match the expectation of a new structure. Args: values (dict): Dictionary of values to be used to generate a structure. Raises: ValueError: When the value for branchid or chainage are not valid. Returns: bool: Result of valid branchid / chainage in dictionary. \"\"\" branchid = values . get ( \"branchid\" , None ) if branchid is None : return False chainage = values . get ( \"chainage\" , None ) if str_is_empty_or_none ( branchid ) or chainage is None : raise ValueError ( \"A valid value for branchId and chainage is required when branchId key is specified.\" ) return True","title":"validate_branch_and_chainage_in_model()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Structure.validate_coordinates_in_model","text":"Static method to validate whether the given values match the expectations of a structure to define its coordinates. Parameters: Name Type Description Default values dict Dictionary of values to be used to generate a structure. required Exceptions: Type Description ValueError When the given coordinates is less than 2. ValueError When the given coordinates do not match in expected size. Returns: Type Description bool Result of valid coordinates in dictionary. Source code in hydrolib/core/dflowfm/structure/models.py @staticmethod def validate_coordinates_in_model ( values : dict ) -> bool : \"\"\" Static method to validate whether the given values match the expectations of a structure to define its coordinates. Args: values (dict): Dictionary of values to be used to generate a structure. Raises: ValueError: When the given coordinates is less than 2. ValueError: When the given coordinates do not match in expected size. Returns: bool: Result of valid coordinates in dictionary. \"\"\" searched_keys = [ \"numcoordinates\" , \"xcoordinates\" , \"ycoordinates\" ] if any ( values . get ( k , None ) is None for k in searched_keys ): return False n_coords = values [ \"numcoordinates\" ] if n_coords < 2 : raise ValueError ( f \"Expected at least 2 coordinates, but only { n_coords } declared.\" ) def get_coord_len ( coord : str ) -> int : if values [ coord ] is None : return 0 return len ( values [ coord ]) len_x_coords = get_coord_len ( \"xcoordinates\" ) len_y_coords = get_coord_len ( \"ycoordinates\" ) if n_coords == len_x_coords == len_y_coords : return True raise ValueError ( f \"Expected { n_coords } coordinates, given { len_x_coords } for xCoordinates and { len_y_coords } for yCoordinates.\" )","title":"validate_coordinates_in_model()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.StructureGeneral","text":"[General] section with structure file metadata.","title":"StructureGeneral"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.StructureModel","text":"The overall structure model that contains the contents of one structure file. This model is typically referenced under a FMModel .geometry.structurefile[..] . Attributes: Name Type Description general StructureGeneral [General] block with file metadata. branch List[Structure] List of [Structure] blocks for all hydraulic structures.","title":"StructureModel"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.UniversalWeir","text":"Hydraulic structure with type=universalWeir , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the universal weir input as described in UM Sec.C.12.2 .","title":"UniversalWeir"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Weir","text":"Hydraulic structure with type=weir , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the weir input as described in UM Sec.C.12.1 .","title":"Weir"},{"location":"reference/tim/","text":"Timeseries .tim files \u00b6 .tim files contain time series data of a D-Flow FM model. The support of .tim files for boundary time series will be discontinued. Instead, these will be replaced by the *.bc file . They are represented by the classes below. Model \u00b6 TimModel ( ParsableFileModel ) pydantic-model \u00b6 Class representing a tim (*.tim) file. TimRecord ( BaseModel ) pydantic-model \u00b6 Single tim record, representing a time and a list of data. Parser \u00b6 TimParser \u00b6 A parser for .tim files. Full line comments at the start of the file are supported. Comment lines start with either a * or a # . No other comments are supported. parse ( filepath : Path ) -> Dict [ str , List [ Any ]] staticmethod \u00b6 Parse a .tim file into a dictionary with comments and time series data. Parameters: Name Type Description Default filepath Path Path to the .tim file to be parsed. required Returns: Type Description Dict[str, List[Any]] A dictionary with keys \"comments\" and \"timeseries\". - \"comments\" represents comments found at the start of the file. - \"timeseries\" is a list of dictionaries with the key as \"time\" and values as \"data\". - \"time\" is a time as a string. - \"data\" is data as a list of strings. Exceptions: Type Description ValueError If the file contains a comment that is not at the start of the file. ValueError If the data of the timeseries is empty. Source code in hydrolib/core/dflowfm/tim/parser.py @staticmethod def parse ( filepath : Path ) -> Dict [ str , List [ Any ]]: \"\"\"Parse a .tim file into a dictionary with comments and time series data. Args: filepath (Path): Path to the .tim file to be parsed. Returns: Dict[str, List[Any]]: A dictionary with keys \"comments\" and \"timeseries\". - \"comments\" represents comments found at the start of the file. - \"timeseries\" is a list of dictionaries with the key as \"time\" and values as \"data\". - \"time\" is a time as a string. - \"data\" is data as a list of strings. Raises: ValueError: If the file contains a comment that is not at the start of the file. ValueError: If the data of the timeseries is empty. \"\"\" comments : List [ str ] = [] timeseries : List [ TimData ] = [] with filepath . open ( encoding = \"utf8\" ) as file : lines = file . readlines () comments , start_timeseries_index = TimParser . _read_header_comments ( lines ) timeseries = TimParser . _read_time_series_data ( lines , start_timeseries_index ) return { \"comments\" : comments , \"timeseries\" : timeseries } Serializer \u00b6 TimSerializer \u00b6 serialize ( path : Path , data : Dict [ str , List [ Any ]], config : TimSerializerConfig , save_settings : ModelSaveSettings ) -> None staticmethod \u00b6 Serialize timeseries data to a file in .tim format. Parameters: Name Type Description Default path Path The path to the destination .tim file. required data Dict[str, List[Any]] A dictionary with keys \"comments\" and \"timeseries\". required config TimSerializerConfig The serialization configuration settings. required save_settings ModelSaveSettings The save settings to be used. required Source code in hydrolib/core/dflowfm/tim/serializer.py @staticmethod def serialize ( path : Path , data : Dict [ str , List [ Any ]], config : TimSerializerConfig , save_settings : ModelSaveSettings , ) -> None : \"\"\" Serialize timeseries data to a file in .tim format. Args: path (Path): The path to the destination .tim file. data (Dict[str, List[Any]]): A dictionary with keys \"comments\" and \"timeseries\". - \"comments\" represents comments found at the start of the file. - \"timeseries\" is a list of dictionaries with the key as \"time\" and values as \"data\". - \"time\" is a time as a string. - \"data\" is data as a list of strings. config (TimSerializerConfig): The serialization configuration settings. save_settings (ModelSaveSettings): The save settings to be used. \"\"\" path . parent . mkdir ( parents = True , exist_ok = True ) commentlines = TimSerializer . _serialize_comment_lines ( data ) timeserieslines = TimSerializer . _serialize_timeseries_lines ( data , config ) file_content = TimSerializer . _serialize_file_content ( timeserieslines , commentlines ) with path . open ( \"w\" , encoding = \"utf8\" ) as file : file . write ( file_content ) TimSerializerConfig ( SerializerConfig ) pydantic-model \u00b6 Configuration settings for the TimSerializer.","title":"Timeseries .tim files"},{"location":"reference/tim/#timeseries-tim-files","text":".tim files contain time series data of a D-Flow FM model. The support of .tim files for boundary time series will be discontinued. Instead, these will be replaced by the *.bc file . They are represented by the classes below.","title":"Timeseries .tim files"},{"location":"reference/tim/#model","text":"","title":"Model"},{"location":"reference/tim/#hydrolib.core.dflowfm.tim.models.TimModel","text":"Class representing a tim (*.tim) file.","title":"TimModel"},{"location":"reference/tim/#hydrolib.core.dflowfm.tim.models.TimRecord","text":"Single tim record, representing a time and a list of data.","title":"TimRecord"},{"location":"reference/tim/#parser","text":"","title":"Parser"},{"location":"reference/tim/#hydrolib.core.dflowfm.tim.parser.TimParser","text":"A parser for .tim files. Full line comments at the start of the file are supported. Comment lines start with either a * or a # . No other comments are supported.","title":"TimParser"},{"location":"reference/tim/#hydrolib.core.dflowfm.tim.parser.TimParser.parse","text":"Parse a .tim file into a dictionary with comments and time series data. Parameters: Name Type Description Default filepath Path Path to the .tim file to be parsed. required Returns: Type Description Dict[str, List[Any]] A dictionary with keys \"comments\" and \"timeseries\". - \"comments\" represents comments found at the start of the file. - \"timeseries\" is a list of dictionaries with the key as \"time\" and values as \"data\". - \"time\" is a time as a string. - \"data\" is data as a list of strings. Exceptions: Type Description ValueError If the file contains a comment that is not at the start of the file. ValueError If the data of the timeseries is empty. Source code in hydrolib/core/dflowfm/tim/parser.py @staticmethod def parse ( filepath : Path ) -> Dict [ str , List [ Any ]]: \"\"\"Parse a .tim file into a dictionary with comments and time series data. Args: filepath (Path): Path to the .tim file to be parsed. Returns: Dict[str, List[Any]]: A dictionary with keys \"comments\" and \"timeseries\". - \"comments\" represents comments found at the start of the file. - \"timeseries\" is a list of dictionaries with the key as \"time\" and values as \"data\". - \"time\" is a time as a string. - \"data\" is data as a list of strings. Raises: ValueError: If the file contains a comment that is not at the start of the file. ValueError: If the data of the timeseries is empty. \"\"\" comments : List [ str ] = [] timeseries : List [ TimData ] = [] with filepath . open ( encoding = \"utf8\" ) as file : lines = file . readlines () comments , start_timeseries_index = TimParser . _read_header_comments ( lines ) timeseries = TimParser . _read_time_series_data ( lines , start_timeseries_index ) return { \"comments\" : comments , \"timeseries\" : timeseries }","title":"parse()"},{"location":"reference/tim/#serializer","text":"","title":"Serializer"},{"location":"reference/tim/#hydrolib.core.dflowfm.tim.serializer.TimSerializer","text":"","title":"TimSerializer"},{"location":"reference/tim/#hydrolib.core.dflowfm.tim.serializer.TimSerializer.serialize","text":"Serialize timeseries data to a file in .tim format. Parameters: Name Type Description Default path Path The path to the destination .tim file. required data Dict[str, List[Any]] A dictionary with keys \"comments\" and \"timeseries\". required config TimSerializerConfig The serialization configuration settings. required save_settings ModelSaveSettings The save settings to be used. required Source code in hydrolib/core/dflowfm/tim/serializer.py @staticmethod def serialize ( path : Path , data : Dict [ str , List [ Any ]], config : TimSerializerConfig , save_settings : ModelSaveSettings , ) -> None : \"\"\" Serialize timeseries data to a file in .tim format. Args: path (Path): The path to the destination .tim file. data (Dict[str, List[Any]]): A dictionary with keys \"comments\" and \"timeseries\". - \"comments\" represents comments found at the start of the file. - \"timeseries\" is a list of dictionaries with the key as \"time\" and values as \"data\". - \"time\" is a time as a string. - \"data\" is data as a list of strings. config (TimSerializerConfig): The serialization configuration settings. save_settings (ModelSaveSettings): The save settings to be used. \"\"\" path . parent . mkdir ( parents = True , exist_ok = True ) commentlines = TimSerializer . _serialize_comment_lines ( data ) timeserieslines = TimSerializer . _serialize_timeseries_lines ( data , config ) file_content = TimSerializer . _serialize_file_content ( timeserieslines , commentlines ) with path . open ( \"w\" , encoding = \"utf8\" ) as file : file . write ( file_content )","title":"serialize()"},{"location":"reference/tim/#hydrolib.core.dflowfm.tim.serializer.TimSerializerConfig","text":"Configuration settings for the TimSerializer.","title":"TimSerializerConfig"},{"location":"reference/xyz/","text":"Sample files \u00b6 Sample .xyz files contain spatial input point data for a D-Flow FM model, and are used in various other input files. A sample data file is described by the classes below. Model \u00b6 XYZModel ( ParsableFileModel ) pydantic-model \u00b6 Sample or forcing file. Attributes: Name Type Description points List[hydrolib.core.dflowfm.xyz.models.XYZPoint] List of XYZPoint dict ( self , * args , ** kwargs ) \u00b6 Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dflowfm/xyz/models.py def dict ( self , * args , ** kwargs ): # speed up serializing by not converting these lowest models to dict return dict ( points = self . points ) XYZPoint ( BaseModel ) pydantic-model \u00b6 Single sample or forcing point. Attributes: Name Type Description x float x or \u03bb coordinate y float y or \u03c6 coordinate z float sample value or group number (forcing) comment Optional[str] keyword for grouping (forcing) comment : str pydantic-field \u00b6 comment or group name Parser \u00b6 XYZParser \u00b6 A parser for .xyz files which are like this: number number number number number number # comment Note that the whitespace can vary and the comment left out. parse ( filepath : Path ) -> Dict staticmethod \u00b6 Parse an .xyz file into a Dict with the list of points read. Parameters: Name Type Description Default filepath Path .xyz file to be read. required Returns: Type Description Dict dictionary with \"points\" value set to a list of points each of which is a dict itself, with keys 'x', 'y', 'z' and 'c' for an optional comment. Exceptions: Type Description ValueError if a line in the file contains no values that could be parsed. Source code in hydrolib/core/dflowfm/xyz/parser.py @staticmethod def parse ( filepath : Path ) -> Dict : \"\"\"Parse an .xyz file into a Dict with the list of points read. Args: filepath (Path): .xyz file to be read. Returns: Dict: dictionary with \"points\" value set to a list of points each of which is a dict itself, with keys 'x', 'y', 'z' and 'c' for an optional comment. Raises: ValueError: if a line in the file contains no values that could be parsed. \"\"\" data : Dict = dict ( points = []) with filepath . open ( encoding = \"utf8\" ) as f : for linenr , line in enumerate ( f . readlines ()): line = line . strip () if line . startswith ( \"*\" ) or len ( line ) == 0 : continue try : x , y , z , * c = re . split ( xyzpattern , line , maxsplit = 3 ) except ValueError : raise ValueError ( f \"Error parsing XYZ file ' { filepath } ', line { linenr + 1 } .\" ) c = c [ 0 ] if len ( c ) > 0 else \"\" c = c . strip ( \"#\" ) . strip () if len ( c ) == 0 : c = None data [ \"points\" ] . append ( dict ( x = x , y = y , z = z , comment = c )) return data Serializer \u00b6 XYZSerializer \u00b6 serialize ( path : Path , data : Dict , config : SerializerConfig , save_settings : ModelSaveSettings ) -> None staticmethod \u00b6 Serializes the XYZ data to the file at the specified path. Attributes: Name Type Description path Path The path to the destination file. data Dict The data to be serialized. config SerializerConfig The serialization configuration. save_settings ModelSaveSettings The model save settings. Source code in hydrolib/core/dflowfm/xyz/serializer.py @staticmethod def serialize ( path : Path , data : Dict , config : SerializerConfig , save_settings : ModelSaveSettings , ) -> None : \"\"\" Serializes the XYZ data to the file at the specified path. Attributes: path (Path): The path to the destination file. data (Dict): The data to be serialized. config (SerializerConfig): The serialization configuration. save_settings (ModelSaveSettings): The model save settings. \"\"\" path . parent . mkdir ( parents = True , exist_ok = True ) space = 1 * \" \" format_float = lambda x : f \" { x :{ config . float_format }} \" with path . open ( \"w\" , encoding = \"utf8\" ) as f : for point in data [ \"points\" ]: geometry : str = space . join ( [ format_float ( p ) for p in XYZSerializer . _get_point_values ( point )] ) if point . comment : f . write ( f \" { geometry } # { point . comment } \\n \" ) else : f . write ( f \" { geometry } \\n \" )","title":"Sample files"},{"location":"reference/xyz/#sample-files","text":"Sample .xyz files contain spatial input point data for a D-Flow FM model, and are used in various other input files. A sample data file is described by the classes below.","title":"Sample files"},{"location":"reference/xyz/#model","text":"","title":"Model"},{"location":"reference/xyz/#hydrolib.core.dflowfm.xyz.models.XYZModel","text":"Sample or forcing file. Attributes: Name Type Description points List[hydrolib.core.dflowfm.xyz.models.XYZPoint] List of XYZPoint","title":"XYZModel"},{"location":"reference/xyz/#hydrolib.core.dflowfm.xyz.models.XYZModel.dict","text":"Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dflowfm/xyz/models.py def dict ( self , * args , ** kwargs ): # speed up serializing by not converting these lowest models to dict return dict ( points = self . points )","title":"dict()"},{"location":"reference/xyz/#hydrolib.core.dflowfm.xyz.models.XYZPoint","text":"Single sample or forcing point. Attributes: Name Type Description x float x or \u03bb coordinate y float y or \u03c6 coordinate z float sample value or group number (forcing) comment Optional[str] keyword for grouping (forcing)","title":"XYZPoint"},{"location":"reference/xyz/#hydrolib.core.dflowfm.xyz.models.XYZPoint.comment","text":"comment or group name","title":"comment"},{"location":"reference/xyz/#parser","text":"","title":"Parser"},{"location":"reference/xyz/#hydrolib.core.dflowfm.xyz.parser.XYZParser","text":"A parser for .xyz files which are like this: number number number number number number # comment Note that the whitespace can vary and the comment left out.","title":"XYZParser"},{"location":"reference/xyz/#hydrolib.core.dflowfm.xyz.parser.XYZParser.parse","text":"Parse an .xyz file into a Dict with the list of points read. Parameters: Name Type Description Default filepath Path .xyz file to be read. required Returns: Type Description Dict dictionary with \"points\" value set to a list of points each of which is a dict itself, with keys 'x', 'y', 'z' and 'c' for an optional comment. Exceptions: Type Description ValueError if a line in the file contains no values that could be parsed. Source code in hydrolib/core/dflowfm/xyz/parser.py @staticmethod def parse ( filepath : Path ) -> Dict : \"\"\"Parse an .xyz file into a Dict with the list of points read. Args: filepath (Path): .xyz file to be read. Returns: Dict: dictionary with \"points\" value set to a list of points each of which is a dict itself, with keys 'x', 'y', 'z' and 'c' for an optional comment. Raises: ValueError: if a line in the file contains no values that could be parsed. \"\"\" data : Dict = dict ( points = []) with filepath . open ( encoding = \"utf8\" ) as f : for linenr , line in enumerate ( f . readlines ()): line = line . strip () if line . startswith ( \"*\" ) or len ( line ) == 0 : continue try : x , y , z , * c = re . split ( xyzpattern , line , maxsplit = 3 ) except ValueError : raise ValueError ( f \"Error parsing XYZ file ' { filepath } ', line { linenr + 1 } .\" ) c = c [ 0 ] if len ( c ) > 0 else \"\" c = c . strip ( \"#\" ) . strip () if len ( c ) == 0 : c = None data [ \"points\" ] . append ( dict ( x = x , y = y , z = z , comment = c )) return data","title":"parse()"},{"location":"reference/xyz/#serializer","text":"","title":"Serializer"},{"location":"reference/xyz/#hydrolib.core.dflowfm.xyz.serializer.XYZSerializer","text":"","title":"XYZSerializer"},{"location":"reference/xyz/#hydrolib.core.dflowfm.xyz.serializer.XYZSerializer.serialize","text":"Serializes the XYZ data to the file at the specified path. Attributes: Name Type Description path Path The path to the destination file. data Dict The data to be serialized. config SerializerConfig The serialization configuration. save_settings ModelSaveSettings The model save settings. Source code in hydrolib/core/dflowfm/xyz/serializer.py @staticmethod def serialize ( path : Path , data : Dict , config : SerializerConfig , save_settings : ModelSaveSettings , ) -> None : \"\"\" Serializes the XYZ data to the file at the specified path. Attributes: path (Path): The path to the destination file. data (Dict): The data to be serialized. config (SerializerConfig): The serialization configuration. save_settings (ModelSaveSettings): The model save settings. \"\"\" path . parent . mkdir ( parents = True , exist_ok = True ) space = 1 * \" \" format_float = lambda x : f \" { x :{ config . float_format }} \" with path . open ( \"w\" , encoding = \"utf8\" ) as f : for point in data [ \"points\" ]: geometry : str = space . join ( [ format_float ( p ) for p in XYZSerializer . _get_point_values ( point )] ) if point . comment : f . write ( f \" { geometry } # { point . comment } \\n \" ) else : f . write ( f \" { geometry } \\n \" )","title":"serialize()"},{"location":"reference/rr/meteo/","text":"The Rainfall Runoff meteo layer \u00b6 The meteo layer currently contains only support for the BUI file. The \"bui\" file contains the precipitation input data for Rainfall Runoff . It is represented by the classes below. Model \u00b6 BuiModel ( ParsableFileModel ) pydantic-model \u00b6 Model that represents the file structure of a .bui file. get_station_events ( self , station : str ) -> Dict [ datetime . datetime , List [ float ]] \u00b6 Returns all the events (start time and precipitations) related to a given station. Parameters: Name Type Description Default station str Name of the station to retrieve. required Exceptions: Type Description ValueError If the station name does not exist in the BuiModel. Returns: Type Description Dict[datetime, List[float]] Dictionary with the start time and its precipitations. Source code in hydrolib/core/rr/meteo/models.py def get_station_events ( self , station : str ) -> Dict [ datetime , List [ float ]]: \"\"\" Returns all the events (start time and precipitations) related to a given station. Args: station (str): Name of the station to retrieve. Raises: ValueError: If the station name does not exist in the BuiModel. Returns: Dict[datetime, List[float]]: Dictionary with the start time and its precipitations. \"\"\" if station not in self . name_of_stations : raise ValueError ( \"Station {} not found BuiModel.\" . format ( station )) station_idx = self . name_of_stations . index ( station ) station_events = {} for event in self . precipitation_events : start_time , precipitations = event . get_station_precipitations ( station_idx ) station_events [ start_time ] = precipitations return station_events BuiPrecipitationEvent ( BaseModel ) pydantic-model \u00b6 get_station_precipitations ( self , station_idx : int ) -> Tuple [ datetime . datetime , List [ float ]] \u00b6 Returns all the precipitations related to the given station index (column). Parameters: Name Type Description Default station_idx int Index of the column which values need to be retrieved. required Exceptions: Type Description ValueError If the station index does not exist. Returns: Type Description Tuple[datetime, List[float]] Tuple with the start time and its precipitations. Source code in hydrolib/core/rr/meteo/models.py def get_station_precipitations ( self , station_idx : int ) -> Tuple [ datetime , List [ float ]]: \"\"\" Returns all the precipitations related to the given station index (column). Args: station_idx (int): Index of the column which values need to be retrieved. Raises: ValueError: If the station index does not exist. Returns: Tuple[datetime, List[float]]: Tuple with the start time and its precipitations. \"\"\" number_of_stations = len ( self . precipitation_per_timestep [ 0 ]) if station_idx >= number_of_stations : raise ValueError ( \"Station index not found, number of stations: {} \" . format ( number_of_stations ) ) return ( self . start_time , [ ts_precipitations [ station_idx ] for ts_precipitations in self . precipitation_per_timestep ], ) Parser \u00b6 BuiEventListParser \u00b6 A parser for .bui events which are like this: StartTime (YYYY mm dd HH MM SS) TimeSeriesLength (dd HH MM SS) PrecipitationPerTimestep StartTime (YYYY mm dd HH MM SS) TimeSeriesLength (dd HH MM SS) PrecipitationPerTimestep Example given: 2021 12 20 0 0 0 1 0 4 20 4.2 4.2 4.2 2021 12 21 0 0 0 1 0 4 20 2.4 2.4 2.4 parse ( raw_text : str , n_events : int , timestep : int ) -> List [ Dict ] staticmethod \u00b6 Parses a given raw text containing 0 to many text blocks representing a precipitation event. Parameters: Name Type Description Default raw_text str Text blocks representing precipitation events. required n_events int Number of events contained in the text block. required timestep int Number of seconds conforming a timestep. required Returns: Type Description List[Dict] List containing all the events represented as dictionaries. Source code in hydrolib/core/rr/meteo/parser.py @staticmethod def parse ( raw_text : str , n_events : int , timestep : int ) -> List [ Dict ]: \"\"\" Parses a given raw text containing 0 to many text blocks representing a precipitation event. Args: raw_text (str): Text blocks representing precipitation events. n_events (int): Number of events contained in the text block. timestep (int): Number of seconds conforming a timestep. Returns: List[Dict]: List containing all the events represented as dictionaries. \"\"\" def get_event_timestep_length ( raw_line : str ) -> int : timereference = BuiEventParser . parse_event_time_reference ( raw_line ) ts_length : timedelta = timereference [ \"timeseries_length\" ] return ts_length . total_seconds () def get_multiple_events ( raw_lines : List [ str ]) -> Iterator [ BuiEventParser ]: n_line = 0 while n_line < len ( raw_lines ): ts_seconds = get_event_timestep_length ( raw_lines [ n_line ]) event_lines = int ( ts_seconds / timestep ) + 1 yield BuiEventParser . parse ( \" \\n \" . join ( raw_lines [ n_line :][: event_lines ])) n_line += event_lines event_list = [] if n_events == 1 : event_list . append ( BuiEventParser . parse ( raw_text )) elif n_events > 1 : raw_lines = raw_text . splitlines ( keepends = False ) event_list = list ( get_multiple_events ( raw_lines )) return event_list BuiEventParser \u00b6 A parser for the precipitation event section within a .bui file. It resembles something like this: StartTime (YYYY mm dd HH MM SS) TimeSeriesLength (dd HH MM SS) PrecipitationPerTimestep Example given: 2021 12 20 0 0 0 1 0 4 20 4.2 2.4 4.2 2.4 4.2 2.4 (it should match the timeseries length based on the seconds per timstep.) Each column of the last three lines represents a station. parse ( raw_text : str ) -> Dict staticmethod \u00b6 Given text representing a single BuiPrecipitationEvent parses it into a dictionary. Parameters: Name Type Description Default raw_text str Text containing a single precipitation event. required Returns: Type Description Dict Mapped contents of the text. Source code in hydrolib/core/rr/meteo/parser.py @staticmethod def parse ( raw_text : str ) -> Dict : \"\"\" Given text representing a single BuiPrecipitationEvent parses it into a dictionary. Args: raw_text (str): Text containing a single precipitation event. Returns: Dict: Mapped contents of the text. \"\"\" def get_precipitations_per_ts ( line : str ) -> List [ str ]: return [ prec for prec in line . split ()] event_lines = raw_text . splitlines ( keepends = False ) time_reference = BuiEventParser . parse_event_time_reference ( event_lines [ 0 ]) return dict ( start_time = time_reference [ \"start_time\" ], timeseries_length = time_reference [ \"timeseries_length\" ], precipitation_per_timestep = list ( map ( get_precipitations_per_ts , event_lines [ 1 :]) ), ) parse_event_time_reference ( raw_text : str ) -> Dict staticmethod \u00b6 Parses a single event time reference line containing both the start time and the timeseries length into a dictionary. Parameters: Name Type Description Default raw_text str Line representing both start time and timeseries length. required Returns: Type Description Dict Resulting dictionary with keys start_time and timeseries_length. Source code in hydrolib/core/rr/meteo/parser.py @staticmethod def parse_event_time_reference ( raw_text : str ) -> Dict : \"\"\" Parses a single event time reference line containing both the start time and the timeseries length into a dictionary. Args: raw_text (str): Line representing both start time and timeseries length. Returns: Dict: Resulting dictionary with keys start_time and timeseries_length. \"\"\" def get_start_time ( line : str ) -> datetime : return datetime . strptime ( line , \"%Y %m %d %H %M %S\" ) def get_timeseries_length ( line : str ) -> timedelta : time_fields = line . split () return timedelta ( days = int ( time_fields [ 0 ]), hours = int ( time_fields [ 1 ]), minutes = int ( time_fields [ 2 ]), seconds = int ( time_fields [ 3 ]), ) timeref = raw_text . split () return dict ( start_time = get_start_time ( \" \" . join ( timeref [: 6 ])), timeseries_length = get_timeseries_length ( \" \" . join ( timeref [ 6 :])), ) BuiParser \u00b6 A parser for .bui files which are like this: * comments Dataset type to use (always 1). * comments Number of stations. * comments Name of stations * comments Number of events Number of seconds per timestep. * comments First datetime reference. Precipitation per timestep per station. parse ( filepath : Path ) -> Dict staticmethod \u00b6 Parses a given file, in case valid, into a dictionary which can later be mapped to the BuiModel. Parameters: Name Type Description Default filepath Path Path to file containing the data to parse. required Returns: Type Description Dict Parsed values. Source code in hydrolib/core/rr/meteo/parser.py @staticmethod def parse ( filepath : Path ) -> Dict : \"\"\" Parses a given file, in case valid, into a dictionary which can later be mapped to the BuiModel. Args: filepath (Path): Path to file containing the data to parse. Returns: Dict: Parsed values. \"\"\" def get_station_ids ( lines : List [ str ]) -> List [ str ]: return [ s_id . strip ( \"' \\\" \" ) for s_id in lines ] def parse_events_and_timestep ( line : str ) -> Tuple [ int , int ]: n_events_timestep = line . split () return ( int ( n_events_timestep [ 0 ]), int ( n_events_timestep [ 1 ])) bui_lines = [ line for line in filepath . read_text ( encoding = \"utf8\" ) . splitlines () if not line . startswith ( \"*\" ) ] number_of_stations = int ( bui_lines [ 1 ]) last_station_line = 1 + number_of_stations n_events , timestep = parse_events_and_timestep ( bui_lines [ last_station_line + 1 ]) return dict ( default_dataset = bui_lines [ 0 ], number_of_stations = bui_lines [ 1 ], name_of_stations = get_station_ids ( bui_lines [ 2 : last_station_line + 1 ]), number_of_events = n_events , seconds_per_timestep = timestep , precipitation_events = BuiEventListParser . parse ( \" \\n \" . join ( bui_lines [ last_station_line + 2 :]), n_events , timestep ), ) Serializer \u00b6 BuiEventSerializer \u00b6 Serializer class to transform a bui event into a text block. get_timedelta_fields ( duration : timedelta ) -> Dict staticmethod \u00b6 Gets a dictionary containing the time delta in days, hours, minutes and seconds. This means that the seconds field does not contain the accumulative value of days hours and minutes. Parameters: Name Type Description Default duration timedelta Timedelta to convert. required Returns: Type Description Dict Dictionary containing all fields. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def get_timedelta_fields ( duration : timedelta ) -> Dict : \"\"\" Gets a dictionary containing the time delta in days, hours, minutes and seconds. This means that the seconds field does not contain the accumulative value of days hours and minutes. Args: duration (timedelta): Timedelta to convert. Returns: Dict: Dictionary containing all fields. \"\"\" total_hours = int ( duration . seconds / ( 60 * 60 )) total_minutes = int (( duration . seconds / 60 ) - ( total_hours * 60 )) total_seconds = int ( duration . seconds - (( total_hours * 60 + total_minutes ) * 60 ) ) return dict ( d_seconds = total_seconds , d_minutes = total_minutes , d_hours = total_hours , d_days = duration . days , ) serialize ( event_data : Dict , config : SerializerConfig ) -> str staticmethod \u00b6 Serializes a dictionary representing an event into a text block. Parameters: Name Type Description Default event_data Dict Dictionary representing precipitation event. required config SerializerConfig The serialization configuration. required Returns: Type Description str Formatted string. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize ( event_data : Dict , config : SerializerConfig ) -> str : \"\"\" Serializes a dictionary representing an event into a text block. Args: event_data (Dict): Dictionary representing precipitation event. config (SerializerConfig): The serialization configuration. Returns: str: Formatted string. \"\"\" event_data [ \"start_time\" ] = BuiEventSerializer . serialize_start_time ( event_data [ \"start_time\" ] ) ts_duration = event_data [ \"timeseries_length\" ] event_data = { ** event_data , ** BuiEventSerializer . get_timedelta_fields ( ts_duration ), } event_data [ \"timeseries_length\" ] = BuiEventSerializer . serialize_timeseries_length ( event_data [ \"timeseries_length\" ] ) event_data [ \"precipitation_per_timestep\" ] = BuiEventSerializer . serialize_precipitation_per_timestep ( event_data [ \"precipitation_per_timestep\" ], config ) if \"event_idx\" not in event_data . keys (): event_data [ \"event_idx\" ] = 1 return BuiEventSerializer . bui_event_template . format ( ** event_data ) serialize_precipitation_per_timestep ( data_to_serialize : List [ List [ float ]], config : SerializerConfig ) -> str staticmethod \u00b6 Serialized the data containing all the precipitations per timestep (and station) into a single string ready to be mapped. Parameters: Name Type Description Default data_to_serialize List[List[str]] Data to be mapped. required config SerializerConfig The serialization configuration. required Returns: Type Description str Serialized string in .bui format. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_precipitation_per_timestep ( data_to_serialize : List [ List [ float ]], config : SerializerConfig ) -> str : \"\"\" Serialized the data containing all the precipitations per timestep (and station) into a single string ready to be mapped. Args: data_to_serialize (List[List[str]]): Data to be mapped. config (SerializerConfig): The serialization configuration. Returns: str: Serialized string in .bui format. \"\"\" float_format = lambda v : f \" { v :{ config . float_format }} \" serialized_data = str . join ( \" \\n \" , [ str . join ( \" \" , map ( float_format , listed_data )) for listed_data in data_to_serialize ], ) return serialized_data serialize_start_time ( data_to_serialize : datetime ) -> str staticmethod \u00b6 Serializes a datetime into the expected .bui format. Parameters: Name Type Description Default data_to_serialize datetime Datetime representing reference time. required Returns: Type Description str Converted datetime into string. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_start_time ( data_to_serialize : datetime ) -> str : \"\"\" Serializes a datetime into the expected .bui format. Args: data_to_serialize (datetime): Datetime representing reference time. Returns: str: Converted datetime into string. \"\"\" # Not using the following format because we only want one digit instead of # double (day 1 -> 1, instead of 01). # data_to_serialize.strftime(\"%Y %m %d %H %M %S\") dt = data_to_serialize return f \" { dt . year } { dt . month } { dt . day } { dt . hour } { dt . minute } { dt . second } \" serialize_timeseries_length ( data_to_serialize : timedelta ) -> str staticmethod \u00b6 Serializes a given timedelta into the .bui format. Parameters: Name Type Description Default data_to_serialize timedelta Reference timespan to serialize. required Returns: Type Description str Converted timedelta in string. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_timeseries_length ( data_to_serialize : timedelta ) -> str : \"\"\" Serializes a given timedelta into the .bui format. Args: data_to_serialize (timedelta): Reference timespan to serialize. Returns: str: Converted timedelta in string. \"\"\" fields_dict = BuiEventSerializer . get_timedelta_fields ( data_to_serialize ) total_hours = fields_dict [ \"d_hours\" ] total_minutes = fields_dict [ \"d_minutes\" ] total_seconds = fields_dict [ \"d_seconds\" ] return f \" { data_to_serialize . days } { total_hours } { total_minutes } { total_seconds } \" BuiSerializer \u00b6 Serializer class to transform an object into a .bui file text format. serialize ( bui_data : Dict , config : SerializerConfig ) -> str staticmethod \u00b6 Formats the bui_template with the content of the given data. NOTE: It requires that caller injects file_path into bui_data prior to this call. Otherwise it will crash. Parameters: Name Type Description Default bui_data Dict Data to serialize. required config SerializerConfig The serialization configuration. required Returns: Type Description str The serialized data. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize ( bui_data : Dict , config : SerializerConfig ) -> str : \"\"\" Formats the bui_template with the content of the given data. NOTE: It requires that caller injects file_path into bui_data prior to this call. Otherwise it will crash. Args: bui_data (Dict): Data to serialize. config (SerializerConfig): The serialization configuration. Returns: str: The serialized data. \"\"\" bui_data [ \"datetime_now\" ] = datetime . now () . strftime ( \" %d -%m-%y %H:%M:%S\" ) bui_data [ \"name_of_stations\" ] = BuiSerializer . serialize_stations_ids ( bui_data [ \"name_of_stations\" ] ) bui_data [ \"precipitation_events\" ] = BuiSerializer . serialize_event_list ( bui_data [ \"precipitation_events\" ], config ) return BuiSerializer . bui_template . format ( ** bui_data ) serialize_event_list ( data_to_serialize : List [ Dict ], config : SerializerConfig ) -> str staticmethod \u00b6 Serializes a event list dictionary into a single text block. Parameters: Name Type Description Default data_to_serialize Dict Dictionary containing list of events. required config SerializerConfig The serialization configuration. required Returns: Type Description str Text block representing all precipitation events. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_event_list ( data_to_serialize : List [ Dict ], config : SerializerConfig ) -> str : \"\"\" Serializes a event list dictionary into a single text block. Args: data_to_serialize (Dict): Dictionary containing list of events. config (SerializerConfig): The serialization configuration. Returns: str: Text block representing all precipitation events. \"\"\" serialized_list = [] for n_event , event in enumerate ( data_to_serialize ): event [ \"event_idx\" ] = n_event + 1 serialized_list . append ( BuiEventSerializer . serialize ( event , config )) return \" \\n \" . join ( serialized_list ) serialize_stations_ids ( data_to_serialize : List [ str ]) -> str staticmethod \u00b6 Serializes the stations ids into a single string as expected in a .bui file. Parameters: Name Type Description Default data_to_serialize List[str] List of station ids. required Returns: Type Description str Serialized string. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_stations_ids ( data_to_serialize : List [ str ]) -> str : \"\"\" Serializes the stations ids into a single string as expected in a .bui file. Args: data_to_serialize (List[str]): List of station ids. Returns: str: Serialized string. \"\"\" return \" \\n \" . join ( f \"' { station_id } '\" for station_id in data_to_serialize ) write_bui_file ( path : Path , data : Dict , config : SerializerConfig , save_settings : ModelSaveSettings ) -> None \u00b6 Writes a .bui file in the given path based on the data given in a dictionary. Parameters: Name Type Description Default path Path Path where to output the text. required data Dict Data to serialize into the file. required config SerializerConfig The serialization configuration. required save_settings ModelSaveSettings The model save settings. required Source code in hydrolib/core/rr/meteo/serializer.py def write_bui_file ( path : Path , data : Dict , config : SerializerConfig , save_settings : ModelSaveSettings ) -> None : \"\"\" Writes a .bui file in the given path based on the data given in a dictionary. Args: path (Path): Path where to output the text. data (Dict): Data to serialize into the file. config (SerializerConfig): The serialization configuration. save_settings (ModelSaveSettings): The model save settings. \"\"\" data [ \"filepath\" ] = path # This is redundant as already exists in the data. serialized_bui_data = BuiSerializer . serialize ( data , config ) path . parent . mkdir ( parents = True , exist_ok = True ) path . write_text ( serialized_bui_data , encoding = \"utf8\" )","title":"The Rainfall Runoff meteo layer"},{"location":"reference/rr/meteo/#the-rainfall-runoff-meteo-layer","text":"The meteo layer currently contains only support for the BUI file. The \"bui\" file contains the precipitation input data for Rainfall Runoff . It is represented by the classes below.","title":"The Rainfall Runoff meteo layer"},{"location":"reference/rr/meteo/#model","text":"","title":"Model"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.models.BuiModel","text":"Model that represents the file structure of a .bui file.","title":"BuiModel"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.models.BuiModel.get_station_events","text":"Returns all the events (start time and precipitations) related to a given station. Parameters: Name Type Description Default station str Name of the station to retrieve. required Exceptions: Type Description ValueError If the station name does not exist in the BuiModel. Returns: Type Description Dict[datetime, List[float]] Dictionary with the start time and its precipitations. Source code in hydrolib/core/rr/meteo/models.py def get_station_events ( self , station : str ) -> Dict [ datetime , List [ float ]]: \"\"\" Returns all the events (start time and precipitations) related to a given station. Args: station (str): Name of the station to retrieve. Raises: ValueError: If the station name does not exist in the BuiModel. Returns: Dict[datetime, List[float]]: Dictionary with the start time and its precipitations. \"\"\" if station not in self . name_of_stations : raise ValueError ( \"Station {} not found BuiModel.\" . format ( station )) station_idx = self . name_of_stations . index ( station ) station_events = {} for event in self . precipitation_events : start_time , precipitations = event . get_station_precipitations ( station_idx ) station_events [ start_time ] = precipitations return station_events","title":"get_station_events()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.models.BuiPrecipitationEvent","text":"","title":"BuiPrecipitationEvent"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.models.BuiPrecipitationEvent.get_station_precipitations","text":"Returns all the precipitations related to the given station index (column). Parameters: Name Type Description Default station_idx int Index of the column which values need to be retrieved. required Exceptions: Type Description ValueError If the station index does not exist. Returns: Type Description Tuple[datetime, List[float]] Tuple with the start time and its precipitations. Source code in hydrolib/core/rr/meteo/models.py def get_station_precipitations ( self , station_idx : int ) -> Tuple [ datetime , List [ float ]]: \"\"\" Returns all the precipitations related to the given station index (column). Args: station_idx (int): Index of the column which values need to be retrieved. Raises: ValueError: If the station index does not exist. Returns: Tuple[datetime, List[float]]: Tuple with the start time and its precipitations. \"\"\" number_of_stations = len ( self . precipitation_per_timestep [ 0 ]) if station_idx >= number_of_stations : raise ValueError ( \"Station index not found, number of stations: {} \" . format ( number_of_stations ) ) return ( self . start_time , [ ts_precipitations [ station_idx ] for ts_precipitations in self . precipitation_per_timestep ], )","title":"get_station_precipitations()"},{"location":"reference/rr/meteo/#parser","text":"","title":"Parser"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.parser.BuiEventListParser","text":"A parser for .bui events which are like this: StartTime (YYYY mm dd HH MM SS) TimeSeriesLength (dd HH MM SS) PrecipitationPerTimestep StartTime (YYYY mm dd HH MM SS) TimeSeriesLength (dd HH MM SS) PrecipitationPerTimestep Example given: 2021 12 20 0 0 0 1 0 4 20 4.2 4.2 4.2 2021 12 21 0 0 0 1 0 4 20 2.4 2.4 2.4","title":"BuiEventListParser"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.parser.BuiEventListParser.parse","text":"Parses a given raw text containing 0 to many text blocks representing a precipitation event. Parameters: Name Type Description Default raw_text str Text blocks representing precipitation events. required n_events int Number of events contained in the text block. required timestep int Number of seconds conforming a timestep. required Returns: Type Description List[Dict] List containing all the events represented as dictionaries. Source code in hydrolib/core/rr/meteo/parser.py @staticmethod def parse ( raw_text : str , n_events : int , timestep : int ) -> List [ Dict ]: \"\"\" Parses a given raw text containing 0 to many text blocks representing a precipitation event. Args: raw_text (str): Text blocks representing precipitation events. n_events (int): Number of events contained in the text block. timestep (int): Number of seconds conforming a timestep. Returns: List[Dict]: List containing all the events represented as dictionaries. \"\"\" def get_event_timestep_length ( raw_line : str ) -> int : timereference = BuiEventParser . parse_event_time_reference ( raw_line ) ts_length : timedelta = timereference [ \"timeseries_length\" ] return ts_length . total_seconds () def get_multiple_events ( raw_lines : List [ str ]) -> Iterator [ BuiEventParser ]: n_line = 0 while n_line < len ( raw_lines ): ts_seconds = get_event_timestep_length ( raw_lines [ n_line ]) event_lines = int ( ts_seconds / timestep ) + 1 yield BuiEventParser . parse ( \" \\n \" . join ( raw_lines [ n_line :][: event_lines ])) n_line += event_lines event_list = [] if n_events == 1 : event_list . append ( BuiEventParser . parse ( raw_text )) elif n_events > 1 : raw_lines = raw_text . splitlines ( keepends = False ) event_list = list ( get_multiple_events ( raw_lines )) return event_list","title":"parse()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.parser.BuiEventParser","text":"A parser for the precipitation event section within a .bui file. It resembles something like this: StartTime (YYYY mm dd HH MM SS) TimeSeriesLength (dd HH MM SS) PrecipitationPerTimestep Example given: 2021 12 20 0 0 0 1 0 4 20 4.2 2.4 4.2 2.4 4.2 2.4 (it should match the timeseries length based on the seconds per timstep.) Each column of the last three lines represents a station.","title":"BuiEventParser"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.parser.BuiEventParser.parse","text":"Given text representing a single BuiPrecipitationEvent parses it into a dictionary. Parameters: Name Type Description Default raw_text str Text containing a single precipitation event. required Returns: Type Description Dict Mapped contents of the text. Source code in hydrolib/core/rr/meteo/parser.py @staticmethod def parse ( raw_text : str ) -> Dict : \"\"\" Given text representing a single BuiPrecipitationEvent parses it into a dictionary. Args: raw_text (str): Text containing a single precipitation event. Returns: Dict: Mapped contents of the text. \"\"\" def get_precipitations_per_ts ( line : str ) -> List [ str ]: return [ prec for prec in line . split ()] event_lines = raw_text . splitlines ( keepends = False ) time_reference = BuiEventParser . parse_event_time_reference ( event_lines [ 0 ]) return dict ( start_time = time_reference [ \"start_time\" ], timeseries_length = time_reference [ \"timeseries_length\" ], precipitation_per_timestep = list ( map ( get_precipitations_per_ts , event_lines [ 1 :]) ), )","title":"parse()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.parser.BuiEventParser.parse_event_time_reference","text":"Parses a single event time reference line containing both the start time and the timeseries length into a dictionary. Parameters: Name Type Description Default raw_text str Line representing both start time and timeseries length. required Returns: Type Description Dict Resulting dictionary with keys start_time and timeseries_length. Source code in hydrolib/core/rr/meteo/parser.py @staticmethod def parse_event_time_reference ( raw_text : str ) -> Dict : \"\"\" Parses a single event time reference line containing both the start time and the timeseries length into a dictionary. Args: raw_text (str): Line representing both start time and timeseries length. Returns: Dict: Resulting dictionary with keys start_time and timeseries_length. \"\"\" def get_start_time ( line : str ) -> datetime : return datetime . strptime ( line , \"%Y %m %d %H %M %S\" ) def get_timeseries_length ( line : str ) -> timedelta : time_fields = line . split () return timedelta ( days = int ( time_fields [ 0 ]), hours = int ( time_fields [ 1 ]), minutes = int ( time_fields [ 2 ]), seconds = int ( time_fields [ 3 ]), ) timeref = raw_text . split () return dict ( start_time = get_start_time ( \" \" . join ( timeref [: 6 ])), timeseries_length = get_timeseries_length ( \" \" . join ( timeref [ 6 :])), )","title":"parse_event_time_reference()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.parser.BuiParser","text":"A parser for .bui files which are like this: * comments Dataset type to use (always 1). * comments Number of stations. * comments Name of stations * comments Number of events Number of seconds per timestep. * comments First datetime reference. Precipitation per timestep per station.","title":"BuiParser"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.parser.BuiParser.parse","text":"Parses a given file, in case valid, into a dictionary which can later be mapped to the BuiModel. Parameters: Name Type Description Default filepath Path Path to file containing the data to parse. required Returns: Type Description Dict Parsed values. Source code in hydrolib/core/rr/meteo/parser.py @staticmethod def parse ( filepath : Path ) -> Dict : \"\"\" Parses a given file, in case valid, into a dictionary which can later be mapped to the BuiModel. Args: filepath (Path): Path to file containing the data to parse. Returns: Dict: Parsed values. \"\"\" def get_station_ids ( lines : List [ str ]) -> List [ str ]: return [ s_id . strip ( \"' \\\" \" ) for s_id in lines ] def parse_events_and_timestep ( line : str ) -> Tuple [ int , int ]: n_events_timestep = line . split () return ( int ( n_events_timestep [ 0 ]), int ( n_events_timestep [ 1 ])) bui_lines = [ line for line in filepath . read_text ( encoding = \"utf8\" ) . splitlines () if not line . startswith ( \"*\" ) ] number_of_stations = int ( bui_lines [ 1 ]) last_station_line = 1 + number_of_stations n_events , timestep = parse_events_and_timestep ( bui_lines [ last_station_line + 1 ]) return dict ( default_dataset = bui_lines [ 0 ], number_of_stations = bui_lines [ 1 ], name_of_stations = get_station_ids ( bui_lines [ 2 : last_station_line + 1 ]), number_of_events = n_events , seconds_per_timestep = timestep , precipitation_events = BuiEventListParser . parse ( \" \\n \" . join ( bui_lines [ last_station_line + 2 :]), n_events , timestep ), )","title":"parse()"},{"location":"reference/rr/meteo/#serializer","text":"","title":"Serializer"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiEventSerializer","text":"Serializer class to transform a bui event into a text block.","title":"BuiEventSerializer"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiEventSerializer.get_timedelta_fields","text":"Gets a dictionary containing the time delta in days, hours, minutes and seconds. This means that the seconds field does not contain the accumulative value of days hours and minutes. Parameters: Name Type Description Default duration timedelta Timedelta to convert. required Returns: Type Description Dict Dictionary containing all fields. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def get_timedelta_fields ( duration : timedelta ) -> Dict : \"\"\" Gets a dictionary containing the time delta in days, hours, minutes and seconds. This means that the seconds field does not contain the accumulative value of days hours and minutes. Args: duration (timedelta): Timedelta to convert. Returns: Dict: Dictionary containing all fields. \"\"\" total_hours = int ( duration . seconds / ( 60 * 60 )) total_minutes = int (( duration . seconds / 60 ) - ( total_hours * 60 )) total_seconds = int ( duration . seconds - (( total_hours * 60 + total_minutes ) * 60 ) ) return dict ( d_seconds = total_seconds , d_minutes = total_minutes , d_hours = total_hours , d_days = duration . days , )","title":"get_timedelta_fields()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiEventSerializer.serialize","text":"Serializes a dictionary representing an event into a text block. Parameters: Name Type Description Default event_data Dict Dictionary representing precipitation event. required config SerializerConfig The serialization configuration. required Returns: Type Description str Formatted string. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize ( event_data : Dict , config : SerializerConfig ) -> str : \"\"\" Serializes a dictionary representing an event into a text block. Args: event_data (Dict): Dictionary representing precipitation event. config (SerializerConfig): The serialization configuration. Returns: str: Formatted string. \"\"\" event_data [ \"start_time\" ] = BuiEventSerializer . serialize_start_time ( event_data [ \"start_time\" ] ) ts_duration = event_data [ \"timeseries_length\" ] event_data = { ** event_data , ** BuiEventSerializer . get_timedelta_fields ( ts_duration ), } event_data [ \"timeseries_length\" ] = BuiEventSerializer . serialize_timeseries_length ( event_data [ \"timeseries_length\" ] ) event_data [ \"precipitation_per_timestep\" ] = BuiEventSerializer . serialize_precipitation_per_timestep ( event_data [ \"precipitation_per_timestep\" ], config ) if \"event_idx\" not in event_data . keys (): event_data [ \"event_idx\" ] = 1 return BuiEventSerializer . bui_event_template . format ( ** event_data )","title":"serialize()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiEventSerializer.serialize_precipitation_per_timestep","text":"Serialized the data containing all the precipitations per timestep (and station) into a single string ready to be mapped. Parameters: Name Type Description Default data_to_serialize List[List[str]] Data to be mapped. required config SerializerConfig The serialization configuration. required Returns: Type Description str Serialized string in .bui format. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_precipitation_per_timestep ( data_to_serialize : List [ List [ float ]], config : SerializerConfig ) -> str : \"\"\" Serialized the data containing all the precipitations per timestep (and station) into a single string ready to be mapped. Args: data_to_serialize (List[List[str]]): Data to be mapped. config (SerializerConfig): The serialization configuration. Returns: str: Serialized string in .bui format. \"\"\" float_format = lambda v : f \" { v :{ config . float_format }} \" serialized_data = str . join ( \" \\n \" , [ str . join ( \" \" , map ( float_format , listed_data )) for listed_data in data_to_serialize ], ) return serialized_data","title":"serialize_precipitation_per_timestep()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiEventSerializer.serialize_start_time","text":"Serializes a datetime into the expected .bui format. Parameters: Name Type Description Default data_to_serialize datetime Datetime representing reference time. required Returns: Type Description str Converted datetime into string. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_start_time ( data_to_serialize : datetime ) -> str : \"\"\" Serializes a datetime into the expected .bui format. Args: data_to_serialize (datetime): Datetime representing reference time. Returns: str: Converted datetime into string. \"\"\" # Not using the following format because we only want one digit instead of # double (day 1 -> 1, instead of 01). # data_to_serialize.strftime(\"%Y %m %d %H %M %S\") dt = data_to_serialize return f \" { dt . year } { dt . month } { dt . day } { dt . hour } { dt . minute } { dt . second } \"","title":"serialize_start_time()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiEventSerializer.serialize_timeseries_length","text":"Serializes a given timedelta into the .bui format. Parameters: Name Type Description Default data_to_serialize timedelta Reference timespan to serialize. required Returns: Type Description str Converted timedelta in string. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_timeseries_length ( data_to_serialize : timedelta ) -> str : \"\"\" Serializes a given timedelta into the .bui format. Args: data_to_serialize (timedelta): Reference timespan to serialize. Returns: str: Converted timedelta in string. \"\"\" fields_dict = BuiEventSerializer . get_timedelta_fields ( data_to_serialize ) total_hours = fields_dict [ \"d_hours\" ] total_minutes = fields_dict [ \"d_minutes\" ] total_seconds = fields_dict [ \"d_seconds\" ] return f \" { data_to_serialize . days } { total_hours } { total_minutes } { total_seconds } \"","title":"serialize_timeseries_length()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiSerializer","text":"Serializer class to transform an object into a .bui file text format.","title":"BuiSerializer"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiSerializer.serialize","text":"Formats the bui_template with the content of the given data. NOTE: It requires that caller injects file_path into bui_data prior to this call. Otherwise it will crash. Parameters: Name Type Description Default bui_data Dict Data to serialize. required config SerializerConfig The serialization configuration. required Returns: Type Description str The serialized data. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize ( bui_data : Dict , config : SerializerConfig ) -> str : \"\"\" Formats the bui_template with the content of the given data. NOTE: It requires that caller injects file_path into bui_data prior to this call. Otherwise it will crash. Args: bui_data (Dict): Data to serialize. config (SerializerConfig): The serialization configuration. Returns: str: The serialized data. \"\"\" bui_data [ \"datetime_now\" ] = datetime . now () . strftime ( \" %d -%m-%y %H:%M:%S\" ) bui_data [ \"name_of_stations\" ] = BuiSerializer . serialize_stations_ids ( bui_data [ \"name_of_stations\" ] ) bui_data [ \"precipitation_events\" ] = BuiSerializer . serialize_event_list ( bui_data [ \"precipitation_events\" ], config ) return BuiSerializer . bui_template . format ( ** bui_data )","title":"serialize()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiSerializer.serialize_event_list","text":"Serializes a event list dictionary into a single text block. Parameters: Name Type Description Default data_to_serialize Dict Dictionary containing list of events. required config SerializerConfig The serialization configuration. required Returns: Type Description str Text block representing all precipitation events. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_event_list ( data_to_serialize : List [ Dict ], config : SerializerConfig ) -> str : \"\"\" Serializes a event list dictionary into a single text block. Args: data_to_serialize (Dict): Dictionary containing list of events. config (SerializerConfig): The serialization configuration. Returns: str: Text block representing all precipitation events. \"\"\" serialized_list = [] for n_event , event in enumerate ( data_to_serialize ): event [ \"event_idx\" ] = n_event + 1 serialized_list . append ( BuiEventSerializer . serialize ( event , config )) return \" \\n \" . join ( serialized_list )","title":"serialize_event_list()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiSerializer.serialize_stations_ids","text":"Serializes the stations ids into a single string as expected in a .bui file. Parameters: Name Type Description Default data_to_serialize List[str] List of station ids. required Returns: Type Description str Serialized string. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_stations_ids ( data_to_serialize : List [ str ]) -> str : \"\"\" Serializes the stations ids into a single string as expected in a .bui file. Args: data_to_serialize (List[str]): List of station ids. Returns: str: Serialized string. \"\"\" return \" \\n \" . join ( f \"' { station_id } '\" for station_id in data_to_serialize )","title":"serialize_stations_ids()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.write_bui_file","text":"Writes a .bui file in the given path based on the data given in a dictionary. Parameters: Name Type Description Default path Path Path where to output the text. required data Dict Data to serialize into the file. required config SerializerConfig The serialization configuration. required save_settings ModelSaveSettings The model save settings. required Source code in hydrolib/core/rr/meteo/serializer.py def write_bui_file ( path : Path , data : Dict , config : SerializerConfig , save_settings : ModelSaveSettings ) -> None : \"\"\" Writes a .bui file in the given path based on the data given in a dictionary. Args: path (Path): Path where to output the text. data (Dict): Data to serialize into the file. config (SerializerConfig): The serialization configuration. save_settings (ModelSaveSettings): The model save settings. \"\"\" data [ \"filepath\" ] = path # This is redundant as already exists in the data. serialized_bui_data = BuiSerializer . serialize ( data , config ) path . parent . mkdir ( parents = True , exist_ok = True ) path . write_text ( serialized_bui_data , encoding = \"utf8\" )","title":"write_bui_file()"},{"location":"reference/rr/rr/","text":"RainfallRunoff file models \u00b6 The rr module provides the various file models for files that are input to the Rainfall Runoff kernel. Support is still basic, but growing. The input 'layers' listed below correspond with the input description in the SOBEK UM . Main input (sobek_3b.fnm) \u00b6 models.py defines the RainfallRunoffModel and supporting structures. ImmutableDiskOnlyFileModel ( DiskOnlyFileModel ) pydantic-model \u00b6 ImmutableDiskOnlyFileModel modifies the DiskOnlyFileModel to provide faux immutablitity. This behaviour is required for the mappix properties, which should always have the same name and path and should not be modified by users. RainfallRunoffModel ( ParsableFileModel ) pydantic-model \u00b6 The RainfallRunoffModel contains all paths and sub-models related to the Rainfall Runoff model. General layer \u00b6 rainfall file \u00b6 BuiModel ( ParsableFileModel ) pydantic-model \u00b6 Model that represents the file structure of a .bui file. get_station_events ( self , station : str ) -> Dict [ datetime . datetime , List [ float ]] \u00b6 Returns all the events (start time and precipitations) related to a given station. Parameters: Name Type Description Default station str Name of the station to retrieve. required Exceptions: Type Description ValueError If the station name does not exist in the BuiModel. Returns: Type Description Dict[datetime, List[float]] Dictionary with the start time and its precipitations. Source code in hydrolib/core/rr/meteo/models.py def get_station_events ( self , station : str ) -> Dict [ datetime , List [ float ]]: \"\"\" Returns all the events (start time and precipitations) related to a given station. Args: station (str): Name of the station to retrieve. Raises: ValueError: If the station name does not exist in the BuiModel. Returns: Dict[datetime, List[float]]: Dictionary with the start time and its precipitations. \"\"\" if station not in self . name_of_stations : raise ValueError ( \"Station {} not found BuiModel.\" . format ( station )) station_idx = self . name_of_stations . index ( station ) station_events = {} for event in self . precipitation_events : start_time , precipitations = event . get_station_precipitations ( station_idx ) station_events [ start_time ] = precipitations return station_events BuiPrecipitationEvent ( BaseModel ) pydantic-model \u00b6 get_station_precipitations ( self , station_idx : int ) -> Tuple [ datetime . datetime , List [ float ]] \u00b6 Returns all the precipitations related to the given station index (column). Parameters: Name Type Description Default station_idx int Index of the column which values need to be retrieved. required Exceptions: Type Description ValueError If the station index does not exist. Returns: Type Description Tuple[datetime, List[float]] Tuple with the start time and its precipitations. Source code in hydrolib/core/rr/meteo/models.py def get_station_precipitations ( self , station_idx : int ) -> Tuple [ datetime , List [ float ]]: \"\"\" Returns all the precipitations related to the given station index (column). Args: station_idx (int): Index of the column which values need to be retrieved. Raises: ValueError: If the station index does not exist. Returns: Tuple[datetime, List[float]]: Tuple with the start time and its precipitations. \"\"\" number_of_stations = len ( self . precipitation_per_timestep [ 0 ]) if station_idx >= number_of_stations : raise ValueError ( \"Station index not found, number of stations: {} \" . format ( number_of_stations ) ) return ( self . start_time , [ ts_precipitations [ station_idx ] for ts_precipitations in self . precipitation_per_timestep ], ) Topology layer (\"Topography\" in SOBEK UM) \u00b6 Link ( BaseModel ) pydantic-model \u00b6 Represents a link from the topology link file. dict ( self , * args , ** kwargs ) \u00b6 Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/rr/topology/models.py def dict ( self , * args , ** kwargs ): kwargs [ \"by_alias\" ] = True return super () . dict ( * args , ** kwargs ) LinkFile ( ParsableFileModel ) pydantic-model \u00b6 Represents the file with the RR link topology data. Node ( BaseModel ) pydantic-model \u00b6 Represents a node from the topology node file. dict ( self , * args , ** kwargs ) \u00b6 Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/rr/topology/models.py def dict ( self , * args , ** kwargs ): kwargs [ \"by_alias\" ] = True return super () . dict ( * args , ** kwargs ) NodeFile ( ParsableFileModel ) pydantic-model \u00b6 Represents the file with the RR node topology data. nodetypes_netter_to_rr \u00b6 Dictionary with nt mapped against the expected mt . Some model types mt do not have a related netter type; in that case the dict key is a dummy value of - . (Other input layers foreseen in future releases) \u00b6","title":"RainfallRunoff file models"},{"location":"reference/rr/rr/#rainfallrunoff-file-models","text":"The rr module provides the various file models for files that are input to the Rainfall Runoff kernel. Support is still basic, but growing. The input 'layers' listed below correspond with the input description in the SOBEK UM .","title":"RainfallRunoff file models"},{"location":"reference/rr/rr/#main-input-sobek_3bfnm","text":"models.py defines the RainfallRunoffModel and supporting structures.","title":"Main input (sobek_3b.fnm)"},{"location":"reference/rr/rr/#hydrolib.core.rr.models.ImmutableDiskOnlyFileModel","text":"ImmutableDiskOnlyFileModel modifies the DiskOnlyFileModel to provide faux immutablitity. This behaviour is required for the mappix properties, which should always have the same name and path and should not be modified by users.","title":"ImmutableDiskOnlyFileModel"},{"location":"reference/rr/rr/#hydrolib.core.rr.models.RainfallRunoffModel","text":"The RainfallRunoffModel contains all paths and sub-models related to the Rainfall Runoff model.","title":"RainfallRunoffModel"},{"location":"reference/rr/rr/#general-layer","text":"","title":"General layer"},{"location":"reference/rr/rr/#rainfall-file","text":"","title":"rainfall file"},{"location":"reference/rr/rr/#hydrolib.core.rr.meteo.models.BuiModel","text":"Model that represents the file structure of a .bui file.","title":"BuiModel"},{"location":"reference/rr/rr/#hydrolib.core.rr.meteo.models.BuiModel.get_station_events","text":"Returns all the events (start time and precipitations) related to a given station. Parameters: Name Type Description Default station str Name of the station to retrieve. required Exceptions: Type Description ValueError If the station name does not exist in the BuiModel. Returns: Type Description Dict[datetime, List[float]] Dictionary with the start time and its precipitations. Source code in hydrolib/core/rr/meteo/models.py def get_station_events ( self , station : str ) -> Dict [ datetime , List [ float ]]: \"\"\" Returns all the events (start time and precipitations) related to a given station. Args: station (str): Name of the station to retrieve. Raises: ValueError: If the station name does not exist in the BuiModel. Returns: Dict[datetime, List[float]]: Dictionary with the start time and its precipitations. \"\"\" if station not in self . name_of_stations : raise ValueError ( \"Station {} not found BuiModel.\" . format ( station )) station_idx = self . name_of_stations . index ( station ) station_events = {} for event in self . precipitation_events : start_time , precipitations = event . get_station_precipitations ( station_idx ) station_events [ start_time ] = precipitations return station_events","title":"get_station_events()"},{"location":"reference/rr/rr/#hydrolib.core.rr.meteo.models.BuiPrecipitationEvent","text":"","title":"BuiPrecipitationEvent"},{"location":"reference/rr/rr/#hydrolib.core.rr.meteo.models.BuiPrecipitationEvent.get_station_precipitations","text":"Returns all the precipitations related to the given station index (column). Parameters: Name Type Description Default station_idx int Index of the column which values need to be retrieved. required Exceptions: Type Description ValueError If the station index does not exist. Returns: Type Description Tuple[datetime, List[float]] Tuple with the start time and its precipitations. Source code in hydrolib/core/rr/meteo/models.py def get_station_precipitations ( self , station_idx : int ) -> Tuple [ datetime , List [ float ]]: \"\"\" Returns all the precipitations related to the given station index (column). Args: station_idx (int): Index of the column which values need to be retrieved. Raises: ValueError: If the station index does not exist. Returns: Tuple[datetime, List[float]]: Tuple with the start time and its precipitations. \"\"\" number_of_stations = len ( self . precipitation_per_timestep [ 0 ]) if station_idx >= number_of_stations : raise ValueError ( \"Station index not found, number of stations: {} \" . format ( number_of_stations ) ) return ( self . start_time , [ ts_precipitations [ station_idx ] for ts_precipitations in self . precipitation_per_timestep ], )","title":"get_station_precipitations()"},{"location":"reference/rr/rr/#topology-layer-topography-in-sobek-um","text":"","title":"Topology layer (\"Topography\" in SOBEK UM)"},{"location":"reference/rr/rr/#hydrolib.core.rr.topology.models.Link","text":"Represents a link from the topology link file.","title":"Link"},{"location":"reference/rr/rr/#hydrolib.core.rr.topology.models.Link.dict","text":"Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/rr/topology/models.py def dict ( self , * args , ** kwargs ): kwargs [ \"by_alias\" ] = True return super () . dict ( * args , ** kwargs )","title":"dict()"},{"location":"reference/rr/rr/#hydrolib.core.rr.topology.models.LinkFile","text":"Represents the file with the RR link topology data.","title":"LinkFile"},{"location":"reference/rr/rr/#hydrolib.core.rr.topology.models.Node","text":"Represents a node from the topology node file.","title":"Node"},{"location":"reference/rr/rr/#hydrolib.core.rr.topology.models.Node.dict","text":"Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/rr/topology/models.py def dict ( self , * args , ** kwargs ): kwargs [ \"by_alias\" ] = True return super () . dict ( * args , ** kwargs )","title":"dict()"},{"location":"reference/rr/rr/#hydrolib.core.rr.topology.models.NodeFile","text":"Represents the file with the RR node topology data.","title":"NodeFile"},{"location":"reference/rr/rr/#hydrolib.core.rr.topology.models.nodetypes_netter_to_rr","text":"Dictionary with nt mapped against the expected mt . Some model types mt do not have a related netter type; in that case the dict key is a dummy value of - .","title":"nodetypes_netter_to_rr"},{"location":"reference/rr/rr/#other-input-layers-foreseen-in-future-releases","text":"","title":"(Other input layers foreseen in future releases)"},{"location":"topics/dhydro_support/","text":"List of D-HYDRO functionalities and support in HYDROLIB-core \u00b6 Below is a list of D-HYDRO functionalities, grouped by kernel, and the current status of support inside hydrolib-core. Symbology \u00b6 : All toplevel file contents can be read/written. : Partial support, see notes. : No support yet, but may come in future. : No support foreseen. Out of scope. * indicates a scheduled release that is not out yet. DIMR \u00b6 Functionality Read Write Supported since API ref Notes DIMR dimr_config.xml 0.2.0 DIMR Critical bugfix for #127 . FM component 0.1.1 FMComponent RR component 0.1.1 RRComponent RTC component parallel MPI models 0.1.1 Component coupler elements 0.1.1 Coupler FM \u00b6 Functionality Read Write Supported since API ref Notes FM MDU file 0.1.1 FMModel Network file _net.nc 0.1.1 Mesh2d Structure file 0.1.1 StructureModel * Weir 0.1.1 Weir * Universal weir 0.1.1 UniversalWeir * Culvert 0.1.1 Culvert * Long culvert * Bridge 0.1.5 Bridge * Pump 0.1.1 Pump * Orifice 0.1.1 Orifice * Gate * General structure 0.2.0 GeneralStructure * Dambreak 0.1.5 Dambreak * Compound structure 0.1.1 Compound External forcings file External forcings file (old) 0.5.0 ExtOldModel External forcings file (new) 0.1.1 ExtModel * Boundary 0.1.1 Boundary * Lateral 0.1.1 Lateral * Meteo 0.5.0 Meteo .bc file 0.1.1 ForcingModel * timeSeries 0.1.1 TimeSeries * harmonic (-Correction) 0.1.1 Harmonic * astronomic (-Correction) 0.1.1 Astronomic * t3D 0.3.1 T3D * QHTable 0.1.1 QHTable * constant 0.1.1 Constant * vector quantities 0.3.1 VectorQuantityUnitPairs .tim file 0.5.0 TimModel Cross section files Moved to io.crosssections in 0.2.0 Cross section definition file 0.1.1 CrossDefModel * Circle 0.1.5 CircleCrsDef * Rectangle 0.1.5 RectangleCrsDef * Tabulated river 0.1.5 ZWRiverCrsDef * ZW (tabulated) 0.1.5 ZWCrsDef * XYZ 0.1.5 XYZCrsDef * YZ 0.1.5 YZCrsDef Cross section location file 0.1.1 CrossLocModel 1D roughness file 0.2.0 FrictionModel Storage node file 0.2.0 StorageNodeModel Spatial data files Initial and parameter field file 0.2.0 IniFieldModel 1D field INI files 0.2.0 OneDFieldModel Sample file 0.1.1 XYZModel Output Observation station file (.xyn) 0.5.0 XYNModel Observation station file (.ini) 0.3.0 ObservationPointModel Observation crosssection file (.pli) 0.5.0 PolyFile Observation crosssection file (.ini) 0.3.1 ObservationCrossSectionModel History file _his.nc Map file (old) Map file (UGRID) _map.nc Fourier input file Fourier output file _fou.nc via map file reader Class map file via map file reader RR \u00b6 Functionality Read Write Supported since API ref Notes RR Main sobek_3b.fnm 0.1.5 RainfallRunoffModel Used to be in hydrolib.core.io.fnm.models before 0.3.0 Rainfall .bui file 0.1.5 BuiModel Used to be in hydrolib.core.io.bui.models before 0.3.0 Topology layer Node file 3b_node.tp 0.2.0 NodeFile Link file 3b_link.tp 0.2.0 LinkFile (Table source available on: https://github.com/Deltares/HYDROLIB-core/blob/main/docs/topics/dhydro_support_hydrolib-core.xlsx )","title":"List of D-HYDRO functionalities and support in HYDROLIB-core"},{"location":"topics/dhydro_support/#list-of-d-hydro-functionalities-and-support-in-hydrolib-core","text":"Below is a list of D-HYDRO functionalities, grouped by kernel, and the current status of support inside hydrolib-core.","title":"List of D-HYDRO functionalities and support in HYDROLIB-core"},{"location":"topics/dhydro_support/#symbology","text":": All toplevel file contents can be read/written. : Partial support, see notes. : No support yet, but may come in future. : No support foreseen. Out of scope. * indicates a scheduled release that is not out yet.","title":"Symbology"},{"location":"topics/dhydro_support/#dimr","text":"Functionality Read Write Supported since API ref Notes DIMR dimr_config.xml 0.2.0 DIMR Critical bugfix for #127 . FM component 0.1.1 FMComponent RR component 0.1.1 RRComponent RTC component parallel MPI models 0.1.1 Component coupler elements 0.1.1 Coupler","title":"DIMR"},{"location":"topics/dhydro_support/#fm","text":"Functionality Read Write Supported since API ref Notes FM MDU file 0.1.1 FMModel Network file _net.nc 0.1.1 Mesh2d Structure file 0.1.1 StructureModel * Weir 0.1.1 Weir * Universal weir 0.1.1 UniversalWeir * Culvert 0.1.1 Culvert * Long culvert * Bridge 0.1.5 Bridge * Pump 0.1.1 Pump * Orifice 0.1.1 Orifice * Gate * General structure 0.2.0 GeneralStructure * Dambreak 0.1.5 Dambreak * Compound structure 0.1.1 Compound External forcings file External forcings file (old) 0.5.0 ExtOldModel External forcings file (new) 0.1.1 ExtModel * Boundary 0.1.1 Boundary * Lateral 0.1.1 Lateral * Meteo 0.5.0 Meteo .bc file 0.1.1 ForcingModel * timeSeries 0.1.1 TimeSeries * harmonic (-Correction) 0.1.1 Harmonic * astronomic (-Correction) 0.1.1 Astronomic * t3D 0.3.1 T3D * QHTable 0.1.1 QHTable * constant 0.1.1 Constant * vector quantities 0.3.1 VectorQuantityUnitPairs .tim file 0.5.0 TimModel Cross section files Moved to io.crosssections in 0.2.0 Cross section definition file 0.1.1 CrossDefModel * Circle 0.1.5 CircleCrsDef * Rectangle 0.1.5 RectangleCrsDef * Tabulated river 0.1.5 ZWRiverCrsDef * ZW (tabulated) 0.1.5 ZWCrsDef * XYZ 0.1.5 XYZCrsDef * YZ 0.1.5 YZCrsDef Cross section location file 0.1.1 CrossLocModel 1D roughness file 0.2.0 FrictionModel Storage node file 0.2.0 StorageNodeModel Spatial data files Initial and parameter field file 0.2.0 IniFieldModel 1D field INI files 0.2.0 OneDFieldModel Sample file 0.1.1 XYZModel Output Observation station file (.xyn) 0.5.0 XYNModel Observation station file (.ini) 0.3.0 ObservationPointModel Observation crosssection file (.pli) 0.5.0 PolyFile Observation crosssection file (.ini) 0.3.1 ObservationCrossSectionModel History file _his.nc Map file (old) Map file (UGRID) _map.nc Fourier input file Fourier output file _fou.nc via map file reader Class map file via map file reader","title":"FM"},{"location":"topics/dhydro_support/#rr","text":"Functionality Read Write Supported since API ref Notes RR Main sobek_3b.fnm 0.1.5 RainfallRunoffModel Used to be in hydrolib.core.io.fnm.models before 0.3.0 Rainfall .bui file 0.1.5 BuiModel Used to be in hydrolib.core.io.bui.models before 0.3.0 Topology layer Node file 3b_node.tp 0.2.0 NodeFile Link file 3b_link.tp 0.2.0 LinkFile (Table source available on: https://github.com/Deltares/HYDROLIB-core/blob/main/docs/topics/dhydro_support_hydrolib-core.xlsx )","title":"RR"},{"location":"topics/loadsave/","text":"Loading and Saving within HYDROLIB-core \u00b6 This article describes the architectural choices of saving and loading, if you are looking for how to save, please refer to the tutorials. The motivation of HYDROLIB-core is to provide a python library to interact with the D-HYDRO suite files. These files generally form a sort of tree structure, with a single root model (generally a DIMR or an FM model), and different layers of child models which are referenced in their parent models. These child models can either be referenced relative to their parent models or with absolute file paths. This leads to potentially complex model structures, which need to be read and written correctly by HYDROLIB-core without any changes to either the contents or the structure. This article discusses the architectural choices made when designing the read and write capabalities, as well as the considerations that should be taken when implementing your own models. As such we will discuss the following topics: Motivation: HYDROLIB-core should not adjust files when reading and writing Structure of Models Loading Models: Resolving the tree structure with the FileLoadContext Saving Models: Traversing the model tree with the ModelTreeTraverser Extensions: Caveats to ensure your model plays nice with HYDROLIB-core Motivation: HYDROLIB-core should not adjust files when reading and writing \u00b6 When implementing the model read and write behaviour of HYDROLIB-core, the main design choice is to ensure models are read and written as is. Properties should not be adjusted nor dropped when reading or writing (unless there is a very clear reason to do so). This behaviour should extend to the way the tree structure of the models is handled. Therefor, file paths, stored in the filepath property, which are not explicitly set to be absolute are kept relative and resolved while reading or writing. This has the drawback that the file location of a child model is not explicitly defined without the root model it is part of. Within the current implementation, child models have no reference to their parent. This simplifies the bookkeeping when building models in memory, however it also means that it is not possible to resolve the absolute path of a child model without also providing the root model it is part of. This behaviour is further documented in the following sections. In order to alleviate this shortcoming, each file model internally keeps track of its resolved save location, which can be explicitly synchronized with the file path of the root model, if this is required. Loading Models: Resolving the tree structure with the FileLoadContext \u00b6 In order to load a model from disk, we need to call the appropriate constructor with a file path to an existing model file. The constructor will then ensure the model, and its child models are read. Multiple references to the same sub-model will reference the same sub-model after reading. Current Behaviour: Root models are read through the constructor while caching sub-models \u00b6 Currently, a model is loaded by calling the constructor with the filepath of the input file. HYDROLIB-core will then load the model as well as any children. Every child will only be read once, multiple references to the same child in the input files will result in references to the same child model in memory. When reading the model and its children, the file structure will be kept intact. Any models with absolute paths will still reference the same absolute paths, while models with relative paths will also have the same relative paths as within the original file. Architectural Choices: The tree structure is resolved with the FileLoadContext \u00b6 In order to properly resolve the model tree, we need to be able to keep track of the current parent of a model, as well as a way to store and retrieve read models. Both of these tasks are handled by the FileLoadContext . The context can be used to resolve relative paths by keeping track of the current parent folder of a model. It also provides a cache for read models, which ensures files are not read more than once. A single FileLoadContext is created at the start of the constructor of the root model as a context variable. Subsequent child models can then reference this FileLoadContext , by retrieving this same FileLoadContext . A convenience context manager is provided through the file_load_context() method in the basemodel.py . The constructor of the filepath performs the following tasks: Request the context. Register itself within the model cache with its file path. Store the absolute file path anchor (i.e. the absolute path to its parent) Resolve its absolute path, to read from. Update the current parent directory. Read all the model data including sub-models. Remove itself as a parent directory. Because the constructor recursively reads child models, and the data is only read after the current parent directory has been updated, the child models will correctly resolve their resolve their relative paths. The FileModel further overrides its __new__ . During the __new__ call, it will verify if the current (resolved) filepath which is being read, has already been defined in the file model cache. If it is, then this instance will be returned, instead of creating a new instance through the __init__ . This ensures no duplicates are created. Saving Models: Traversing the model tree with the ModelTreeTraverser \u00b6 Currently, the save function on the FileModel offers the following options: filepath : Allows the user to set a new file path. If none is defined, the current file path will be used. recurse : A flag indicating whether only this model needs to be saved, or also it child models. As such it is possible to store both individual models, as well as model trees. When saving a model, it will be stored at the save_location . If recurse is true, then the child model will be evaluated with regards to the root model. This may lead to some inconsistencies, especially with the deprecated pathsRelativeToParent set to false in the FlowFM model. As such care needs to be taken by the user. The save_location of relative child models will NOT be automatically updated when the parent filepath is updated. If such an update is required the user is expected to call synchronize_filepaths on the parent model. ModelTreeTraverser \u00b6 For writing the models to file, as well as other operations, we need to be able to traverse the model tree. In order to do so, the ModelTreeTraverser is provided. It can be configured with the following 4 functions: should_traverse : Evaluates whether to traverse to the provided BaseModel. should_execute : Determines whether the traverse functions are executed for the given model. pre_traverse_func : Function called with the current model before traversal into the children, i.e. top-down behaviour. post_traverse_func : Function called with the current model after traversal into the children, i.e. bottom-up behaviour. All functions receive an accumulator, which flows through the program and is finally returned to the caller. This can be used to store state in between calls to traverse or to build an output value while traversing the model tree. Saving a complete model tree \u00b6 In order to store a model as well as its children, we need to perform the following tasks. Ensure the file paths of both the model and all of its children are set. Save the the models and its children recursively. We need to ensure all file paths are set before we store the models, in order to resolve the actual file paths during the save operation. As such these two operations are done in separate steps. Both of these tasks make use of the ModelTreeTraverser . It will traverse through any immediate file link model, and execute the pre and post functions for any file link. In case of task 1, it will generate the file paths if none is set. The save traversal uses the pre and post traverse functions to maintain the parent path used to resolve the relative file paths of any models. The post function is further used to actually write the model to file through a dedicated _save function. Saving a sub-tree relative to some model tree \u00b6 Saving a sub tree is in principle the same as calling save on the root model, but only a child model. One thing that should be taken into account is, the save is called relative to the current value in save_location . As such if changes were made to the filepath of a parent model, synchronize_filepaths should be called on the root model. Saving individual models without their children \u00b6 An individual model can be saved with the save and recurse set to False (i.e. the default behaviour). When this is done, only the model on which save was called will be written to disk at the current save_location . Exporting / Save as \u00b6 Exporting is currently not implemented, but will be as part of issue #170 . Inheritance hierachy of FileModels: SerializableFileModels and DiskOnlyFileModels \u00b6 The FileModel is the abstract base class for any file model. It provides the logic to manage the file paths as well as the common logic to load and save models. In order to do so, it requires child classes to implement a _save and a _load method. Two child classes have been defined which extend the FileModel : ParsableFileModel : Abstract class which defines a FileModel with a serializer and parser. This is the base model used by most in-memory models. DiskOnlyFileModel : A generic file model which does not read data into memory but does copy the underlying file when a parent FileModel is saved recursively. ParsableFileModel \u00b6 The ParsableFileModel defines an abstract base class for in-memory models, it does so by requiring child classes to define a parser, to read input files, and a serializer, to write the data again. This forms the basis for most of the in-memory file models. DiskOnlyFileModel \u00b6 The DiskOnlyFileModel provides a file model implementation for files which do not have a representation in HYDROLIB.Core (yet). The DiskOnlyFileModel ensures the underlying file, specified with the filepath of the FileModel , is copied when a parent model is saved recursively. It does so by maintaining an internal source file path, which is initialized at construction of the DiskOnlyFileModel . When a DiskOnlyFileModel is saved, the underlying file is copied from this internal source file path to the new target path. If the file at the source file model does not exist, or the target path is invalid, no file is copied. Lastly, regardless of whether a file was copied, the internal source file path is updated. Extensions: Caveats to ensure your model plays nice with HYDROLIB-core \u00b6 In the most common case, all of the file reading and writing is handled in the FileModel as such, just inheriting from the FileModel and providing the required parser and setting the _parser and _serializer will be enough to ensure your model works as expected. There might be however some exceptions to your model that require additional configuration. The file model provides several hooks for this: For loading: _post_init_load : function called after a model is initialised but before the current FileLoadContext is changed. This allows the user to put any actions here which require a FileLoadContext . Examples of this can be found in the DIMR and NetworkModel classes. Overwrite __init__ : We can overwrite the __init__ of a child the FileModel however some care needs to be taken in this case. In particular the __super__ needs to be called in order to ensure the model is loaded appropriately. Furthermore, if the FileLoadContext is required within the __init__ , the file_load_context should be called before __super__ : def __init__ ( self , ... ): with file_load_context () as context : __super__ () . __init__ () ... # your code using the context ... For saving: _save : provides the save functionality called by the recursive saving of models. Overwriting this will allow you complete control over how the model is saved. An example of this can be found in the NetworkFile . _serialize : provides the method to serialize your model. This can be overwritten in case a more specialised serialization is required, for example as done in IniBasedModel children. self._resolved_filepath : will provide you with a resolved absolute version of the filepath . This only works in the context of _save and _serialize , as it relies on the context being started in the save method.","title":"Loading and Saving within HYDROLIB-core"},{"location":"topics/loadsave/#loading-and-saving-within-hydrolib-core","text":"This article describes the architectural choices of saving and loading, if you are looking for how to save, please refer to the tutorials. The motivation of HYDROLIB-core is to provide a python library to interact with the D-HYDRO suite files. These files generally form a sort of tree structure, with a single root model (generally a DIMR or an FM model), and different layers of child models which are referenced in their parent models. These child models can either be referenced relative to their parent models or with absolute file paths. This leads to potentially complex model structures, which need to be read and written correctly by HYDROLIB-core without any changes to either the contents or the structure. This article discusses the architectural choices made when designing the read and write capabalities, as well as the considerations that should be taken when implementing your own models. As such we will discuss the following topics: Motivation: HYDROLIB-core should not adjust files when reading and writing Structure of Models Loading Models: Resolving the tree structure with the FileLoadContext Saving Models: Traversing the model tree with the ModelTreeTraverser Extensions: Caveats to ensure your model plays nice with HYDROLIB-core","title":"Loading and Saving within HYDROLIB-core"},{"location":"topics/loadsave/#motivation-hydrolib-core-should-not-adjust-files-when-reading-and-writing","text":"When implementing the model read and write behaviour of HYDROLIB-core, the main design choice is to ensure models are read and written as is. Properties should not be adjusted nor dropped when reading or writing (unless there is a very clear reason to do so). This behaviour should extend to the way the tree structure of the models is handled. Therefor, file paths, stored in the filepath property, which are not explicitly set to be absolute are kept relative and resolved while reading or writing. This has the drawback that the file location of a child model is not explicitly defined without the root model it is part of. Within the current implementation, child models have no reference to their parent. This simplifies the bookkeeping when building models in memory, however it also means that it is not possible to resolve the absolute path of a child model without also providing the root model it is part of. This behaviour is further documented in the following sections. In order to alleviate this shortcoming, each file model internally keeps track of its resolved save location, which can be explicitly synchronized with the file path of the root model, if this is required.","title":"Motivation: HYDROLIB-core should not adjust files when reading and writing"},{"location":"topics/loadsave/#loading-models-resolving-the-tree-structure-with-the-fileloadcontext","text":"In order to load a model from disk, we need to call the appropriate constructor with a file path to an existing model file. The constructor will then ensure the model, and its child models are read. Multiple references to the same sub-model will reference the same sub-model after reading.","title":"Loading Models: Resolving the tree structure with the FileLoadContext"},{"location":"topics/loadsave/#current-behaviour-root-models-are-read-through-the-constructor-while-caching-sub-models","text":"Currently, a model is loaded by calling the constructor with the filepath of the input file. HYDROLIB-core will then load the model as well as any children. Every child will only be read once, multiple references to the same child in the input files will result in references to the same child model in memory. When reading the model and its children, the file structure will be kept intact. Any models with absolute paths will still reference the same absolute paths, while models with relative paths will also have the same relative paths as within the original file.","title":"Current Behaviour: Root models are read through the constructor while caching sub-models"},{"location":"topics/loadsave/#architectural-choices-the-tree-structure-is-resolved-with-the-fileloadcontext","text":"In order to properly resolve the model tree, we need to be able to keep track of the current parent of a model, as well as a way to store and retrieve read models. Both of these tasks are handled by the FileLoadContext . The context can be used to resolve relative paths by keeping track of the current parent folder of a model. It also provides a cache for read models, which ensures files are not read more than once. A single FileLoadContext is created at the start of the constructor of the root model as a context variable. Subsequent child models can then reference this FileLoadContext , by retrieving this same FileLoadContext . A convenience context manager is provided through the file_load_context() method in the basemodel.py . The constructor of the filepath performs the following tasks: Request the context. Register itself within the model cache with its file path. Store the absolute file path anchor (i.e. the absolute path to its parent) Resolve its absolute path, to read from. Update the current parent directory. Read all the model data including sub-models. Remove itself as a parent directory. Because the constructor recursively reads child models, and the data is only read after the current parent directory has been updated, the child models will correctly resolve their resolve their relative paths. The FileModel further overrides its __new__ . During the __new__ call, it will verify if the current (resolved) filepath which is being read, has already been defined in the file model cache. If it is, then this instance will be returned, instead of creating a new instance through the __init__ . This ensures no duplicates are created.","title":"Architectural Choices: The tree structure is resolved with the FileLoadContext"},{"location":"topics/loadsave/#saving-models-traversing-the-model-tree-with-the-modeltreetraverser","text":"Currently, the save function on the FileModel offers the following options: filepath : Allows the user to set a new file path. If none is defined, the current file path will be used. recurse : A flag indicating whether only this model needs to be saved, or also it child models. As such it is possible to store both individual models, as well as model trees. When saving a model, it will be stored at the save_location . If recurse is true, then the child model will be evaluated with regards to the root model. This may lead to some inconsistencies, especially with the deprecated pathsRelativeToParent set to false in the FlowFM model. As such care needs to be taken by the user. The save_location of relative child models will NOT be automatically updated when the parent filepath is updated. If such an update is required the user is expected to call synchronize_filepaths on the parent model.","title":"Saving Models: Traversing the model tree with the ModelTreeTraverser"},{"location":"topics/loadsave/#modeltreetraverser","text":"For writing the models to file, as well as other operations, we need to be able to traverse the model tree. In order to do so, the ModelTreeTraverser is provided. It can be configured with the following 4 functions: should_traverse : Evaluates whether to traverse to the provided BaseModel. should_execute : Determines whether the traverse functions are executed for the given model. pre_traverse_func : Function called with the current model before traversal into the children, i.e. top-down behaviour. post_traverse_func : Function called with the current model after traversal into the children, i.e. bottom-up behaviour. All functions receive an accumulator, which flows through the program and is finally returned to the caller. This can be used to store state in between calls to traverse or to build an output value while traversing the model tree.","title":"ModelTreeTraverser"},{"location":"topics/loadsave/#saving-a-complete-model-tree","text":"In order to store a model as well as its children, we need to perform the following tasks. Ensure the file paths of both the model and all of its children are set. Save the the models and its children recursively. We need to ensure all file paths are set before we store the models, in order to resolve the actual file paths during the save operation. As such these two operations are done in separate steps. Both of these tasks make use of the ModelTreeTraverser . It will traverse through any immediate file link model, and execute the pre and post functions for any file link. In case of task 1, it will generate the file paths if none is set. The save traversal uses the pre and post traverse functions to maintain the parent path used to resolve the relative file paths of any models. The post function is further used to actually write the model to file through a dedicated _save function.","title":"Saving a complete model tree"},{"location":"topics/loadsave/#saving-a-sub-tree-relative-to-some-model-tree","text":"Saving a sub tree is in principle the same as calling save on the root model, but only a child model. One thing that should be taken into account is, the save is called relative to the current value in save_location . As such if changes were made to the filepath of a parent model, synchronize_filepaths should be called on the root model.","title":"Saving a sub-tree relative to some model tree"},{"location":"topics/loadsave/#saving-individual-models-without-their-children","text":"An individual model can be saved with the save and recurse set to False (i.e. the default behaviour). When this is done, only the model on which save was called will be written to disk at the current save_location .","title":"Saving individual models without their children"},{"location":"topics/loadsave/#exporting-save-as","text":"Exporting is currently not implemented, but will be as part of issue #170 .","title":"Exporting / Save as"},{"location":"topics/loadsave/#inheritance-hierachy-of-filemodels-serializablefilemodels-and-diskonlyfilemodels","text":"The FileModel is the abstract base class for any file model. It provides the logic to manage the file paths as well as the common logic to load and save models. In order to do so, it requires child classes to implement a _save and a _load method. Two child classes have been defined which extend the FileModel : ParsableFileModel : Abstract class which defines a FileModel with a serializer and parser. This is the base model used by most in-memory models. DiskOnlyFileModel : A generic file model which does not read data into memory but does copy the underlying file when a parent FileModel is saved recursively.","title":"Inheritance hierachy of FileModels: SerializableFileModels and DiskOnlyFileModels"},{"location":"topics/loadsave/#parsablefilemodel","text":"The ParsableFileModel defines an abstract base class for in-memory models, it does so by requiring child classes to define a parser, to read input files, and a serializer, to write the data again. This forms the basis for most of the in-memory file models.","title":"ParsableFileModel"},{"location":"topics/loadsave/#diskonlyfilemodel","text":"The DiskOnlyFileModel provides a file model implementation for files which do not have a representation in HYDROLIB.Core (yet). The DiskOnlyFileModel ensures the underlying file, specified with the filepath of the FileModel , is copied when a parent model is saved recursively. It does so by maintaining an internal source file path, which is initialized at construction of the DiskOnlyFileModel . When a DiskOnlyFileModel is saved, the underlying file is copied from this internal source file path to the new target path. If the file at the source file model does not exist, or the target path is invalid, no file is copied. Lastly, regardless of whether a file was copied, the internal source file path is updated.","title":"DiskOnlyFileModel"},{"location":"topics/loadsave/#extensions-caveats-to-ensure-your-model-plays-nice-with-hydrolib-core","text":"In the most common case, all of the file reading and writing is handled in the FileModel as such, just inheriting from the FileModel and providing the required parser and setting the _parser and _serializer will be enough to ensure your model works as expected. There might be however some exceptions to your model that require additional configuration. The file model provides several hooks for this: For loading: _post_init_load : function called after a model is initialised but before the current FileLoadContext is changed. This allows the user to put any actions here which require a FileLoadContext . Examples of this can be found in the DIMR and NetworkModel classes. Overwrite __init__ : We can overwrite the __init__ of a child the FileModel however some care needs to be taken in this case. In particular the __super__ needs to be called in order to ensure the model is loaded appropriately. Furthermore, if the FileLoadContext is required within the __init__ , the file_load_context should be called before __super__ : def __init__ ( self , ... ): with file_load_context () as context : __super__ () . __init__ () ... # your code using the context ... For saving: _save : provides the save functionality called by the recursive saving of models. Overwriting this will allow you complete control over how the model is saved. An example of this can be found in the NetworkFile . _serialize : provides the method to serialize your model. This can be overwritten in case a more specialised serialization is required, for example as done in IniBasedModel children. self._resolved_filepath : will provide you with a resolved absolute version of the filepath . This only works in the context of _save and _serialize , as it relies on the context being started in the save method.","title":"Extensions: Caveats to ensure your model plays nice with HYDROLIB-core"},{"location":"topics/principles/","text":"First principles \u00b6 hydrolib-core is structured around the input and output files (I/O) of the DHYDRO suite. Inheritance/file handling \u00b6 Model setups often consist of different files, many implicitly linked to each other. HYDROLIB makes these links explicit, by recursively loading all child configuration files. For example, when parsing a DIMR file, one could happen upon a reference to an MDU file, which contain references to other files, such as cross sections, etc. >>> dimr = DIMR ( filepath = Path ( test_data_dir / \"dimr_config.xml\" )) You can see this tree structure if you call show_tree . >>> dimr . show_tree () DIMR represented by dimr_config . xml . RRComponent FMComponent \u221f FMModel represented by FlowFM . mdu . \u221f Geometry \u221f StructureModel represented by structures . ini . \u221f CrossDefModel represented by crsdef . ini . \u221f CrossLocModel represented by crsloc . ini . \u221f FrictionModel represented by roughness - Main . ini . \u221f FrictionModel represented by roughness - Sewer1 . ini . \u221f FrictionModel represented by roughness - Sewer2 . ini . \u221f ExternalForcing \u221f ExtModel represented by FlowFM_bnd . ext . \u221f Boundary \u221f ForcingModel represented by FlowFM_boundaryconditions1d . bc . \u221f Boundary \u221f ForcingModel represented by FlowFM_boundaryconditions1d . bc . \u221f Boundary \u221f ForcingModel represented by FlowFM_boundaryconditions1d . bc . Program flow while recursively creating FileModels \u00b6 In short: \u00b6 The file resolver and the model cache are stored in context variable context_file_loading , such that referenced files can be found. During loading, the parsed data from files are cached in the FileLoadContext to ensure multiple references to the same model will not result in duplicate parsing and instances. Pydantic first calls the FileModel.validate and then the initializer ( FileModel.__new__ and FileModel.__init__ ). In detail: \u00b6 User initializes a new root FileModel from file : FileModel.__new__(cls, filepath: str/Path) Returns the result of the default __new__ function FileModel.__init__(self, filepath: str/Path) self holds the FileModel instance that was returned in step 1. filepath is holds the file path to the root file. Registers this model in the FileLoadContext with the file path. Resolves the absolute path to this model. Adds the folder of this model to the file resolver, such that the children can be resolved as well. Loads the data ( dict ) from the file. Initialize self with the data. Pydantic tries to convert the data to objects, a.o. sub FileModels : FileModel.validate(value: str) value holds a relative or absolute file path to the referenced file. If value is not an absolute file path, resolves the absolute path by using the FileLoadContext stored in the context_file_loading , previously set in step 2. Calls super().validate(value) with the file path stored in value . Pydantic create a new FileModel with the data : FileModel.__new__(cls, filepath: str) filepath holds the file path. If FileModel._file_models_cache already contains a FileModel instance with this filepath , returns the cached instance, Otherwise, returns the result of the default __new__ function. Repeat steps 2-4 Parsing and serializing INIBasedModels \u00b6 Parsing an INI file should be case-insensitive. To achieve this, the parsable field names of each INIBasedModel should be equal to the expected key in the file in lower case. Some property values are explicitly made case-insensitive for parsing as well. This applies to enum values and values that represent a specific type of INIBasedModel , such as the type property of a structure. To support this, custom validators are placed to compare the given value with the available known values. Structures are initialized based on the value in the type field. The value of this field of each subclass of a Structure is compared to the input and the subclass with the corresponding type is initialized. The serialization of an INIBasedModel to an INI file should respect certain casing rules (overriding the casing used by the user): - Property keys need to be \"lowerCamelCase\" - Section headers need to be \"UpperCamelCase\" To achieve this, each serializable field in a INIBasedModel has an alias. This alias will be written as property key to file. Each INIBasedModel that represents an INI section, has a field _header . The default value of this field will be written to file. Enum values and the values that represent a specific type of INIBasedModel will be serialized to file by how they are defined.","title":"First principles"},{"location":"topics/principles/#first-principles","text":"hydrolib-core is structured around the input and output files (I/O) of the DHYDRO suite.","title":"First principles"},{"location":"topics/principles/#inheritancefile-handling","text":"Model setups often consist of different files, many implicitly linked to each other. HYDROLIB makes these links explicit, by recursively loading all child configuration files. For example, when parsing a DIMR file, one could happen upon a reference to an MDU file, which contain references to other files, such as cross sections, etc. >>> dimr = DIMR ( filepath = Path ( test_data_dir / \"dimr_config.xml\" )) You can see this tree structure if you call show_tree . >>> dimr . show_tree () DIMR represented by dimr_config . xml . RRComponent FMComponent \u221f FMModel represented by FlowFM . mdu . \u221f Geometry \u221f StructureModel represented by structures . ini . \u221f CrossDefModel represented by crsdef . ini . \u221f CrossLocModel represented by crsloc . ini . \u221f FrictionModel represented by roughness - Main . ini . \u221f FrictionModel represented by roughness - Sewer1 . ini . \u221f FrictionModel represented by roughness - Sewer2 . ini . \u221f ExternalForcing \u221f ExtModel represented by FlowFM_bnd . ext . \u221f Boundary \u221f ForcingModel represented by FlowFM_boundaryconditions1d . bc . \u221f Boundary \u221f ForcingModel represented by FlowFM_boundaryconditions1d . bc . \u221f Boundary \u221f ForcingModel represented by FlowFM_boundaryconditions1d . bc .","title":"Inheritance/file handling"},{"location":"topics/principles/#program-flow-while-recursively-creating-filemodels","text":"","title":"Program flow while recursively creating FileModels"},{"location":"topics/principles/#in-short","text":"The file resolver and the model cache are stored in context variable context_file_loading , such that referenced files can be found. During loading, the parsed data from files are cached in the FileLoadContext to ensure multiple references to the same model will not result in duplicate parsing and instances. Pydantic first calls the FileModel.validate and then the initializer ( FileModel.__new__ and FileModel.__init__ ).","title":"In short:"},{"location":"topics/principles/#in-detail","text":"User initializes a new root FileModel from file : FileModel.__new__(cls, filepath: str/Path) Returns the result of the default __new__ function FileModel.__init__(self, filepath: str/Path) self holds the FileModel instance that was returned in step 1. filepath is holds the file path to the root file. Registers this model in the FileLoadContext with the file path. Resolves the absolute path to this model. Adds the folder of this model to the file resolver, such that the children can be resolved as well. Loads the data ( dict ) from the file. Initialize self with the data. Pydantic tries to convert the data to objects, a.o. sub FileModels : FileModel.validate(value: str) value holds a relative or absolute file path to the referenced file. If value is not an absolute file path, resolves the absolute path by using the FileLoadContext stored in the context_file_loading , previously set in step 2. Calls super().validate(value) with the file path stored in value . Pydantic create a new FileModel with the data : FileModel.__new__(cls, filepath: str) filepath holds the file path. If FileModel._file_models_cache already contains a FileModel instance with this filepath , returns the cached instance, Otherwise, returns the result of the default __new__ function. Repeat steps 2-4","title":"In detail:"},{"location":"topics/principles/#parsing-and-serializing-inibasedmodels","text":"Parsing an INI file should be case-insensitive. To achieve this, the parsable field names of each INIBasedModel should be equal to the expected key in the file in lower case. Some property values are explicitly made case-insensitive for parsing as well. This applies to enum values and values that represent a specific type of INIBasedModel , such as the type property of a structure. To support this, custom validators are placed to compare the given value with the available known values. Structures are initialized based on the value in the type field. The value of this field of each subclass of a Structure is compared to the input and the subclass with the corresponding type is initialized. The serialization of an INIBasedModel to an INI file should respect certain casing rules (overriding the casing used by the user): - Property keys need to be \"lowerCamelCase\" - Section headers need to be \"UpperCamelCase\" To achieve this, each serializable field in a INIBasedModel has an alias. This alias will be written as property key to file. Each INIBasedModel that represents an INI section, has a field _header . The default value of this field will be written to file. Enum values and the values that represent a specific type of INIBasedModel will be serialized to file by how they are defined.","title":"Parsing and serializing INIBasedModels"},{"location":"topics/pydantic/","text":"Pydantic \u00b6 Pydantic override \u00b6 We love using Pydantic , but we need have multiple overrides in place to enable specific functionality. This document tries to document these instances, as they are in essence exceptions to an otherwise well understood and documented architecture. BaseModel __init__ override \u00b6 We override de __init__ method to catch all validation errors and reissue them with an better error message. FileModel override \u00b6 We override both __new__ and __init__ of the FileModel to cache models from disk. The FileModel utilises the FileLoadContext to resolve relative paths and to retrieve models previously read as part of the loading of a root model. Specifically we also use it to load a filepath from disk. This mostly happens in validate , a Pydantic override, to make sure that if we initialize with a single unnamed argument (Pydantic only accepts keyword arguments) we try to parse it as a filepath. ForcingBase, Structure and CrossSectionDefinition validate override \u00b6 Validate is overriden to try to initialize the correct subclass of ForcingBase and CrossSectionDefinition, as discriminated unions do not work yet in Pydantic. I.e. if you specify Union{A, B} and A and B have clearly defined Literals it still can't choose whether to create A or B. The PR to fix this hasn't been merged yet. The code is duplicated in three places. INIBasedModel validate override \u00b6 In INIBasedModel we override validate to make sure we can flatten any Section input coming from the parser. Couldn't this be done in the parser? Structure Root validator explicitely checks subclass \u00b6 Because the validation behaviour is different for Compound , Dambreak etc. We might want to split these things once a new Pydantic release has been made that allows a root_validator to be overriden.","title":"Pydantic"},{"location":"topics/pydantic/#pydantic","text":"","title":"Pydantic"},{"location":"topics/pydantic/#pydantic-override","text":"We love using Pydantic , but we need have multiple overrides in place to enable specific functionality. This document tries to document these instances, as they are in essence exceptions to an otherwise well understood and documented architecture.","title":"Pydantic override"},{"location":"topics/pydantic/#basemodel-__init__-override","text":"We override de __init__ method to catch all validation errors and reissue them with an better error message.","title":"BaseModel __init__ override"},{"location":"topics/pydantic/#filemodel-override","text":"We override both __new__ and __init__ of the FileModel to cache models from disk. The FileModel utilises the FileLoadContext to resolve relative paths and to retrieve models previously read as part of the loading of a root model. Specifically we also use it to load a filepath from disk. This mostly happens in validate , a Pydantic override, to make sure that if we initialize with a single unnamed argument (Pydantic only accepts keyword arguments) we try to parse it as a filepath.","title":"FileModel override"},{"location":"topics/pydantic/#forcingbase-structure-and-crosssectiondefinition-validate-override","text":"Validate is overriden to try to initialize the correct subclass of ForcingBase and CrossSectionDefinition, as discriminated unions do not work yet in Pydantic. I.e. if you specify Union{A, B} and A and B have clearly defined Literals it still can't choose whether to create A or B. The PR to fix this hasn't been merged yet. The code is duplicated in three places.","title":"ForcingBase, Structure and CrossSectionDefinition validate override"},{"location":"topics/pydantic/#inibasedmodel-validate-override","text":"In INIBasedModel we override validate to make sure we can flatten any Section input coming from the parser. Couldn't this be done in the parser?","title":"INIBasedModel validate override"},{"location":"topics/pydantic/#structure-root-validator-explicitely-checks-subclass","text":"Because the validation behaviour is different for Compound , Dambreak etc. We might want to split these things once a new Pydantic release has been made that allows a root_validator to be overriden.","title":"Structure Root validator explicitely checks subclass"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/","text":"(function (global, factory) { typeof exports === 'object' && typeof module !== 'undefined' ? module.exports = factory() : typeof define === 'function' && define.amd ? define(factory) : (global = global || self, global.ClipboardCopyElement = factory()); }(this, function () { 'use strict'; function createNode(text) { const node = document.createElement('pre'); node.style.width = '1px'; node.style.height = '1px'; node.style.position = 'fixed'; node.style.top = '5px'; node.textContent = text; 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When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(0, 0, 0, 1); --jp-ui-font-color1: rgba(0, 0, 0, 0.87); --jp-ui-font-color2: rgba(0, 0, 0, 0.54); --jp-ui-font-color3: rgba(0, 0, 0, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color1: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color2: rgba(255, 255, 255, 0.7); --jp-ui-inverse-font-color3: rgba(255, 255, 255, 0.5); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(0, 0, 0, 1); --jp-content-font-color1: rgba(0, 0, 0, 0.87); --jp-content-font-color2: rgba(0, 0, 0, 0.54); --jp-content-font-color3: rgba(0, 0, 0, 0.38); --jp-content-link-color: var(--md-blue-700); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: white; --jp-layout-color1: white; --jp-layout-color2: var(--md-grey-200); --jp-layout-color3: var(--md-grey-400); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: #111111; --jp-inverse-layout-color1: var(--md-grey-900); --jp-inverse-layout-color2: var(--md-grey-800); --jp-inverse-layout-color3: var(--md-grey-700); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-900); --jp-brand-color1: var(--md-blue-700); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-900); --jp-accent-color1: var(--md-green-700); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-900); --jp-warn-color1: var(--md-orange-700); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-900); --jp-error-color1: var(--md-red-700); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-900); --jp-success-color1: var(--md-green-700); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-900); --jp-info-color1: var(--md-cyan-700); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--md-grey-100); --jp-cell-editor-border-color: var(--md-grey-300); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 0.5; --jp-cell-prompt-not-active-font-color: var(--md-grey-700); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: var(--md-blue-50); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: #fdd; --jp-rendermime-table-row-background: var(--md-grey-100); --jp-rendermime-table-row-hover-background: var(--md-light-blue-50); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.25); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color1); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.24); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--md-grey-300); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color1); --jp-input-hover-background: var(--jp-layout-color1); --jp-input-background: var(--md-grey-100); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: #d9d9d9; --jp-editor-selected-focused-background: #d7d4f0; --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: #008000; --jp-mirror-editor-atom-color: #88f; --jp-mirror-editor-number-color: #080; --jp-mirror-editor-def-color: #00f; --jp-mirror-editor-variable-color: var(--md-grey-900); --jp-mirror-editor-variable-2-color: #05a; --jp-mirror-editor-variable-3-color: #085; --jp-mirror-editor-punctuation-color: #05a; --jp-mirror-editor-property-color: #05a; --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ba2121; --jp-mirror-editor-string-2-color: #708; --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: #008000; --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: #170; --jp-mirror-editor-attribute-color: #00c; --jp-mirror-editor-header-color: blue; --jp-mirror-editor-quote-color: #090; --jp-mirror-editor-link-color: #00c; --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: white; /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.5; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(245, 200, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } [data-md-color-scheme=\"slate\"] .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ /* The dark theme shadows need a bit of work, but this will probably also require work on the core layout * colors used in the theme as well. */ --jp-shadow-base-lightness: 32; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-700); --jp-border-color1: var(--md-grey-700); --jp-border-color2: var(--md-grey-800); --jp-border-color3: var(--md-grey-900); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(255, 255, 255, 1); --jp-ui-font-color1: rgba(255, 255, 255, 0.87); --jp-ui-font-color2: rgba(255, 255, 255, 0.54); --jp-ui-font-color3: rgba(255, 255, 255, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(0, 0, 0, 1); --jp-ui-inverse-font-color1: rgba(0, 0, 0, 0.8); --jp-ui-inverse-font-color2: rgba(0, 0, 0, 0.5); --jp-ui-inverse-font-color3: rgba(0, 0, 0, 0.3); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(255, 255, 255, 1); --jp-content-font-color1: rgba(255, 255, 255, 1); --jp-content-font-color2: rgba(255, 255, 255, 0.7); --jp-content-font-color3: rgba(255, 255, 255, 0.5); --jp-content-link-color: var(--md-blue-300); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: #111111; --jp-layout-color1: var(--md-grey-900); --jp-layout-color2: var(--md-grey-800); --jp-layout-color3: var(--md-grey-700); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: white; --jp-inverse-layout-color1: white; --jp-inverse-layout-color2: var(--md-grey-200); --jp-inverse-layout-color3: var(--md-grey-400); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-700); --jp-brand-color1: var(--md-blue-500); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-700); --jp-accent-color1: var(--md-green-500); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-700); --jp-warn-color1: var(--md-orange-500); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-700); --jp-error-color1: var(--md-red-500); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-700); --jp-success-color1: var(--md-green-500); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-700); --jp-info-color1: var(--md-cyan-500); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--jp-layout-color1); --jp-cell-editor-border-color: var(--md-grey-700); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 1; --jp-cell-prompt-not-active-font-color: var(--md-grey-300); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: rgba(33, 150, 243, 0.24); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: rgba(244, 67, 54, 0.28); --jp-rendermime-table-row-background: var(--md-grey-900); --jp-rendermime-table-row-hover-background: rgba(3, 169, 244, 0.2); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.6); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color2); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.8); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--jp-layout-color0); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color0); --jp-input-hover-background: var(--jp-layout-color2); --jp-input-background: var(--md-grey-800); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: var(--jp-layout-color2); --jp-editor-selected-focused-background: rgba(33, 150, 243, 0.24); --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: var(--md-green-500); --jp-mirror-editor-atom-color: var(--md-blue-300); --jp-mirror-editor-number-color: var(--md-green-400); --jp-mirror-editor-def-color: var(--md-blue-600); --jp-mirror-editor-variable-color: var(--md-grey-300); --jp-mirror-editor-variable-2-color: var(--md-blue-400); --jp-mirror-editor-variable-3-color: var(--md-green-600); --jp-mirror-editor-punctuation-color: var(--md-blue-400); --jp-mirror-editor-property-color: var(--md-blue-400); --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ff7070; --jp-mirror-editor-string-2-color: var(--md-purple-300); --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: var(--md-green-600); --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: var(--md-green-700); --jp-mirror-editor-attribute-color: var(--md-blue-700); --jp-mirror-editor-header-color: var(--md-blue-500); --jp-mirror-editor-quote-color: var(--md-green-300); --jp-mirror-editor-link-color: var(--md-blue-700); --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: var(--md-grey-400); /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.6; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(255, 225, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* scrollbar related styles. Supports every browser except Edge. */ /* colors based on JetBrain's Darcula theme */ --jp-scrollbar-background-color: #3f4244; --jp-scrollbar-thumb-color: 88, 96, 97; /* need to specify thumb color as an RGB triplet */ --jp-scrollbar-endpad: 3px; /* the minimum gap between the thumb and the ends of a scrollbar */ /* hacks for setting the thumb shape. These do nothing in Firefox */ --jp-scrollbar-thumb-margin: 3.5px; /* the space in between the sides of the thumb and the track */ --jp-scrollbar-thumb-radius: 9px; /* set to a large-ish value for rounded endcaps on the thumb */ /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } :root{--md-red-50: #ffebee;--md-red-100: #ffcdd2;--md-red-200: #ef9a9a;--md-red-300: #e57373;--md-red-400: #ef5350;--md-red-500: #f44336;--md-red-600: #e53935;--md-red-700: #d32f2f;--md-red-800: #c62828;--md-red-900: #b71c1c;--md-red-A100: #ff8a80;--md-red-A200: #ff5252;--md-red-A400: #ff1744;--md-red-A700: #d50000;--md-pink-50: #fce4ec;--md-pink-100: #f8bbd0;--md-pink-200: #f48fb1;--md-pink-300: #f06292;--md-pink-400: #ec407a;--md-pink-500: #e91e63;--md-pink-600: #d81b60;--md-pink-700: #c2185b;--md-pink-800: 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#7986cb;--md-indigo-400: #5c6bc0;--md-indigo-500: #3f51b5;--md-indigo-600: #3949ab;--md-indigo-700: #303f9f;--md-indigo-800: #283593;--md-indigo-900: #1a237e;--md-indigo-A100: #8c9eff;--md-indigo-A200: #536dfe;--md-indigo-A400: #3d5afe;--md-indigo-A700: #304ffe;--md-blue-50: #e3f2fd;--md-blue-100: #bbdefb;--md-blue-200: #90caf9;--md-blue-300: #64b5f6;--md-blue-400: #42a5f5;--md-blue-500: #2196f3;--md-blue-600: #1e88e5;--md-blue-700: #1976d2;--md-blue-800: #1565c0;--md-blue-900: #0d47a1;--md-blue-A100: #82b1ff;--md-blue-A200: #448aff;--md-blue-A400: #2979ff;--md-blue-A700: #2962ff;--md-light-blue-50: #e1f5fe;--md-light-blue-100: #b3e5fc;--md-light-blue-200: #81d4fa;--md-light-blue-300: #4fc3f7;--md-light-blue-400: #29b6f6;--md-light-blue-500: #03a9f4;--md-light-blue-600: #039be5;--md-light-blue-700: #0288d1;--md-light-blue-800: #0277bd;--md-light-blue-900: #01579b;--md-light-blue-A100: #80d8ff;--md-light-blue-A200: #40c4ff;--md-light-blue-A400: #00b0ff;--md-light-blue-A700: #0091ea;--md-cyan-50: #e0f7fa;--md-cyan-100: #b2ebf2;--md-cyan-200: #80deea;--md-cyan-300: #4dd0e1;--md-cyan-400: #26c6da;--md-cyan-500: #00bcd4;--md-cyan-600: #00acc1;--md-cyan-700: #0097a7;--md-cyan-800: #00838f;--md-cyan-900: #006064;--md-cyan-A100: #84ffff;--md-cyan-A200: #18ffff;--md-cyan-A400: #00e5ff;--md-cyan-A700: #00b8d4;--md-teal-50: #e0f2f1;--md-teal-100: #b2dfdb;--md-teal-200: #80cbc4;--md-teal-300: #4db6ac;--md-teal-400: #26a69a;--md-teal-500: #009688;--md-teal-600: #00897b;--md-teal-700: #00796b;--md-teal-800: #00695c;--md-teal-900: #004d40;--md-teal-A100: #a7ffeb;--md-teal-A200: #64ffda;--md-teal-A400: #1de9b6;--md-teal-A700: #00bfa5;--md-green-50: #e8f5e9;--md-green-100: #c8e6c9;--md-green-200: #a5d6a7;--md-green-300: #81c784;--md-green-400: #66bb6a;--md-green-500: #4caf50;--md-green-600: #43a047;--md-green-700: #388e3c;--md-green-800: #2e7d32;--md-green-900: #1b5e20;--md-green-A100: #b9f6ca;--md-green-A200: #69f0ae;--md-green-A400: #00e676;--md-green-A700: #00c853;--md-light-green-50: #f1f8e9;--md-light-green-100: #dcedc8;--md-light-green-200: #c5e1a5;--md-light-green-300: #aed581;--md-light-green-400: #9ccc65;--md-light-green-500: #8bc34a;--md-light-green-600: #7cb342;--md-light-green-700: #689f38;--md-light-green-800: #558b2f;--md-light-green-900: #33691e;--md-light-green-A100: #ccff90;--md-light-green-A200: #b2ff59;--md-light-green-A400: #76ff03;--md-light-green-A700: #64dd17;--md-lime-50: #f9fbe7;--md-lime-100: #f0f4c3;--md-lime-200: #e6ee9c;--md-lime-300: #dce775;--md-lime-400: #d4e157;--md-lime-500: #cddc39;--md-lime-600: #c0ca33;--md-lime-700: #afb42b;--md-lime-800: #9e9d24;--md-lime-900: #827717;--md-lime-A100: #f4ff81;--md-lime-A200: #eeff41;--md-lime-A400: #c6ff00;--md-lime-A700: #aeea00;--md-yellow-50: #fffde7;--md-yellow-100: #fff9c4;--md-yellow-200: #fff59d;--md-yellow-300: #fff176;--md-yellow-400: #ffee58;--md-yellow-500: #ffeb3b;--md-yellow-600: #fdd835;--md-yellow-700: #fbc02d;--md-yellow-800: #f9a825;--md-yellow-900: #f57f17;--md-yellow-A100: #ffff8d;--md-yellow-A200: #ffff00;--md-yellow-A400: #ffea00;--md-yellow-A700: #ffd600;--md-amber-50: #fff8e1;--md-amber-100: #ffecb3;--md-amber-200: #ffe082;--md-amber-300: #ffd54f;--md-amber-400: #ffca28;--md-amber-500: #ffc107;--md-amber-600: #ffb300;--md-amber-700: #ffa000;--md-amber-800: #ff8f00;--md-amber-900: #ff6f00;--md-amber-A100: #ffe57f;--md-amber-A200: #ffd740;--md-amber-A400: #ffc400;--md-amber-A700: #ffab00;--md-orange-50: #fff3e0;--md-orange-100: #ffe0b2;--md-orange-200: #ffcc80;--md-orange-300: #ffb74d;--md-orange-400: #ffa726;--md-orange-500: #ff9800;--md-orange-600: #fb8c00;--md-orange-700: #f57c00;--md-orange-800: #ef6c00;--md-orange-900: #e65100;--md-orange-A100: #ffd180;--md-orange-A200: #ffab40;--md-orange-A400: #ff9100;--md-orange-A700: #ff6d00;--md-deep-orange-50: #fbe9e7;--md-deep-orange-100: #ffccbc;--md-deep-orange-200: #ffab91;--md-deep-orange-300: #ff8a65;--md-deep-orange-400: #ff7043;--md-deep-orange-500: 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sourceMappingURL=mkdocs-jupyter.css.map*/ init_mathjax = function() { if (window.MathJax) { // MathJax loaded MathJax.Hub.Config({ TeX: { equationNumbers: { autoNumber: \"AMS\", useLabelIds: true } }, tex2jax: { inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ], displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ], processEscapes: true, processEnvironments: true }, displayAlign: 'center', CommonHTML: { linebreaks: { automatic: true } } }); MathJax.Hub.Queue([\"Typeset\", MathJax.Hub]); } } init_mathjax(); Tutorial Delft3D FM 1D2D fluvial flood model of Magdalena river \u00b6 This notebook is an introduction on how to use HYDROLIB-core functionalities to create and adjust a Delft3D FM Suite 1D2D fluvial flood model of the Magdalena river in Columbia. First a 1D river model of the Magdalena river and Canal del Dique will be created, shown in the left figure. This model will be extended with a 2D Flexible Mesh, with a uniform roughness field. Adding a DTM on that 2D mesh is currently not part of this tutorial, but normally this is of course indispensible to mimic the fluvial flood patterns. Running the model or importing the model in the Delft3D FM Suite 1D2D is not shown in this tutorial. Note that the model and tutorial are created for educational purposes and consist partially of fictive/unvalidated model data. HYDROLIB-core is the core library of Python wrappers around the D-HYDRO Suite 1D2D model files (input and output) and model engines (kernel libraries). HYDROLIB is a Python package with tools for pre-processing, post-processing and analysis of hydrodynamical data and simulation results, currently focused on Delft3D Suite 1D2D. HYDROLIB builds upon the basic HYDROLIB-core functionalities. The goal of this tutorial is to familiarize modelers with how to apply HYDROLIB-core functionalities in their modelling procedures for building new models or adjusting existing models. As mentioned above, you will create an 1D2D fluvial flood model from scratch using the D-Flow FM HYDROLIB-core functionalities and the underlying functions from mesh generation ( MeshKernelPy ). The building of the model is done by the following steps Loading libraries Connect to data folder Create empty D-Flow FM model Read branches Create computational grid Add cross-sections Add roughness Add boundary conditions Add initial conditions Add a weir to the model Save 1D model Create 2D flexible mesh Add 2D DTM to model Save 1D2D model Note that HYDROLIB-core also contains functionalities to setup lumped rainfall runoff models ( D-RR ) and to apply real-time control at structures ( D-RTC ), but these are not covered in this tutorial. Installation \u00b6 To run this notebook a simple Python environment with the following packages is required: - python=3.9 - pandas - geopandas - pyogrio - matplotlib - numpy - jupyter - xarray - openpyxl - pip - pip: - hydrolib-core==0.3.1 - meshkernel==1.0.0 Note that all participants received an e-mail to download the material from the Deltares download portal and to create a Conda environment with the packages automatically installed from environment.yml . Furthermore, a dummy model is provided at the download portal to test the environment. Tips for working in the Jupyter Notebook: \u00b6 Tab : Auto-complete on code Shift + Tab : Tooltip Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell Ctrl + Shift + P : Open command palette Let's get started! Loading libraries \u00b6 Several Python packages are required to run the notebook. These packages are imported below. Please consult the HYDROLIB-core documentation if you want to import additional HYDROLIB-core functionalities later. The import of HYDROLIB-core packages will be simplied in future HYDROLIB-core release (> 0.3.1) In [ ]: Copied! # basic packages import numpy as np import pandas as pd import matplotlib.pyplot as plt # I/O from pathlib import Path # vector/polygon packages import geopandas as gpd from shapely import wkt from shapely.geometry import box # HYDROLIB-core libraries from hydrolib.core.mdu.models import FMModel , AutoStartOption from hydrolib.core.net.models import * from hydrolib.core.crosssection.models import CrossLocModel , CrossDefModel , CrossSection , YZCrsDef from hydrolib.core.friction.models import * from hydrolib.core.bc.models import * from hydrolib.core.ext.models import * from hydrolib.core.inifield.models import * from hydrolib.core.onedfield.models import * from hydrolib.core.structure.models import Weir , FlowDirection , StructureModel # basic packages import numpy as np import pandas as pd import matplotlib.pyplot as plt # I/O from pathlib import Path # vector/polygon packages import geopandas as gpd from shapely import wkt from shapely.geometry import box # HYDROLIB-core libraries from hydrolib.core.mdu.models import FMModel, AutoStartOption from hydrolib.core.net.models import * from hydrolib.core.crosssection.models import CrossLocModel, CrossDefModel, CrossSection, YZCrsDef from hydrolib.core.friction.models import * from hydrolib.core.bc.models import * from hydrolib.core.ext.models import * from hydrolib.core.inifield.models import * from hydrolib.core.onedfield.models import * from hydrolib.core.structure.models import Weir, FlowDirection, StructureModel Connect to data \u00b6 The data for this tutorial is provided via the download portal. EX1 : Change the inputdir to the path of your unzipped data folder. In [ ]: Copied! # Get the directory of the notebook location root = Path . cwd () # Answer EX1 # Specify the path to the data folder inputdir = # Get the directory of the notebook location root = Path.cwd() # Answer EX1 # Specify the path to the data folder inputdir = Create empty D-Flow FM model \u00b6 To start a model from scratch you need to create first an empty model without data and assign a filepath to the model. In this case a D-Flow FM model is created. The MDU file (master definition file) is the main file of the D-Flow FM model. This is created with the FMModel() function. The fm model object is only created in memory. To save the actual model file, call fm.save() . EX2 : Set the outputdir of the model and give it a name. Verify that an MDU file has been written in your output directory. In [ ]: Copied! # Create empty D-Flow FM model fm = FMModel () # Answer EX2 # Assign filepath to the D-Flow FM model outputdir = fm . filepath = outputdir / 'Magdalena_1D.mdu' fm . save () # Create empty D-Flow FM model fm = FMModel() # Answer EX2 # Assign filepath to the D-Flow FM model outputdir = fm.filepath = outputdir / 'Magdalena_1D.mdu' fm.save() PART 1: Set up a 1D Delft3D FM model \u00b6 In this part we will build up the complete 1D model schematization step by step. At the end you should have a complete set of model input files for a 1D calculation. Read branches \u00b6 The model will include the lower part of the Magadalena from Cordoba Teton to the river mouth Baranquilla and the Canal del Dique. EX2 : Please investigate the branches variable and answer the following questions for yourself: How many river branches does the model have? What are their names? Which friction type and values are used for each branch? In [ ]: Copied! # Read the branches branches = gpd . read_file ( filename = inputdir / 'branches_Branches.shp' ) # Answer EX3 # Read the branches branches = gpd.read_file(filename = inputdir / 'branches_Branches.shp') # Answer EX3 Create 1D computational grid \u00b6 In the previous step you read the geometry and attributes of the branches into the notebook. These branches will become the network input to our FMModel . The cell below shows how the geometry and name of the branches are assigned to the network. In addition a 1D computational grid ( mesh1d ) with gridpoint every 1000 meter is created on top of this network. Since the network does not yet exist, you need to create an empty network model . Assign the geometry of the branches followed by the generation of the computational grid. The network model should be added to the D-Flow FM model ( fm variable in this notebook) as network in the netfile parameter in the section geometry . Note that you have to specify a filepath for the networkfile. Note that the network model can consist of 1D, 2D flexible mesh ( mesh2d ) and 1D2D links ( links1d2d ). In [ ]: Copied! # Specify 1D computational grid distance dx = 1000.0 # Create an empty network network = Network () # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch in branches . iterrows (): xy = np . transpose ( branch . geometry . xy ) branch_new = Branch ( geometry = xy ) branch_new . generate_nodes ( mesh1d_edge_length = dx ) network . mesh1d_add_branch ( branch_new , name = branch . Name ) # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm . geometry . netfile . network = network fm . geometry . netfile . filepath = \"FlowFM_net.nc\" # Specify 1D computational grid distance dx = 1000.0 # Create an empty network network = Network() # Assign geometry of the branches and generate the computational grid on top of the branches. for index,branch in branches.iterrows(): xy = np.transpose(branch.geometry.xy) branch_new = Branch(geometry=xy) branch_new.generate_nodes(mesh1d_edge_length=dx) network.mesh1d_add_branch(branch_new, name=branch.Name) # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm.geometry.netfile.network = network fm.geometry.netfile.filepath = \"FlowFM_net.nc\" EX3 : Please change the computational grid distance of each branch accordingly: Branch name dx [m] Channel_1D_1_A 1000 Channel_1D_1_B 1000 Channel_1D 500 Tip : Do not forget to create a new network. In [ ]: Copied! # Answer EX3 # Specify 1D computational grid distance dx = # Create an empty network # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch in branches . iterrows (): xy = np . transpose ( branch . geometry . xy ) branch_new = Branch ( geometry = xy ) branch_new . generate_nodes ( mesh1d_edge_length = dx ) network . mesh1d_add_branch ( branch_new , name = branch . Name ) network . _mesh1d . _set_mesh1d () # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm . geometry . netfile . network = fm . geometry . netfile . filepath = # Answer EX3 # Specify 1D computational grid distance dx = # Create an empty network # Assign geometry of the branches and generate the computational grid on top of the branches. for index,branch in branches.iterrows(): xy = np.transpose(branch.geometry.xy) branch_new = Branch(geometry=xy) branch_new.generate_nodes(mesh1d_edge_length=dx) network.mesh1d_add_branch(branch_new, name=branch.Name) network._mesh1d._set_mesh1d() # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm.geometry.netfile.network = fm.geometry.netfile.filepath = The 1D branches are plotted on a map in the figure below. Also, the computational grid points in the mesh1d definition are shown. In [ ]: Copied! # Create a figure with the flowlinks of the model figure , ( ax1 , ax2 ) = plt . subplots ( ncols = 2 ) img = plt . imread ( inputdir / \"osm_background.png\" ) mesh1d_meshkernel = network . _mesh1d . _get_mesh1d () ax1 . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) mesh1d_meshkernel . plot_edges ( ax = ax1 , color = 'red' ) # Add some annotation of branches: for index , branch in branches . iterrows (): middleIndex = int (( len ( branch [ 'geometry' ] . coords ) - 1 ) / 2 ) ax1 . text ( branch [ 'geometry' ] . xy [ 0 ][ middleIndex ], branch [ 'geometry' ] . xy [ 1 ][ middleIndex ], branch [ 'Name' ], ha = 'right' ) # Make a second plot with a zoom-in view of the computational grid points near the junction ax2 . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) ax2 . set_xlim ([ 500000 , 525000 ]) ax2 . set_ylim ([ 1125000 , 1150000 ]) mesh1d_meshkernel . plot_edges ( ax = ax2 , color = 'red' , marker = '.' , markeredgecolor = 'k' , markersize = 1 ) # Create a figure with the flowlinks of the model figure, (ax1, ax2) = plt.subplots(ncols=2) img = plt.imread(inputdir/\"osm_background.png\") mesh1d_meshkernel = network._mesh1d._get_mesh1d() ax1.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) mesh1d_meshkernel.plot_edges(ax=ax1, color='red') # Add some annotation of branches: for index,branch in branches.iterrows(): middleIndex = int((len(branch['geometry'].coords) - 1)/2) ax1.text(branch['geometry'].xy[0][middleIndex], branch['geometry'].xy[1][middleIndex], branch['Name'], ha='right') # Make a second plot with a zoom-in view of the computational grid points near the junction ax2.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) ax2.set_xlim([500000, 525000]) ax2.set_ylim([1125000 ,1150000]) mesh1d_meshkernel.plot_edges(ax=ax2, color='red',marker='.',markeredgecolor='k',markersize=1) Add cross-sections \u00b6 In order to determine the flow area of the 1D model during the computation, you need cross-sections. These cross-sections consist of two components: Cross-section locations ( crosslocfile ): The crosslocfile contains the location of the cross-section on the branches. This is indicated with branchId chainage , where branchId is the name of the branch and chainage the distance to the upstream node. The figure below shows the cross-section locations in grey. In addition the cross-section location consist of the cross-section definition used at that location and a vertical shift of the profile. The latter is mainly used to create a good longitudinal slope over the 1D model (in case of shared cross-sections).

    Cross-section definitions ( crossdeffile ): The crossdeffile has the cross-section definitions in it. These definitions describe the shape of the profile. There are multiple types available: circle, rectangle, ZW- (tabulated), YZ- and XYZ-profiles. Depending on what type of watersystem you try to model you decide which cross-section to use. We recommend to use ZW- or YZ-profiles for rivers.

    Add cross-section locations \u00b6 Below the cross-section locations are read from a CSV-file and added to an empty CrossLocModel . Note that the entire dataframe with the cross-section locations is converted at once to CrossLocModel. More about dataframe handling in HYDROLIB-core can be found here . EX4 : Please investigate the profile_loc variable and answer the following questions for yourself: How many cross-sections are there in the model and per branch? Check the chainage. Also print the cross-sections locations assigned to the D-Flow FM model. Use fm.geometry.crosslocfile.crosssection (part 2). What happens if you only print the first fm.geometry.crosslocfile In [ ]: Copied! # Read profile location file profiles_location_file = inputdir / 'cross_section_locations.csv' profiles_loc = pd . read_csv ( profiles_location_file , index_col = False ) # Answer EX4 - part 1 # Create empty cross-section location model crsloc = CrossLocModel () # Assign filepath to the model crsloc . filepath = 'crsloc.ini' # Convert the dataframe crsloc . crosssection = profiles_loc . to_dict ( \"records\" ) # Assign CrossLocModel to the D-Flow FM model. fm . geometry . crosslocfile = crsloc # Answer EX4 - part 2 # Read profile location file profiles_location_file = inputdir / 'cross_section_locations.csv' profiles_loc = pd.read_csv(profiles_location_file, index_col=False) # Answer EX4 - part 1 # Create empty cross-section location model crsloc = CrossLocModel() # Assign filepath to the model crsloc.filepath = 'crsloc.ini' # Convert the dataframe crsloc.crosssection = profiles_loc.to_dict(\"records\") # Assign CrossLocModel to the D-Flow FM model. fm.geometry.crosslocfile = crsloc # Answer EX4 - part 2 Add cross-section definitions \u00b6 In the following cell the definitions belonging to the cross-section locations are added to the D-Flow FM model. These cross-sections are all YZ-profiles in order to define natural shape of the river. Please see that the following steps are included: Read the cross-section definitions from an excel. Note that the cross-section definitions id's match with the definitions specified in the crossLocModel. Create an empty CrossDefModel and assign filepath Specify some characteristics for YZ profile. Please consult appendix C.16.1.6 from D-Flow FM 1D2D Create YZCrsDef for each profile definition. Append the definition to the CrossDefModel. Append the CrossDefModel to the D-Flow FM model. In [ ]: Copied! # Create cross-section definitions profiles_file = inputdir / '1D_YZ_CrossSections.xlsx' profiles = pd . read_excel ( profiles_file , sheet_name = None ) names = list ( profiles . keys ()) print ( names ) # Create empty CrossDefModel crsdef = CrossDefModel () crsdef . filepath = 'crsdef.ini' # Specify some charachteristics for YZ profile type_crs = 'yz' thalweg = 0.0 singleValued = 'yes' conveyance = 'segmented' sectionCount = 1 # Create the YZ profiles and append them to the CrossDefModel for name in names : yzCount = len ( profiles [ name ] . values ) ycoord = profiles [ name ] . y . to_list () zcoord = profiles [ name ] . z . to_list () frictionIds = 'channels' frictionPositions = [ profiles [ name ] . y [ 0 ], profiles [ name ] . y [ yzCount - 1 ]] crosssection = YZCrsDef ( id = name , type = type_crs , thalweg = thalweg , singleValuedZ = singleValued , conveyance = conveyance , yzCount = yzCount , yCoordinates = ycoord , zCoordinates = zcoord , sectionCount = sectionCount , frictionIds = frictionIds , frictionPositions = frictionPositions ) crsdef . definition . append ( crosssection ) print ( f 'definition of { name } added to cross-section model' ) # Append CrossDefModel to D-Flow FM model fm . geometry . crossdeffile = crsdef # Create cross-section definitions profiles_file = inputdir / '1D_YZ_CrossSections.xlsx' profiles = pd.read_excel(profiles_file, sheet_name=None) names = list(profiles.keys()) print(names) # Create empty CrossDefModel crsdef = CrossDefModel() crsdef.filepath = 'crsdef.ini' # Specify some charachteristics for YZ profile type_crs = 'yz' thalweg = 0.0 singleValued = 'yes' conveyance = 'segmented' sectionCount = 1 # Create the YZ profiles and append them to the CrossDefModel for name in names: yzCount = len(profiles[name].values) ycoord = profiles[name].y.to_list() zcoord = profiles[name].z.to_list() frictionIds = 'channels' frictionPositions = [profiles[name].y[0], profiles[name].y[yzCount-1]] crosssection = YZCrsDef(id=name, type=type_crs, thalweg=thalweg, singleValuedZ=singleValued, conveyance=conveyance, yzCount=yzCount, yCoordinates= ycoord, zCoordinates=zcoord, sectionCount=sectionCount, frictionIds = frictionIds, frictionPositions=frictionPositions) crsdef.definition.append(crosssection) print(f'definition of {name} added to cross-section model') # Append CrossDefModel to D-Flow FM model fm.geometry.crossdeffile = crsdef Add roughness \u00b6 The 1D model has now a network topology, computational 1D grid and cross-sections. Friction is a component that should be added to the model to get the proper bed roughness and channel conveyance. In this step you will add the FrictionModel to the D-Flow FM model by specifying the friction type and value at the upstream cross-section location (chainage=1000.0 m) of each branch in the model ( FrictBranch ). Also a global roughness section is specified ( FrictGlobal ). This global section is used when there is no friction type and values specified for a specific branch. It also contains the frictionId. In the cross-section definition model a reference is made to this frictionId. You can check this with the commands below and search for frictionIds . In [ ]: Copied! # Print directly the modelobject (in this case all definitions) print ( fm . geometry . crossdeffile . definition ) # Or convert it first to a dataframe df_def = pd . DataFrame ([ f . __dict__ for f in fm . geometry . crossdeffile . definition ]) print ( df_def [[ 'frictionids' ]]) # Print directly the modelobject (in this case all definitions) print(fm.geometry.crossdeffile.definition) # Or convert it first to a dataframe df_def = pd.DataFrame([f.__dict__ for f in fm.geometry.crossdeffile.definition]) print(df_def[['frictionids']]) Note that YZ profiles can refer to multiple frictionIds, since the friction can vary over the cross-section. Hence the frictionId is given in a List() . This means indirectly that multiple FrictionModels can be added to one D-Flow FM model. The created FrictionModel should therefore been added in a List() to the D-Flow FM model. In [ ]: Copied! # Specify frictionId(s) for the FrictionModel(s) friction_name = 'channels' # Specify for each FrictionModel a global type and value global_type = FrictionType . manning # Options are chezy,debosbijkerk, manning, strickler, stricklernikuradse, wallawnikuradse, whitecolebrook global_value = 0.023 # Create empty friction model and assign filepath roughness = FrictionModel () roughness . filepath = \"roughness-channels.ini\" # often we specify the filenames as \"roughness-frictionId.ini\" # Create global friction model and add it to frictionmodel roughness . global_ = FrictGlobal ( frictionId = friction_name , frictionType = global_type , frictionValue = global_value ) # Add friction from branches function_type = 'constant' # This model uses constant friction per branch df_friction = branches [[ 'Name' , 'fric_type' , 'fric_value' , 'chainage' ]] df_friction . columns = [ 'branchId' , 'frictionType' , 'frictionValues' , 'chainage' ] df_friction = df_friction . assign ( frictionValues = [[ i ] for i in df_friction . frictionValues . values ]) df_friction = df_friction . assign ( functionType = function_type ) df_friction = df_friction . assign ( chainage = [[ i ] for i in df_friction . chainage . values ]) df_friction = df_friction . assign ( numlocations = 1 ) # you can specify multiple location along the branch with different friction values. roughness . branch = df_friction . to_dict ( 'records' ) # the dataframe is converted to FrictBranch models at once # Add frictionmodel to the D-Flow FM model. fm . geometry . frictfile = [ roughness ] # frictfile is a list of frictionModels # Specify frictionId(s) for the FrictionModel(s) friction_name = 'channels' # Specify for each FrictionModel a global type and value global_type = FrictionType.manning # Options are chezy,debosbijkerk, manning, strickler, stricklernikuradse, wallawnikuradse, whitecolebrook global_value = 0.023 # Create empty friction model and assign filepath roughness = FrictionModel() roughness.filepath = \"roughness-channels.ini\" # often we specify the filenames as \"roughness-frictionId.ini\" # Create global friction model and add it to frictionmodel roughness.global_ = FrictGlobal(frictionId=friction_name,frictionType=global_type,frictionValue=global_value) # Add friction from branches function_type = 'constant' # This model uses constant friction per branch df_friction = branches[['Name', 'fric_type', 'fric_value', 'chainage']] df_friction.columns = ['branchId','frictionType','frictionValues', 'chainage'] df_friction = df_friction.assign(frictionValues = [[i] for i in df_friction.frictionValues.values]) df_friction = df_friction.assign(functionType=function_type) df_friction = df_friction.assign(chainage = [[i] for i in df_friction.chainage.values]) df_friction = df_friction.assign(numlocations=1) # you can specify multiple location along the branch with different friction values. roughness.branch = df_friction.to_dict('records') # the dataframe is converted to FrictBranch models at once # Add frictionmodel to the D-Flow FM model. fm.geometry.frictfile = [roughness] # frictfile is a list of frictionModels EX5 : Let's build another frictionmodel with frictionId dique representing the friction in Canal del Dique. This frictionmodel assumes Chezy as global friction type and has a friction value of 45. In [ ]: Copied! # Answer to EX5 # Specify frictionId(s) for the FrictionModel(s) friction_id2 = # Specify for each FrictionModel a global type and value global_type2 = global_value2 = # Create empty friction model and assign filepath roughness_dique = roughness_dique . filepath = # Create global friction model and add it to frictionmodel roughness_dique . global_ = # Add frictionmodels to the D-Flow FM model. fm . geometry . frictfile = # Note that the other friction needs to be added to the list. # Answer to EX5 # Specify frictionId(s) for the FrictionModel(s) friction_id2 = # Specify for each FrictionModel a global type and value global_type2 = global_value2 = # Create empty friction model and assign filepath roughness_dique = roughness_dique.filepath = # Create global friction model and add it to frictionmodel roughness_dique.global_ = # Add frictionmodels to the D-Flow FM model. fm.geometry.frictfile = # Note that the other friction needs to be added to the list. The cross-sections on the Canal del Dique (Channel_1D_1) do not refer to this new frictionId. Please uncomment the code below to change this after completion of exercise 5. In [ ]: Copied! ## Convert crosssection defintions from D-Flow FM model to dataframe #df_def = pd.DataFrame([f.__dict__ for f in fm.geometry.crossdeffile.definition]) #print(df_def) # ## Check which cross-section locations are located on Channel_1D_1 #df_loc = pd.DataFrame([f.__dict__ for f in fm.geometry.crosslocfile.crosssection]) #print(df_loc.loc[:,['id','branchid','definitionid']]) # ## To which definition do these locations refer: #defs = df_loc.loc[df_loc.index[df_loc.branchid=='Channel_1D_1'],'definitionid'].values # ## Change the Frictionids to dique for Channel_1D_1 #index_defs = df_def.index[df_def.id.isin(defs)] # #for i in index_defs: # df_def.loc[i, 'frictionids'] = ['dique'] # ## Overwrite the definitions in D-Flow FM model with the changes in the dataframe #fm.geometry.crossdeffile.definition = df_def.to_dict(\"records\") ## Convert crosssection defintions from D-Flow FM model to dataframe #df_def = pd.DataFrame([f.__dict__ for f in fm.geometry.crossdeffile.definition]) #print(df_def) # ## Check which cross-section locations are located on Channel_1D_1 #df_loc = pd.DataFrame([f.__dict__ for f in fm.geometry.crosslocfile.crosssection]) #print(df_loc.loc[:,['id','branchid','definitionid']]) # ## To which definition do these locations refer: #defs = df_loc.loc[df_loc.index[df_loc.branchid=='Channel_1D_1'],'definitionid'].values # ## Change the Frictionids to dique for Channel_1D_1 #index_defs = df_def.index[df_def.id.isin(defs)] # #for i in index_defs: # df_def.loc[i, 'frictionids'] = ['dique'] # ## Overwrite the definitions in D-Flow FM model with the changes in the dataframe #fm.geometry.crossdeffile.definition = df_def.to_dict(\"records\") Add boundary conditions to the model \u00b6 Fluvial floods occur when water levels in the river are too high. These high water levels in the rivers can result from several factors. One of those is the occurence of heavy rainfall in the upstream catchment. These heavy rainstorm can lead to a high discharge wave entering the upstream boundary of the river. In this tutorial you will model such a high discharge wave (time series) at the upstream 1D boundary (node id = '521410.278872_1056811.761107'). For the two downstream boundaries (node ids = [wkt_geom Name BridgeCount CrossSectio CulvertCoun GateCount GeometryLen IsLengthCus LateralSour Length LongName OrderNumber PumpCount Source StructureCo Target WeirCount fric_type fric_value chainage]) a constant water level of 0 m AD is assumed. Note that this are tidal boundaries in reality. In order to apply boundary conditions on a model you need two components: Forcing (.bc) file ForcingModel : This model contains the forcing value, time series, astronomical tide, realtime connection with other modules (D-RR) or QHtable. The first two options are created in this tutorial. External Forcing (.ext) file ExtModel : The external forcing specifies the location and type of forcing. Types of forcing are Boundary , Lateral and meteo. In [ ]: Copied! # Get node ids of branches node_ids = fm . geometry . netfile . network . _mesh1d . network1d_node_id print ( node_ids ) # Specify the node ids node_upstream = node_ids [ 0 ] # discharge time series node nodes_downstream = node_ids [ 2 :] # water level nodes # Create an empty external forcing model and forcing model ext = ExtModel () ext . filepath = 'boundary_new.ext' bc = ForcingModel () #bc.filepath = inputdir / 'BoundaryConditions.bc' # Read the upstream boundary time series from excel discharge_file = inputdir / '1D_BoundaryConditions.xlsx' discharge = pd . read_excel ( discharge_file , sheet_name = [ 0 ]) # Create the timeseries bc_up = TimeSeries ( name = node_upstream , nodeid = node_upstream , timeinterpolation = TimeInterpolation . linear , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2012-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], datablock = [[ time , dis ] for [ time , dis ] in discharge [ 0 ] . values ] ) # Create downstream constant boundaries bc_dn1 = Constant ( name = nodes_downstream [ 0 ], nodeid = nodes_downstream [ 0 ], quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], datablock = [[ \"0.0\" ]] ) bc_dn2 = Constant ( name = nodes_downstream [ 1 ], nodeid = nodes_downstream [ 1 ], quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], datablock = [[ \"0.0\" ]] ) # Add the forcing to ForcingModel bc . forcing . extend ([ bc_up , bc_dn1 , bc_dn2 ]) # Create boundary locations in ExtModel ext_up = Boundary ( quantity = 'dischargebnd' , nodeid = node_upstream , forcingfile = bc ) ext_dn1 = Boundary ( quantity = 'waterlevelbnd' , nodeid = nodes_downstream [ 0 ], forcingfile = bc ) ext_dn2 = Boundary ( quantity = 'waterlevelbnd' , nodeid = nodes_downstream [ 1 ], forcingfile = bc ) # Add the boundaries to ExtModel ext . boundary . extend ([ ext_up , ext_dn1 , ext_dn2 ]) # Add the ExtModel to D-Flow FM model fm . external_forcing . extforcefilenew = ext # Get node ids of branches node_ids = fm.geometry.netfile.network._mesh1d.network1d_node_id print(node_ids) # Specify the node ids node_upstream = node_ids[0] # discharge time series node nodes_downstream = node_ids[2:] # water level nodes # Create an empty external forcing model and forcing model ext = ExtModel() ext.filepath = 'boundary_new.ext' bc = ForcingModel() #bc.filepath = inputdir / 'BoundaryConditions.bc' # Read the upstream boundary time series from excel discharge_file = inputdir / '1D_BoundaryConditions.xlsx' discharge = pd.read_excel(discharge_file, sheet_name=[0]) # Create the timeseries bc_up = TimeSeries( name = node_upstream, nodeid = node_upstream, timeinterpolation = TimeInterpolation.linear, quantityunitpair = [QuantityUnitPair(quantity = 'time', unit = 'minutes since 2012-01-01 00:00:00'), QuantityUnitPair(quantity = 'dischargebnd', unit = 'm\u00b3/s')], datablock = [[time, dis] for [time,dis] in discharge[0].values] ) # Create downstream constant boundaries bc_dn1 = Constant( name = nodes_downstream[0], nodeid = nodes_downstream[0], quantityunitpair = [QuantityUnitPair(quantity = 'waterlevelbnd', unit = 'm')], datablock = [[\"0.0\"]] ) bc_dn2 = Constant( name = nodes_downstream[1], nodeid = nodes_downstream[1], quantityunitpair = [QuantityUnitPair(quantity = 'waterlevelbnd', unit = 'm')], datablock = [[\"0.0\"]] ) # Add the forcing to ForcingModel bc.forcing.extend([bc_up,bc_dn1,bc_dn2]) # Create boundary locations in ExtModel ext_up = Boundary( quantity = 'dischargebnd', nodeid = node_upstream, forcingfile = bc ) ext_dn1 = Boundary( quantity = 'waterlevelbnd', nodeid = nodes_downstream[0], forcingfile = bc ) ext_dn2 = Boundary( quantity = 'waterlevelbnd', nodeid = nodes_downstream[1], forcingfile = bc ) # Add the boundaries to ExtModel ext.boundary.extend([ext_up,ext_dn1,ext_dn2]) # Add the ExtModel to D-Flow FM model fm.external_forcing.extforcefilenew = ext Add initial conditions \u00b6 For this model an initial water depth of 1.0 meter is assumed in the 1D model. Below you can see how this initial waterdepth is added to the D-Flow FM model using the following steps: Creating 1D initial conditions field ( 1DField ), which contains the actual waterdepths on each branch. Note that the file is seperately saved from the rest of the model. Creating IniFieldModel (= Initial and parameter field files) in which we collect the initial condition specified in step 1, so that it can be added to the FMModel . In [ ]: Copied! # Create 1D initial conditions field ini_1d = OneDFieldModel () ini_1d . global_ = OneDFieldGlobal ( quantity = 'waterdepth' , unit = 'm' , value = 1.0 ) # only global values are needed in this case, but you could also specify it per branch. ini_1d . filepath = 'initialwaterdepth.ini' ini_1d . save ( outputdir / ini_1d . filepath ) # 1D field ini files needs to be saved seperately from the model save. # Create initial field file ini_field = IniFieldModel () ini_field . filepath = 'inifield.ini' ini_field . initial = InitialField ( quantity = 'waterdepth' , datafile = ini_1d . filepath , datafiletype = DataFileType . onedfield ) fm . geometry . inifieldfile = ini_field # Create 1D initial conditions field ini_1d = OneDFieldModel() ini_1d.global_ = OneDFieldGlobal(quantity='waterdepth', unit='m', value=1.0) # only global values are needed in this case, but you could also specify it per branch. ini_1d.filepath = 'initialwaterdepth.ini' ini_1d.save(outputdir / ini_1d.filepath) # 1D field ini files needs to be saved seperately from the model save. # Create initial field file ini_field = IniFieldModel() ini_field.filepath = 'inifield.ini' ini_field.initial = InitialField(quantity='waterdepth',datafile=ini_1d.filepath, datafiletype=DataFileType.onedfield) fm.geometry.inifieldfile = ini_field Add a weir to the model \u00b6 Many lakes occur close along Canal del Dique. See figure below. This tutorial assumes that these lakes can function as extra storage for the floods from the river. Hence a weir structure, functioning as a small dam, is added downstream of the lakes. This weir structure has the following conditions: It is located at 70 km from the upstream node of the branch. The crestlevel is 4.0 m AD. The crest width is 105.0 m. The flow over the dam is in both directions.

    In [ ]: Copied! # Create weir structure weir = Weir ( id = 'fictive_dam' , name = 'fictive_dam' , branchId = 'Channel_1D_1' , chainage = 70000.0 , allowedFlowDir = FlowDirection . both , crestLevel = 4.0 , crestWidth = 105.0 , corrCoeff = 1.000 , useVelocityHeight = True ) # Create structure model struc = StructureModel () struc . filepath = 'structure.ini' # Append weir to structure struc . structure . append ( weir ) # Assign structure model to D-Flow FM model fm . geometry . structurefile = [ struc ] # Create weir structure weir = Weir( id='fictive_dam', name = 'fictive_dam', branchId='Channel_1D_1', chainage=70000.0, allowedFlowDir=FlowDirection.both, crestLevel=4.0, crestWidth=105.0, corrCoeff=1.000, useVelocityHeight=True ) # Create structure model struc = StructureModel() struc.filepath = 'structure.ini' # Append weir to structure struc.structure.append(weir) # Assign structure model to D-Flow FM model fm.geometry.structurefile = [struc] EX6 : You found out that the dam should be significantly higher. Hence you increase the crestlevel to 10.0 m AD. Your client also decided that flow can only occur from upstream to downstream. Please change the weir above. In [ ]: Copied! # Answer EX6: # Create weir structure weir = # Create structure model struc = StructureModel () struc . filepath = 'structure.ini' # Append weir to structure struc . structure . append ( weir ) # Assign structure model to D-Flow FM model fm . geometry . structurefile = [ struc ] # Answer EX6: # Create weir structure weir = # Create structure model struc = StructureModel() struc.filepath = 'structure.ini' # Append weir to structure struc.structure.append(weir) # Assign structure model to D-Flow FM model fm.geometry.structurefile = [struc] Save 1D model \u00b6 The 1D model is now finished. The commands below are used to save the model to the correct filepath (specified for the MDU-file). Note that the recurse is set to True to make sure all underlying model files are written to the directory. Else the MDU-file will be the only file written to the directory. In [ ]: Copied! # Change some time settings fm . time . refdate = '20120101' fm . time . dtuser = 60. # seconds fm . time . tstart = 43200. fm . time . tstop = 561600. # Save the 1D model. fm . general . autostart = AutoStartOption . no # This is a workaround for a bug in hydrolib-core 0.3.1 fm . save ( recurse = True ) # Change some time settings fm.time.refdate = '20120101' fm.time.dtuser = 60. # seconds fm.time.tstart = 43200. fm.time.tstop = 561600. # Save the 1D model. fm.general.autostart = AutoStartOption.no # This is a workaround for a bug in hydrolib-core 0.3.1 fm.save(recurse=True) PART 2: Extend to a 1D2D Delft3D FM model \u00b6 We will now continue with the model fm from part 1, and add a 2D mesh to it, as well as 1D2D couplings. Create 2D flexible mesh \u00b6 We use a shapefile with the area of interest to define the extent of the new 2D mesh that is to be generated. First, a uniform rectilinear mesh is generated, after which it can be clipped. EX7 : Create a rectangular grid with a cell size of 2500 by 2500 meter. Use create_rectilinear() function. EX8 : Clip the rectangular grid with the clip_geom using clip() function. In [ ]: Copied! # Read grid outline gdf_grid = gpd . read_file ( inputdir / 'outline_2D_grid.shp' ) # Determine the boundary box extent = gdf_grid . geometry [ 0 ] . bounds # Create uniform rectilinear mesh mesh2d = Mesh2d () # Answer EX7 # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np . array ( gdf_grid . geometry [ 0 ] . exterior . xy ) clip_geom = GeometryList ( clip_polygon [ 0 ], clip_polygon [ 1 ]) # Answer EX8 fm . geometry . netfile . network . _mesh2d = mesh2d fm . geometry . netfile . filepath = \"FlowFM_1D2D_net.nc\" # Read grid outline gdf_grid = gpd.read_file(inputdir / 'outline_2D_grid.shp') # Determine the boundary box extent = gdf_grid.geometry[0].bounds # Create uniform rectilinear mesh mesh2d = Mesh2d() # Answer EX7 # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np.array(gdf_grid.geometry[0].exterior.xy) clip_geom = GeometryList(clip_polygon[0],clip_polygon[1]) # Answer EX8 fm.geometry.netfile.network._mesh2d = mesh2d fm.geometry.netfile.filepath = \"FlowFM_1D2D_net.nc\" The cell below produces a basic plot of the 1D + 2D mesh. In [ ]: Copied! # Create a plot mesh2d_mk = network . _mesh2d . get_mesh2d () mesh1d_mk = network . _mesh1d . _get_mesh1d () figure , ax = plt . subplots () ax . set_aspect ( 'equal' ) plt . rcParams [ \"figure.figsize\" ] = 10 , 10 ax . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) # Plot the 1D2D network mesh2d_mk . plot_edges ( ax = ax , color = \"orange\" ) mesh1d_mk . plot_edges ( ax = ax , color = 'blue' ) # Create a plot mesh2d_mk = network._mesh2d.get_mesh2d() mesh1d_mk = network._mesh1d._get_mesh1d() figure, ax = plt.subplots() ax.set_aspect('equal') plt.rcParams[\"figure.figsize\"]=10,10 ax.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) # Plot the 1D2D network mesh2d_mk.plot_edges(ax=ax, color=\"orange\") mesh1d_mk.plot_edges(ax=ax, color='blue') Local refinement of the 2D mesh \u00b6 One of the key functionalities of Delft3D Flexible Mesh is that you can refine the 2D grid locally. The cell below shows how the grid is locally refined around the river by executing the refinement algorithm once ( level=1 ). In [ ]: Copied! # Create empty mesh2d object mesh2d = Mesh2d () # Create rectangular grid mesh2d . create_rectilinear ( extent = extent , dx = 2500.0 , dy = 2500.0 ) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np . array ( gdf_grid . geometry [ 0 ] . exterior . xy ) clip_geom = GeometryList ( clip_polygon [ 0 ], clip_polygon [ 1 ]) mesh2d . clip ( clip_geom ) # Refine the coarse uniform grid in a buffer region around the rivers gdf_refine = gpd . read_file ( inputdir / 'buffer_around_river_proj.shp' ) refine_polygon = np . array ( gdf_refine . geometry [ 0 ] . exterior . xy ) refine_geom = GeometryList ( refine_polygon [ 0 ], refine_polygon [ 1 ]) mesh2d . refine ( refine_geom , level = 1 ) fm . geometry . netfile . network . _mesh2d = mesh2d fm . geometry . netfile . filepath = \"FlowFM_1D2D_refined_net.nc\" # Create empty mesh2d object mesh2d = Mesh2d() # Create rectangular grid mesh2d.create_rectilinear( extent=extent, dx=2500.0, dy=2500.0 ) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np.array(gdf_grid.geometry[0].exterior.xy) clip_geom = GeometryList(clip_polygon[0],clip_polygon[1]) mesh2d.clip(clip_geom) # Refine the coarse uniform grid in a buffer region around the rivers gdf_refine = gpd.read_file(inputdir / 'buffer_around_river_proj.shp') refine_polygon = np.array(gdf_refine.geometry[0].exterior.xy) refine_geom = GeometryList(refine_polygon[0], refine_polygon[1]) mesh2d.refine(refine_geom, level=1) fm.geometry.netfile.network._mesh2d = mesh2d fm.geometry.netfile.filepath = \"FlowFM_1D2D_refined_net.nc\" In [ ]: Copied! # Create a plot mesh2d_mk = network . _mesh2d . get_mesh2d () mesh1d_mk = network . _mesh1d . _get_mesh1d () figure , ax = plt . subplots () ax . set_aspect ( 'equal' ) plt . rcParams [ \"figure.figsize\" ] = 10 , 10 ax . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) # Plot the 1D2D network mesh2d_mk . plot_edges ( ax = ax , color = \"orange\" ) mesh1d_mk . plot_edges ( ax = ax , color = 'blue' ) # Create a plot mesh2d_mk = network._mesh2d.get_mesh2d() mesh1d_mk = network._mesh1d._get_mesh1d() figure, ax = plt.subplots() ax.set_aspect('equal') plt.rcParams[\"figure.figsize\"]=10,10 ax.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) # Plot the 1D2D network mesh2d_mk.plot_edges(ax=ax, color=\"orange\") mesh1d_mk.plot_edges(ax=ax, color='blue') Save 1D2D model \u00b6 The 1D2D model is now finished. The commands below are used to save the model to the correct filepath (specified for the MDU-file). Note that the recurse is set to True to make sure all underlying model files are written to the directory. Else the MDU-file will be the only file written to the directory. Note that the 1D2D links will be generated in the Delft3D FM 1D2D software. Future releases of HYDROLIB-core will consist of 1D2D functionalities. In [ ]: Copied! # Change fm outputdir_1d2d = root / '1D2D_model' fm . filepath = outputdir_1d2d / 'Magdalena_1D2D.mdu' fm . general . autostart = AutoStartOption . no fm . save ( recurse = True ) # Change fm outputdir_1d2d = root / '1D2D_model' fm.filepath = outputdir_1d2d / 'Magdalena_1D2D.mdu' fm.general.autostart = AutoStartOption.no fm.save(recurse=True)","title":"Tutorial Delft3D FM 1D2D fluvial flood model of Magdalena river"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#tutorial-delft3d-fm-1d2d-fluvial-flood-model-of-magdalena-river","text":"This notebook is an introduction on how to use HYDROLIB-core functionalities to create and adjust a Delft3D FM Suite 1D2D fluvial flood model of the Magdalena river in Columbia. First a 1D river model of the Magdalena river and Canal del Dique will be created, shown in the left figure. This model will be extended with a 2D Flexible Mesh, with a uniform roughness field. Adding a DTM on that 2D mesh is currently not part of this tutorial, but normally this is of course indispensible to mimic the fluvial flood patterns. Running the model or importing the model in the Delft3D FM Suite 1D2D is not shown in this tutorial. Note that the model and tutorial are created for educational purposes and consist partially of fictive/unvalidated model data. HYDROLIB-core is the core library of Python wrappers around the D-HYDRO Suite 1D2D model files (input and output) and model engines (kernel libraries). HYDROLIB is a Python package with tools for pre-processing, post-processing and analysis of hydrodynamical data and simulation results, currently focused on Delft3D Suite 1D2D. HYDROLIB builds upon the basic HYDROLIB-core functionalities. The goal of this tutorial is to familiarize modelers with how to apply HYDROLIB-core functionalities in their modelling procedures for building new models or adjusting existing models. As mentioned above, you will create an 1D2D fluvial flood model from scratch using the D-Flow FM HYDROLIB-core functionalities and the underlying functions from mesh generation ( MeshKernelPy ). The building of the model is done by the following steps Loading libraries Connect to data folder Create empty D-Flow FM model Read branches Create computational grid Add cross-sections Add roughness Add boundary conditions Add initial conditions Add a weir to the model Save 1D model Create 2D flexible mesh Add 2D DTM to model Save 1D2D model Note that HYDROLIB-core also contains functionalities to setup lumped rainfall runoff models ( D-RR ) and to apply real-time control at structures ( D-RTC ), but these are not covered in this tutorial.","title":"Tutorial Delft3D FM 1D2D fluvial flood model of Magdalena river"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#installation","text":"To run this notebook a simple Python environment with the following packages is required: - python=3.9 - pandas - geopandas - pyogrio - matplotlib - numpy - jupyter - xarray - openpyxl - pip - pip: - hydrolib-core==0.3.1 - meshkernel==1.0.0 Note that all participants received an e-mail to download the material from the Deltares download portal and to create a Conda environment with the packages automatically installed from environment.yml . Furthermore, a dummy model is provided at the download portal to test the environment.","title":"Installation"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#tips-for-working-in-the-jupyter-notebook","text":"Tab : Auto-complete on code Shift + Tab : Tooltip Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell Ctrl + Shift + P : Open command palette Let's get started!","title":"Tips for working in the Jupyter Notebook:"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#loading-libraries","text":"Several Python packages are required to run the notebook. These packages are imported below. Please consult the HYDROLIB-core documentation if you want to import additional HYDROLIB-core functionalities later. The import of HYDROLIB-core packages will be simplied in future HYDROLIB-core release (> 0.3.1) In [ ]: Copied! # basic packages import numpy as np import pandas as pd import matplotlib.pyplot as plt # I/O from pathlib import Path # vector/polygon packages import geopandas as gpd from shapely import wkt from shapely.geometry import box # HYDROLIB-core libraries from hydrolib.core.mdu.models import FMModel , AutoStartOption from hydrolib.core.net.models import * from hydrolib.core.crosssection.models import CrossLocModel , CrossDefModel , CrossSection , YZCrsDef from hydrolib.core.friction.models import * from hydrolib.core.bc.models import * from hydrolib.core.ext.models import * from hydrolib.core.inifield.models import * from hydrolib.core.onedfield.models import * from hydrolib.core.structure.models import Weir , FlowDirection , StructureModel # basic packages import numpy as np import pandas as pd import matplotlib.pyplot as plt # I/O from pathlib import Path # vector/polygon packages import geopandas as gpd from shapely import wkt from shapely.geometry import box # HYDROLIB-core libraries from hydrolib.core.mdu.models import FMModel, AutoStartOption from hydrolib.core.net.models import * from hydrolib.core.crosssection.models import CrossLocModel, CrossDefModel, CrossSection, YZCrsDef from hydrolib.core.friction.models import * from hydrolib.core.bc.models import * from hydrolib.core.ext.models import * from hydrolib.core.inifield.models import * from hydrolib.core.onedfield.models import * from hydrolib.core.structure.models import Weir, FlowDirection, StructureModel","title":"Loading libraries"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#connect-to-data","text":"The data for this tutorial is provided via the download portal. EX1 : Change the inputdir to the path of your unzipped data folder. In [ ]: Copied! # Get the directory of the notebook location root = Path . cwd () # Answer EX1 # Specify the path to the data folder inputdir = # Get the directory of the notebook location root = Path.cwd() # Answer EX1 # Specify the path to the data folder inputdir =","title":"Connect to data"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#create-empty-d-flow-fm-model","text":"To start a model from scratch you need to create first an empty model without data and assign a filepath to the model. In this case a D-Flow FM model is created. The MDU file (master definition file) is the main file of the D-Flow FM model. This is created with the FMModel() function. The fm model object is only created in memory. To save the actual model file, call fm.save() . EX2 : Set the outputdir of the model and give it a name. Verify that an MDU file has been written in your output directory. In [ ]: Copied! # Create empty D-Flow FM model fm = FMModel () # Answer EX2 # Assign filepath to the D-Flow FM model outputdir = fm . filepath = outputdir / 'Magdalena_1D.mdu' fm . save () # Create empty D-Flow FM model fm = FMModel() # Answer EX2 # Assign filepath to the D-Flow FM model outputdir = fm.filepath = outputdir / 'Magdalena_1D.mdu' fm.save()","title":"Create empty D-Flow FM model"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#part-1-set-up-a-1d-delft3d-fm-model","text":"In this part we will build up the complete 1D model schematization step by step. At the end you should have a complete set of model input files for a 1D calculation.","title":"PART 1: Set up a 1D Delft3D FM model"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#read-branches","text":"The model will include the lower part of the Magadalena from Cordoba Teton to the river mouth Baranquilla and the Canal del Dique. EX2 : Please investigate the branches variable and answer the following questions for yourself: How many river branches does the model have? What are their names? Which friction type and values are used for each branch? In [ ]: Copied! # Read the branches branches = gpd . read_file ( filename = inputdir / 'branches_Branches.shp' ) # Answer EX3 # Read the branches branches = gpd.read_file(filename = inputdir / 'branches_Branches.shp') # Answer EX3","title":"Read branches"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#create-1d-computational-grid","text":"In the previous step you read the geometry and attributes of the branches into the notebook. These branches will become the network input to our FMModel . The cell below shows how the geometry and name of the branches are assigned to the network. In addition a 1D computational grid ( mesh1d ) with gridpoint every 1000 meter is created on top of this network. Since the network does not yet exist, you need to create an empty network model . Assign the geometry of the branches followed by the generation of the computational grid. The network model should be added to the D-Flow FM model ( fm variable in this notebook) as network in the netfile parameter in the section geometry . Note that you have to specify a filepath for the networkfile. Note that the network model can consist of 1D, 2D flexible mesh ( mesh2d ) and 1D2D links ( links1d2d ). In [ ]: Copied! # Specify 1D computational grid distance dx = 1000.0 # Create an empty network network = Network () # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch in branches . iterrows (): xy = np . transpose ( branch . geometry . xy ) branch_new = Branch ( geometry = xy ) branch_new . generate_nodes ( mesh1d_edge_length = dx ) network . mesh1d_add_branch ( branch_new , name = branch . Name ) # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm . geometry . netfile . network = network fm . geometry . netfile . filepath = \"FlowFM_net.nc\" # Specify 1D computational grid distance dx = 1000.0 # Create an empty network network = Network() # Assign geometry of the branches and generate the computational grid on top of the branches. for index,branch in branches.iterrows(): xy = np.transpose(branch.geometry.xy) branch_new = Branch(geometry=xy) branch_new.generate_nodes(mesh1d_edge_length=dx) network.mesh1d_add_branch(branch_new, name=branch.Name) # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm.geometry.netfile.network = network fm.geometry.netfile.filepath = \"FlowFM_net.nc\" EX3 : Please change the computational grid distance of each branch accordingly: Branch name dx [m] Channel_1D_1_A 1000 Channel_1D_1_B 1000 Channel_1D 500 Tip : Do not forget to create a new network. In [ ]: Copied! # Answer EX3 # Specify 1D computational grid distance dx = # Create an empty network # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch in branches . iterrows (): xy = np . transpose ( branch . geometry . xy ) branch_new = Branch ( geometry = xy ) branch_new . generate_nodes ( mesh1d_edge_length = dx ) network . mesh1d_add_branch ( branch_new , name = branch . Name ) network . _mesh1d . _set_mesh1d () # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm . geometry . netfile . network = fm . geometry . netfile . filepath = # Answer EX3 # Specify 1D computational grid distance dx = # Create an empty network # Assign geometry of the branches and generate the computational grid on top of the branches. for index,branch in branches.iterrows(): xy = np.transpose(branch.geometry.xy) branch_new = Branch(geometry=xy) branch_new.generate_nodes(mesh1d_edge_length=dx) network.mesh1d_add_branch(branch_new, name=branch.Name) network._mesh1d._set_mesh1d() # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm.geometry.netfile.network = fm.geometry.netfile.filepath = The 1D branches are plotted on a map in the figure below. Also, the computational grid points in the mesh1d definition are shown. In [ ]: Copied! # Create a figure with the flowlinks of the model figure , ( ax1 , ax2 ) = plt . subplots ( ncols = 2 ) img = plt . imread ( inputdir / \"osm_background.png\" ) mesh1d_meshkernel = network . _mesh1d . _get_mesh1d () ax1 . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) mesh1d_meshkernel . plot_edges ( ax = ax1 , color = 'red' ) # Add some annotation of branches: for index , branch in branches . iterrows (): middleIndex = int (( len ( branch [ 'geometry' ] . coords ) - 1 ) / 2 ) ax1 . text ( branch [ 'geometry' ] . xy [ 0 ][ middleIndex ], branch [ 'geometry' ] . xy [ 1 ][ middleIndex ], branch [ 'Name' ], ha = 'right' ) # Make a second plot with a zoom-in view of the computational grid points near the junction ax2 . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) ax2 . set_xlim ([ 500000 , 525000 ]) ax2 . set_ylim ([ 1125000 , 1150000 ]) mesh1d_meshkernel . plot_edges ( ax = ax2 , color = 'red' , marker = '.' , markeredgecolor = 'k' , markersize = 1 ) # Create a figure with the flowlinks of the model figure, (ax1, ax2) = plt.subplots(ncols=2) img = plt.imread(inputdir/\"osm_background.png\") mesh1d_meshkernel = network._mesh1d._get_mesh1d() ax1.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) mesh1d_meshkernel.plot_edges(ax=ax1, color='red') # Add some annotation of branches: for index,branch in branches.iterrows(): middleIndex = int((len(branch['geometry'].coords) - 1)/2) ax1.text(branch['geometry'].xy[0][middleIndex], branch['geometry'].xy[1][middleIndex], branch['Name'], ha='right') # Make a second plot with a zoom-in view of the computational grid points near the junction ax2.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) ax2.set_xlim([500000, 525000]) ax2.set_ylim([1125000 ,1150000]) mesh1d_meshkernel.plot_edges(ax=ax2, color='red',marker='.',markeredgecolor='k',markersize=1)","title":"Create 1D computational grid"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#add-cross-sections","text":"In order to determine the flow area of the 1D model during the computation, you need cross-sections. These cross-sections consist of two components: Cross-section locations ( crosslocfile ): The crosslocfile contains the location of the cross-section on the branches. This is indicated with branchId chainage , where branchId is the name of the branch and chainage the distance to the upstream node. The figure below shows the cross-section locations in grey. In addition the cross-section location consist of the cross-section definition used at that location and a vertical shift of the profile. The latter is mainly used to create a good longitudinal slope over the 1D model (in case of shared cross-sections).

    Cross-section definitions ( crossdeffile ): The crossdeffile has the cross-section definitions in it. These definitions describe the shape of the profile. There are multiple types available: circle, rectangle, ZW- (tabulated), YZ- and XYZ-profiles. Depending on what type of watersystem you try to model you decide which cross-section to use. We recommend to use ZW- or YZ-profiles for rivers.

    ","title":"Add cross-sections"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/","text":"(function (global, factory) { typeof exports === 'object' && typeof module !== 'undefined' ? module.exports = factory() : typeof define === 'function' && define.amd ? define(factory) : (global = global || self, global.ClipboardCopyElement = factory()); }(this, function () { 'use strict'; function createNode(text) { const node = document.createElement('pre'); node.style.width = '1px'; node.style.height = '1px'; node.style.position = 'fixed'; node.style.top = '5px'; node.textContent = text; return node; } function copyNode(node) { if ('clipboard' in navigator) { // eslint-disable-next-line flowtype/no-flow-fix-me-comments // $FlowFixMe Clipboard is not defined in Flow yet. return navigator.clipboard.writeText(node.textContent); } const selection = getSelection(); if (selection == null) { return Promise.reject(new Error()); } selection.removeAllRanges(); const range = document.createRange(); range.selectNodeContents(node); selection.addRange(range); document.execCommand('copy'); selection.removeAllRanges(); return Promise.resolve(); } function copyText(text) { if ('clipboard' in navigator) { // eslint-disable-next-line flowtype/no-flow-fix-me-comments // $FlowFixMe Clipboard is not defined in Flow yet. return navigator.clipboard.writeText(text); } const body = document.body; if (!body) { return Promise.reject(new Error()); } const node = createNode(text); body.appendChild(node); copyNode(node); body.removeChild(node); return Promise.resolve(); } function copy(button) { const id = button.getAttribute('for'); const text = button.getAttribute('value'); function trigger() { button.dispatchEvent(new CustomEvent('clipboard-copy', { bubbles: true })); } if (text) { copyText(text).then(trigger); } else if (id) { const root = 'getRootNode' in Element.prototype ? button.getRootNode() : button.ownerDocument; if (!(root instanceof Document || 'ShadowRoot' in window && root instanceof ShadowRoot)) return; const node = root.getElementById(id); if (node) copyTarget(node).then(trigger); } } function copyTarget(content) { if (content instanceof HTMLInputElement || content instanceof HTMLTextAreaElement) { return copyText(content.value); } else if (content instanceof HTMLAnchorElement && content.hasAttribute('href')) { return copyText(content.href); } else { return copyNode(content); } } function clicked(event) { const button = event.currentTarget; if (button instanceof HTMLElement) { copy(button); } } function keydown(event) { if (event.key === ' ' || event.key === 'Enter') { const button = event.currentTarget; if (button instanceof HTMLElement) { event.preventDefault(); copy(button); } } } function focused(event) { event.currentTarget.addEventListener('keydown', keydown); } function blurred(event) { event.currentTarget.removeEventListener('keydown', keydown); } class ClipboardCopyElement extends HTMLElement { constructor() { super(); this.addEventListener('click', clicked); this.addEventListener('focus', focused); this.addEventListener('blur', blurred); } connectedCallback() { if (!this.hasAttribute('tabindex')) { this.setAttribute('tabindex', '0'); } if (!this.hasAttribute('role')) { this.setAttribute('role', 'button'); } } get value() { return this.getAttribute('value') || ''; } set value(text) { this.setAttribute('value', text); } } if (!window.customElements.get('clipboard-copy')) { window.ClipboardCopyElement = ClipboardCopyElement; window.customElements.define('clipboard-copy', ClipboardCopyElement); } return ClipboardCopyElement; })); document.addEventListener('clipboard-copy', function(event) { const notice = event.target.querySelector('.notice') notice.hidden = false setTimeout(function() { notice.hidden = true }, 1000) }) pre { line-height: 125%; } td.linenos .normal { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; } span.linenos { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; } td.linenos .special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; } span.linenos.special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; } .highlight-ipynb .hll { background-color: var(--jp-cell-editor-active-background) } .highlight-ipynb { background: var(--jp-cell-editor-background); color: var(--jp-mirror-editor-variable-color) } .highlight-ipynb .c { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment */ .highlight-ipynb .err { color: var(--jp-mirror-editor-error-color) } /* Error */ .highlight-ipynb .k { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword */ .highlight-ipynb .o { color: var(--jp-mirror-editor-operator-color); font-weight: bold } /* Operator */ .highlight-ipynb .p { color: var(--jp-mirror-editor-punctuation-color) } /* Punctuation */ .highlight-ipynb .ch { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Hashbang */ .highlight-ipynb .cm { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Multiline */ .highlight-ipynb .cp { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Preproc */ .highlight-ipynb .cpf { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.PreprocFile */ .highlight-ipynb .c1 { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Single */ .highlight-ipynb .cs { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Special */ .highlight-ipynb .kc { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Constant */ .highlight-ipynb .kd { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Declaration */ .highlight-ipynb .kn { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Namespace */ .highlight-ipynb .kp { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Pseudo */ .highlight-ipynb .kr { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Reserved */ .highlight-ipynb .kt { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Type */ .highlight-ipynb .m { color: var(--jp-mirror-editor-number-color) } /* Literal.Number */ .highlight-ipynb .s { color: var(--jp-mirror-editor-string-color) } /* Literal.String */ .highlight-ipynb .ow { color: var(--jp-mirror-editor-operator-color); font-weight: bold } /* Operator.Word */ .highlight-ipynb .pm { color: var(--jp-mirror-editor-punctuation-color) } /* Punctuation.Marker */ .highlight-ipynb .w { color: var(--jp-mirror-editor-variable-color) } /* Text.Whitespace */ .highlight-ipynb .mb { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Bin */ .highlight-ipynb .mf { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Float */ .highlight-ipynb .mh { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Hex */ .highlight-ipynb .mi { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Integer */ .highlight-ipynb .mo { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Oct */ .highlight-ipynb .sa { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Affix */ .highlight-ipynb .sb { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Backtick */ .highlight-ipynb .sc { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Char */ .highlight-ipynb .dl { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Delimiter */ .highlight-ipynb .sd { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Doc */ .highlight-ipynb .s2 { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Double */ .highlight-ipynb .se { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Escape */ .highlight-ipynb .sh { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Heredoc */ .highlight-ipynb .si { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Interpol */ .highlight-ipynb .sx { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Other */ .highlight-ipynb .sr { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Regex */ .highlight-ipynb .s1 { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Single */ .highlight-ipynb .ss { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Symbol */ .highlight-ipynb .il { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Integer.Long */ /* This file is taken from the built JupyterLab theme.css Found on share/nbconvert/templates/lab/static Some changes have been made and marked with CHANGE */ .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ --jp-shadow-base-lightness: 0; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-400); --jp-border-color1: var(--md-grey-400); --jp-border-color2: var(--md-grey-300); --jp-border-color3: var(--md-grey-200); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(0, 0, 0, 1); --jp-ui-font-color1: rgba(0, 0, 0, 0.87); --jp-ui-font-color2: rgba(0, 0, 0, 0.54); --jp-ui-font-color3: rgba(0, 0, 0, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color1: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color2: rgba(255, 255, 255, 0.7); --jp-ui-inverse-font-color3: rgba(255, 255, 255, 0.5); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(0, 0, 0, 1); --jp-content-font-color1: rgba(0, 0, 0, 0.87); --jp-content-font-color2: rgba(0, 0, 0, 0.54); --jp-content-font-color3: rgba(0, 0, 0, 0.38); --jp-content-link-color: var(--md-blue-700); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: white; --jp-layout-color1: white; --jp-layout-color2: var(--md-grey-200); --jp-layout-color3: var(--md-grey-400); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: #111111; --jp-inverse-layout-color1: var(--md-grey-900); --jp-inverse-layout-color2: var(--md-grey-800); --jp-inverse-layout-color3: var(--md-grey-700); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-900); --jp-brand-color1: var(--md-blue-700); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-900); --jp-accent-color1: var(--md-green-700); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-900); --jp-warn-color1: var(--md-orange-700); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-900); --jp-error-color1: var(--md-red-700); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-900); --jp-success-color1: var(--md-green-700); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-900); --jp-info-color1: var(--md-cyan-700); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--md-grey-100); --jp-cell-editor-border-color: var(--md-grey-300); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 0.5; --jp-cell-prompt-not-active-font-color: var(--md-grey-700); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: var(--md-blue-50); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: #fdd; --jp-rendermime-table-row-background: var(--md-grey-100); --jp-rendermime-table-row-hover-background: var(--md-light-blue-50); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.25); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color1); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.24); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--md-grey-300); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color1); --jp-input-hover-background: var(--jp-layout-color1); --jp-input-background: var(--md-grey-100); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: #d9d9d9; --jp-editor-selected-focused-background: #d7d4f0; --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: #008000; --jp-mirror-editor-atom-color: #88f; --jp-mirror-editor-number-color: #080; --jp-mirror-editor-def-color: #00f; --jp-mirror-editor-variable-color: var(--md-grey-900); --jp-mirror-editor-variable-2-color: #05a; --jp-mirror-editor-variable-3-color: #085; --jp-mirror-editor-punctuation-color: #05a; --jp-mirror-editor-property-color: #05a; --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ba2121; --jp-mirror-editor-string-2-color: #708; --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: #008000; --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: #170; --jp-mirror-editor-attribute-color: #00c; --jp-mirror-editor-header-color: blue; --jp-mirror-editor-quote-color: #090; --jp-mirror-editor-link-color: #00c; --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: white; /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.5; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(245, 200, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } [data-md-color-scheme=\"slate\"] .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ /* The dark theme shadows need a bit of work, but this will probably also require work on the core layout * colors used in the theme as well. */ --jp-shadow-base-lightness: 32; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-700); --jp-border-color1: var(--md-grey-700); --jp-border-color2: var(--md-grey-800); --jp-border-color3: var(--md-grey-900); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(255, 255, 255, 1); --jp-ui-font-color1: rgba(255, 255, 255, 0.87); --jp-ui-font-color2: rgba(255, 255, 255, 0.54); --jp-ui-font-color3: rgba(255, 255, 255, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(0, 0, 0, 1); --jp-ui-inverse-font-color1: rgba(0, 0, 0, 0.8); --jp-ui-inverse-font-color2: rgba(0, 0, 0, 0.5); --jp-ui-inverse-font-color3: rgba(0, 0, 0, 0.3); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(255, 255, 255, 1); --jp-content-font-color1: rgba(255, 255, 255, 1); --jp-content-font-color2: rgba(255, 255, 255, 0.7); --jp-content-font-color3: rgba(255, 255, 255, 0.5); --jp-content-link-color: var(--md-blue-300); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: #111111; --jp-layout-color1: var(--md-grey-900); --jp-layout-color2: var(--md-grey-800); --jp-layout-color3: var(--md-grey-700); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: white; --jp-inverse-layout-color1: white; --jp-inverse-layout-color2: var(--md-grey-200); --jp-inverse-layout-color3: var(--md-grey-400); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-700); --jp-brand-color1: var(--md-blue-500); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-700); --jp-accent-color1: var(--md-green-500); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-700); --jp-warn-color1: var(--md-orange-500); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-700); --jp-error-color1: var(--md-red-500); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-700); --jp-success-color1: var(--md-green-500); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-700); --jp-info-color1: var(--md-cyan-500); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--jp-layout-color1); --jp-cell-editor-border-color: var(--md-grey-700); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 1; --jp-cell-prompt-not-active-font-color: var(--md-grey-300); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: rgba(33, 150, 243, 0.24); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: rgba(244, 67, 54, 0.28); --jp-rendermime-table-row-background: var(--md-grey-900); --jp-rendermime-table-row-hover-background: rgba(3, 169, 244, 0.2); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.6); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color2); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.8); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--jp-layout-color0); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color0); --jp-input-hover-background: var(--jp-layout-color2); --jp-input-background: var(--md-grey-800); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: var(--jp-layout-color2); --jp-editor-selected-focused-background: rgba(33, 150, 243, 0.24); --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: var(--md-green-500); --jp-mirror-editor-atom-color: var(--md-blue-300); --jp-mirror-editor-number-color: var(--md-green-400); --jp-mirror-editor-def-color: var(--md-blue-600); --jp-mirror-editor-variable-color: var(--md-grey-300); --jp-mirror-editor-variable-2-color: var(--md-blue-400); --jp-mirror-editor-variable-3-color: var(--md-green-600); --jp-mirror-editor-punctuation-color: var(--md-blue-400); --jp-mirror-editor-property-color: var(--md-blue-400); --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ff7070; --jp-mirror-editor-string-2-color: var(--md-purple-300); --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: var(--md-green-600); --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: var(--md-green-700); --jp-mirror-editor-attribute-color: var(--md-blue-700); --jp-mirror-editor-header-color: var(--md-blue-500); --jp-mirror-editor-quote-color: var(--md-green-300); --jp-mirror-editor-link-color: var(--md-blue-700); --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: var(--md-grey-400); /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.6; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(255, 225, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* scrollbar related styles. Supports every browser except Edge. */ /* colors based on JetBrain's Darcula theme */ --jp-scrollbar-background-color: #3f4244; --jp-scrollbar-thumb-color: 88, 96, 97; /* need to specify thumb color as an RGB triplet */ --jp-scrollbar-endpad: 3px; /* the minimum gap between the thumb and the ends of a scrollbar */ /* hacks for setting the thumb shape. These do nothing in Firefox */ --jp-scrollbar-thumb-margin: 3.5px; /* the space in between the sides of the thumb and the track */ --jp-scrollbar-thumb-radius: 9px; /* set to a large-ish value for rounded endcaps on the thumb */ /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } :root{--md-red-50: #ffebee;--md-red-100: #ffcdd2;--md-red-200: #ef9a9a;--md-red-300: #e57373;--md-red-400: #ef5350;--md-red-500: #f44336;--md-red-600: #e53935;--md-red-700: #d32f2f;--md-red-800: #c62828;--md-red-900: #b71c1c;--md-red-A100: #ff8a80;--md-red-A200: #ff5252;--md-red-A400: #ff1744;--md-red-A700: #d50000;--md-pink-50: #fce4ec;--md-pink-100: #f8bbd0;--md-pink-200: #f48fb1;--md-pink-300: #f06292;--md-pink-400: #ec407a;--md-pink-500: #e91e63;--md-pink-600: #d81b60;--md-pink-700: #c2185b;--md-pink-800: #ad1457;--md-pink-900: #880e4f;--md-pink-A100: #ff80ab;--md-pink-A200: #ff4081;--md-pink-A400: #f50057;--md-pink-A700: #c51162;--md-purple-50: #f3e5f5;--md-purple-100: #e1bee7;--md-purple-200: #ce93d8;--md-purple-300: #ba68c8;--md-purple-400: #ab47bc;--md-purple-500: #9c27b0;--md-purple-600: #8e24aa;--md-purple-700: #7b1fa2;--md-purple-800: #6a1b9a;--md-purple-900: #4a148c;--md-purple-A100: #ea80fc;--md-purple-A200: #e040fb;--md-purple-A400: #d500f9;--md-purple-A700: #aa00ff;--md-deep-purple-50: #ede7f6;--md-deep-purple-100: #d1c4e9;--md-deep-purple-200: #b39ddb;--md-deep-purple-300: #9575cd;--md-deep-purple-400: #7e57c2;--md-deep-purple-500: #673ab7;--md-deep-purple-600: #5e35b1;--md-deep-purple-700: #512da8;--md-deep-purple-800: #4527a0;--md-deep-purple-900: #311b92;--md-deep-purple-A100: #b388ff;--md-deep-purple-A200: #7c4dff;--md-deep-purple-A400: #651fff;--md-deep-purple-A700: #6200ea;--md-indigo-50: #e8eaf6;--md-indigo-100: #c5cae9;--md-indigo-200: #9fa8da;--md-indigo-300: #7986cb;--md-indigo-400: #5c6bc0;--md-indigo-500: #3f51b5;--md-indigo-600: #3949ab;--md-indigo-700: #303f9f;--md-indigo-800: #283593;--md-indigo-900: #1a237e;--md-indigo-A100: #8c9eff;--md-indigo-A200: #536dfe;--md-indigo-A400: #3d5afe;--md-indigo-A700: #304ffe;--md-blue-50: #e3f2fd;--md-blue-100: #bbdefb;--md-blue-200: #90caf9;--md-blue-300: #64b5f6;--md-blue-400: #42a5f5;--md-blue-500: #2196f3;--md-blue-600: #1e88e5;--md-blue-700: #1976d2;--md-blue-800: #1565c0;--md-blue-900: #0d47a1;--md-blue-A100: #82b1ff;--md-blue-A200: #448aff;--md-blue-A400: #2979ff;--md-blue-A700: #2962ff;--md-light-blue-50: #e1f5fe;--md-light-blue-100: #b3e5fc;--md-light-blue-200: #81d4fa;--md-light-blue-300: #4fc3f7;--md-light-blue-400: #29b6f6;--md-light-blue-500: #03a9f4;--md-light-blue-600: #039be5;--md-light-blue-700: #0288d1;--md-light-blue-800: #0277bd;--md-light-blue-900: #01579b;--md-light-blue-A100: #80d8ff;--md-light-blue-A200: #40c4ff;--md-light-blue-A400: #00b0ff;--md-light-blue-A700: #0091ea;--md-cyan-50: #e0f7fa;--md-cyan-100: #b2ebf2;--md-cyan-200: #80deea;--md-cyan-300: #4dd0e1;--md-cyan-400: #26c6da;--md-cyan-500: #00bcd4;--md-cyan-600: #00acc1;--md-cyan-700: #0097a7;--md-cyan-800: #00838f;--md-cyan-900: #006064;--md-cyan-A100: #84ffff;--md-cyan-A200: #18ffff;--md-cyan-A400: #00e5ff;--md-cyan-A700: #00b8d4;--md-teal-50: #e0f2f1;--md-teal-100: #b2dfdb;--md-teal-200: #80cbc4;--md-teal-300: #4db6ac;--md-teal-400: #26a69a;--md-teal-500: #009688;--md-teal-600: #00897b;--md-teal-700: #00796b;--md-teal-800: #00695c;--md-teal-900: #004d40;--md-teal-A100: #a7ffeb;--md-teal-A200: #64ffda;--md-teal-A400: #1de9b6;--md-teal-A700: #00bfa5;--md-green-50: #e8f5e9;--md-green-100: #c8e6c9;--md-green-200: #a5d6a7;--md-green-300: #81c784;--md-green-400: #66bb6a;--md-green-500: #4caf50;--md-green-600: #43a047;--md-green-700: #388e3c;--md-green-800: #2e7d32;--md-green-900: #1b5e20;--md-green-A100: #b9f6ca;--md-green-A200: #69f0ae;--md-green-A400: #00e676;--md-green-A700: 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sourceMappingURL=mkdocs-jupyter.css.map*/ init_mathjax = function() { if (window.MathJax) { // MathJax loaded MathJax.Hub.Config({ TeX: { equationNumbers: { autoNumber: \"AMS\", useLabelIds: true } }, tex2jax: { inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ], displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ], processEscapes: true, processEnvironments: true }, displayAlign: 'center', CommonHTML: { linebreaks: { automatic: true } } }); MathJax.Hub.Queue([\"Typeset\", MathJax.Hub]); } } init_mathjax(); Tutorial Delft3D FM 1D2D fluvial flood model of Magdalena river \u00b6 This notebook is an introduction on how to use HYDROLIB-core functionalities to create and adjust a Delft3D FM Suite 1D2D fluvial flood model of the Magdalena river in Columbia. First a 1D river model of the Magdalena river and Canal del Dique will be created, shown in the left figure. This model will be extended with a 2D Flexible Mesh, with a uniform roughness field. Adding a DTM on that 2D mesh is currently not part of this tutorial, but normally this is of course indispensible to mimic the fluvial flood patterns. Running the model or importing the model in the Delft3D FM Suite 1D2D is not shown in this tutorial. Note that the model and tutorial are created for educational purposes and consist partially of fictive/unvalidated model data. HYDROLIB-core is the core library of Python wrappers around the D-HYDRO Suite 1D2D model files (input and output) and model engines (kernel libraries). HYDROLIB is a Python package with tools for pre-processing, post-processing and analysis of hydrodynamical data and simulation results, currently focused on Delft3D Suite 1D2D. HYDROLIB builds upon the basic HYDROLIB-core functionalities. The goal of this tutorial is to familiarize modelers with how to apply HYDROLIB-core functionalities in their modelling procedures for building new models or adjusting existing models. As mentioned above, you will create an 1D2D fluvial flood model from scratch using the D-Flow FM HYDROLIB-core functionalities and the underlying functions from mesh generation ( MeshKernelPy ). The building of the model is done by the following steps Loading libraries Connect to data folder Create empty D-Flow FM model Read branches Create computational grid Add cross-sections Add roughness Add boundary conditions Add initial conditions Add a weir to the model Save 1D model Create 2D flexible mesh Add 2D DTM to model Save 1D2D model Note that HYDROLIB-core also contains functionalities to setup lumped rainfall runoff models ( D-RR ) and to apply real-time control at structures ( D-RTC ), but these are not covered in this tutorial. Installation \u00b6 To run this notebook a simple Python environment with the following packages is required: - python=3.9 - pandas - geopandas - pyogrio - matplotlib - numpy - jupyter - xarray - openpyxl - pip - pip: - hydrolib-core==0.3.1 - meshkernel==1.0.0 Note that all participants received an e-mail to download the material from the Deltares download portal and to create a Conda environment with the packages automatically installed from environment.yml . Furthermore, a dummy model is provided at the download portal to test the environment. Tips for working in the Jupyter Notebook: \u00b6 Tab : Auto-complete on code Shift + Tab : Tooltip Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell Ctrl + Shift + P : Open command palette Let's get started! Loading libraries \u00b6 Several Python packages are required to run the notebook. These packages are imported below. Please consult the HYDROLIB-core documentation if you want to import additional HYDROLIB-core functionalities later. The import of HYDROLIB-core packages will be simplied in future HYDROLIB-core release (> 0.3.1) In [ ]: Copied! # basic packages import numpy as np import pandas as pd import matplotlib.pyplot as plt # I/O from pathlib import Path # vector/polygon packages import geopandas as gpd from shapely import wkt from shapely.geometry import box # HYDROLIB-core libraries from hydrolib.core.mdu.models import FMModel , AutoStartOption from hydrolib.core.net.models import * from hydrolib.core.crosssection.models import CrossLocModel , CrossDefModel , CrossSection , YZCrsDef from hydrolib.core.friction.models import * from hydrolib.core.bc.models import * from hydrolib.core.ext.models import * from hydrolib.core.inifield.models import * from hydrolib.core.onedfield.models import * from hydrolib.core.structure.models import Weir , FlowDirection , StructureModel # basic packages import numpy as np import pandas as pd import matplotlib.pyplot as plt # I/O from pathlib import Path # vector/polygon packages import geopandas as gpd from shapely import wkt from shapely.geometry import box # HYDROLIB-core libraries from hydrolib.core.mdu.models import FMModel, AutoStartOption from hydrolib.core.net.models import * from hydrolib.core.crosssection.models import CrossLocModel, CrossDefModel, CrossSection, YZCrsDef from hydrolib.core.friction.models import * from hydrolib.core.bc.models import * from hydrolib.core.ext.models import * from hydrolib.core.inifield.models import * from hydrolib.core.onedfield.models import * from hydrolib.core.structure.models import Weir, FlowDirection, StructureModel Connect to data \u00b6 The data for this tutorial is provided via the download portal. EX1 : Change the inputdir to the path of your unzipped data folder. In [ ]: Copied! # Get the directory of the notebook location root = Path . cwd () # Answer EX1 # Specify the path to the data folder inputdir = root / 'data' #inputdir = Path(r\"c:\\checkouts\\HYDROLIB-data_git\\magdalena\") # Get the directory of the notebook location root = Path.cwd() # Answer EX1 # Specify the path to the data folder inputdir = root / 'data' #inputdir = Path(r\"c:\\checkouts\\HYDROLIB-data_git\\magdalena\") Create empty D-Flow FM model \u00b6 To start a model from scratch you need to create first an empty model without data and assign a filepath to the model. In this case a D-Flow FM model is created. The MDU file (master definition file) is the main file of the D-Flow FM model. This is created with the FMModel() function. The fm model object is only created in memory. To save the actual model file, call fm.save() . EX2 : Set the outputdir of the model and give it a name. Verify that an MDU file has been written in your output directory. In [ ]: Copied! # Create empty D-Flow FM model fm = FMModel () # Answer EX2 # Assign filepath to the D-Flow FM model outputdir = root / '1D_model' fm . filepath = outputdir / 'Magdalena_1D.mdu' fm . save () # Create empty D-Flow FM model fm = FMModel() # Answer EX2 # Assign filepath to the D-Flow FM model outputdir = root / '1D_model' fm.filepath = outputdir / 'Magdalena_1D.mdu' fm.save() PART 1: Set up a 1D Delft3D FM model \u00b6 In this part we will build up the complete 1D model schematization step by step. At the end you should have a complete set of model input files for a 1D calculation. Read branches \u00b6 The model will include the lower part of the Magadalena from Cordoba Teton to the river mouth Baranquilla and the Canal del Dique. EX2 : Please investigate the branches variable and answer the following questions for yourself: How many river branches does the model have? What are their names? Which friction type and values are used for each branch? In [ ]: Copied! # Read the branches branches = gpd . read_file ( filename = inputdir / 'branches_Branches.shp' ) # Answer EX3 print ( branches . head ()) # To show the first part of the dataframe print ( branches . Name ) # To get the names of the branches # The model consist of 3 branches # The names of these branches are Channel_1D_1_A, Channel_1D_1_B and Channel_1D_1. # Manning is used as friction type. Branches Channel_1D_1_B and Channel_1D_1 have a friction value of 0.02. Branch Channel_1D_1_A has a value of 0.03. # Read the branches branches = gpd.read_file(filename = inputdir / 'branches_Branches.shp') # Answer EX3 print(branches.head()) # To show the first part of the dataframe print(branches.Name) # To get the names of the branches # The model consist of 3 branches # The names of these branches are Channel_1D_1_A, Channel_1D_1_B and Channel_1D_1. # Manning is used as friction type. Branches Channel_1D_1_B and Channel_1D_1 have a friction value of 0.02. Branch Channel_1D_1_A has a value of 0.03. Create 1D computational grid \u00b6 In the previous step you read the geometry and attributes of the branches into the notebook. These branches will become the network input to our FMModel . The cell below shows how the geometry and name of the branches are assigned to the network. In addition a 1D computational grid ( mesh1d ) with gridpoint every 1000 meter is created on top of this network. Since the network does not yet exist, you need to create an empty network model . Assign the geometry of the branches followed by the generation of the computational grid. The network model should be added to the D-Flow FM model ( fm variable in this notebook) as network in the netfile parameter in the section geometry . Note that you have to specify a filepath for the networkfile. Note that the network model can consist of 1D, 2D flexible mesh ( mesh2d ) and 1D2D links ( links1d2d ). In [ ]: Copied! # Specify 1D computational grid distance dx = 1000.0 # Create an empty network network = Network () # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch in branches . iterrows (): xy = np . transpose ( branch . geometry . xy ) branch_new = Branch ( geometry = xy ) branch_new . generate_nodes ( mesh1d_edge_length = dx ) network . mesh1d_add_branch ( branch_new , name = branch . Name ) # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm . geometry . netfile . network = network fm . geometry . netfile . filepath = \"FlowFM_net.nc\" # Specify 1D computational grid distance dx = 1000.0 # Create an empty network network = Network() # Assign geometry of the branches and generate the computational grid on top of the branches. for index,branch in branches.iterrows(): xy = np.transpose(branch.geometry.xy) branch_new = Branch(geometry=xy) branch_new.generate_nodes(mesh1d_edge_length=dx) network.mesh1d_add_branch(branch_new, name=branch.Name) # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm.geometry.netfile.network = network fm.geometry.netfile.filepath = \"FlowFM_net.nc\" EX3 : Please change the computational grid distance of each branch accordingly: Branch name dx [m] Channel_1D_1_A 1000 Channel_1D_1_B 1000 Channel_1D 500 Tip : Do not forget to create a new network. In [ ]: Copied! # Answer EX3 # Specify 1D computational grid distance dx = [ 1000. , 1000. , 500. ] # Create an empty network network = Network () # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch in branches . iterrows (): xy = np . transpose ( branch . geometry . xy ) branch_new = Branch ( geometry = xy ) branch_new . generate_nodes ( mesh1d_edge_length = dx [ index ]) network . mesh1d_add_branch ( branch_new , name = branch . Name ) network . _mesh1d . _set_mesh1d () # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm . geometry . netfile . network = network fm . geometry . netfile . filepath = \"FlowFM_EX3_net.nc\" # Answer EX3 # Specify 1D computational grid distance dx = [1000., 1000., 500.] # Create an empty network network = Network() # Assign geometry of the branches and generate the computational grid on top of the branches. for index,branch in branches.iterrows(): xy = np.transpose(branch.geometry.xy) branch_new = Branch(geometry=xy) branch_new.generate_nodes(mesh1d_edge_length=dx[index]) network.mesh1d_add_branch(branch_new, name=branch.Name) network._mesh1d._set_mesh1d() # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm.geometry.netfile.network = network fm.geometry.netfile.filepath = \"FlowFM_EX3_net.nc\" The 1D branches are plotted on a map in the figure below. Also, the computational grid points in the mesh1d definition are shown. In [ ]: Copied! # Create a figure with the flowlinks of the model figure , ( ax1 , ax2 ) = plt . subplots ( ncols = 2 ) img = plt . imread ( inputdir / \"osm_background.png\" ) mesh1d_meshkernel = network . _mesh1d . _get_mesh1d () ax1 . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) mesh1d_meshkernel . plot_edges ( ax = ax1 , color = 'red' ) # Add some annotation of branches: for index , branch in branches . iterrows (): middleIndex = int (( len ( branch [ 'geometry' ] . coords ) - 1 ) / 2 ) ax1 . text ( branch [ 'geometry' ] . xy [ 0 ][ middleIndex ], branch [ 'geometry' ] . xy [ 1 ][ middleIndex ], branch [ 'Name' ], ha = 'right' ) # Make a second plot with a zoom-in view of the computational grid points near the junction ax2 . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) ax2 . set_xlim ([ 500000 , 525000 ]) ax2 . set_ylim ([ 1125000 , 1150000 ]) mesh1d_meshkernel . plot_edges ( ax = ax2 , color = 'red' , marker = '.' , markeredgecolor = 'k' , markersize = 1 ) # Create a figure with the flowlinks of the model figure, (ax1, ax2) = plt.subplots(ncols=2) img = plt.imread(inputdir/\"osm_background.png\") mesh1d_meshkernel = network._mesh1d._get_mesh1d() ax1.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) mesh1d_meshkernel.plot_edges(ax=ax1, color='red') # Add some annotation of branches: for index,branch in branches.iterrows(): middleIndex = int((len(branch['geometry'].coords) - 1)/2) ax1.text(branch['geometry'].xy[0][middleIndex], branch['geometry'].xy[1][middleIndex], branch['Name'], ha='right') # Make a second plot with a zoom-in view of the computational grid points near the junction ax2.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) ax2.set_xlim([500000, 525000]) ax2.set_ylim([1125000 ,1150000]) mesh1d_meshkernel.plot_edges(ax=ax2, color='red',marker='.',markeredgecolor='k',markersize=1) Add cross-sections \u00b6 In order to determine the flow area of the 1D model during the computation, you need cross-sections. These cross-sections consist of two components: Cross-section locations ( crosslocfile ): The crosslocfile contains the location of the cross-section on the branches. This is indicated with branchId chainage , where branchId is the name of the branch and chainage the distance to the upstream node. The figure below shows the cross-section locations in grey. In addition the cross-section location consist of the cross-section definition used at that location and a vertical shift of the profile. The latter is mainly used to create a good longitudinal slope over the 1D model (in case of shared cross-sections).

    Cross-section definitions ( crossdeffile ): The crossdeffile has the cross-section definitions in it. These definitions describe the shape of the profile. There are multiple types available: circle, rectangle, ZW- (tabulated), YZ- and XYZ-profiles. Depending on what type of watersystem you try to model you decide which cross-section to use. We recommend to use ZW- or YZ-profiles for rivers.

    Add cross-section locations \u00b6 Below the cross-section locations are read from a CSV-file and added to an empty CrossLocModel . Note that the entire dataframe with the cross-section locations is converted at once to CrossLocModel. More about dataframe handling in HYDROLIB-core can be found here . EX4 : Please investigate the profile_loc variable and answer the following questions for yourself: How many cross-sections are there in the model and per branch? Check the chainage. Also print the cross-sections locations assigned to the D-Flow FM model. Use fm.geometry.crosslocfile.crosssection (part 2). What happens if you only print the first fm.geometry.crosslocfile In [ ]: Copied! # Read profile location file profiles_location_file = inputdir / 'cross_section_locations.csv' profiles_loc = pd . read_csv ( profiles_location_file , index_col = False ) # Answer EX4 - part 1 print ( profiles_loc . head ()) # There are 6 cross-sections in the model with 2 cross-sections per branch. # The chainage of the cross-sections indicate that the profiles are located upstream and downstream of the branch. # Create empty cross-section location model crsloc = CrossLocModel () # Assign filepath to the model crsloc . filepath = 'crsloc.ini' # Convert the dataframe crsloc . crosssection = profiles_loc . to_dict ( \"records\" ) # Assign CrossLocModel to the D-Flow FM model. fm . geometry . crosslocfile = crsloc # Answer EX4 - part 2 print ( fm . geometry . crosslocfile . crosssection ) print ( fm . geometry . crosslocfile ) # You only get filepath relatively to the MDU-file. # Read profile location file profiles_location_file = inputdir / 'cross_section_locations.csv' profiles_loc = pd.read_csv(profiles_location_file, index_col=False) # Answer EX4 - part 1 print(profiles_loc.head()) # There are 6 cross-sections in the model with 2 cross-sections per branch. # The chainage of the cross-sections indicate that the profiles are located upstream and downstream of the branch. # Create empty cross-section location model crsloc = CrossLocModel() # Assign filepath to the model crsloc.filepath = 'crsloc.ini' # Convert the dataframe crsloc.crosssection = profiles_loc.to_dict(\"records\") # Assign CrossLocModel to the D-Flow FM model. fm.geometry.crosslocfile = crsloc # Answer EX4 - part 2 print(fm.geometry.crosslocfile.crosssection) print(fm.geometry.crosslocfile) # You only get filepath relatively to the MDU-file. Add cross-section definitions \u00b6 In the following cell the definitions belonging to the cross-section locations are added to the D-Flow FM model. These cross-sections are all YZ-profiles in order to define natural shape of the river. Please see that the following steps are included: Read the cross-section definitions from an excel. Note that the cross-section definitions id's match with the definitions specified in the crossLocModel. Create an empty CrossDefModel and assign filepath Specify some characteristics for YZ profile. Please consult appendix C.16.1.6 from D-Flow FM 1D2D Create YZCrsDef for each profile definition. Append the definition to the CrossDefModel. Append the CrossDefModel to the D-Flow FM model. In [ ]: Copied! # Create cross-section definitions profiles_file = inputdir / '1D_YZ_CrossSections.xlsx' profiles = pd . read_excel ( profiles_file , sheet_name = None ) names = list ( profiles . keys ()) print ( names ) # Create empty CrossDefModel crsdef = CrossDefModel () crsdef . filepath = 'crsdef.ini' # Specify some charachteristics for YZ profile type_crs = 'yz' thalweg = 0.0 singleValued = 'yes' conveyance = 'segmented' sectionCount = 1 # Create the YZ profiles and append them to the CrossDefModel for name in names : yzCount = len ( profiles [ name ] . values ) ycoord = profiles [ name ] . y . to_list () zcoord = profiles [ name ] . z . to_list () frictionIds = 'channels' frictionPositions = [ profiles [ name ] . y [ 0 ], profiles [ name ] . y [ yzCount - 1 ]] crosssection = YZCrsDef ( id = name , type = type_crs , thalweg = thalweg , singleValuedZ = singleValued , conveyance = conveyance , yzCount = yzCount , yCoordinates = ycoord , zCoordinates = zcoord , sectionCount = sectionCount , frictionIds = frictionIds , frictionPositions = frictionPositions ) crsdef . definition . append ( crosssection ) print ( f 'definition of { name } added to cross-section model' ) # Append CrossDefModel to D-Flow FM model fm . geometry . crossdeffile = crsdef # Create cross-section definitions profiles_file = inputdir / '1D_YZ_CrossSections.xlsx' profiles = pd.read_excel(profiles_file, sheet_name=None) names = list(profiles.keys()) print(names) # Create empty CrossDefModel crsdef = CrossDefModel() crsdef.filepath = 'crsdef.ini' # Specify some charachteristics for YZ profile type_crs = 'yz' thalweg = 0.0 singleValued = 'yes' conveyance = 'segmented' sectionCount = 1 # Create the YZ profiles and append them to the CrossDefModel for name in names: yzCount = len(profiles[name].values) ycoord = profiles[name].y.to_list() zcoord = profiles[name].z.to_list() frictionIds = 'channels' frictionPositions = [profiles[name].y[0], profiles[name].y[yzCount-1]] crosssection = YZCrsDef(id=name, type=type_crs, thalweg=thalweg, singleValuedZ=singleValued, conveyance=conveyance, yzCount=yzCount, yCoordinates= ycoord, zCoordinates=zcoord, sectionCount=sectionCount, frictionIds = frictionIds, frictionPositions=frictionPositions) crsdef.definition.append(crosssection) print(f'definition of {name} added to cross-section model') # Append CrossDefModel to D-Flow FM model fm.geometry.crossdeffile = crsdef Add roughness \u00b6 The 1D model has now a network topology, computational 1D grid and cross-sections. Friction is a component that should be added to the model to get the proper bed roughness and channel conveyance. In this step you will add the FrictionModel to the D-Flow FM model by specifying the friction type and value at the upstream cross-section location (chainage=1000.0 m) of each branch in the model ( FrictBranch ). Also a global roughness section is specified ( FrictGlobal ). This global section is used when there is no friction type and values specified for a specific branch. It also contains the frictionId. In the cross-section definition model a reference is made to this frictionId. You can check this with the commands below and search for frictionIds . In [ ]: Copied! # Print directly the modelobject (in this case all definitions) print ( fm . geometry . crossdeffile . definition ) # Or convert it first to a dataframe df_def = pd . DataFrame ([ f . __dict__ for f in fm . geometry . crossdeffile . definition ]) print ( df_def [[ 'frictionids' ]]) # Print directly the modelobject (in this case all definitions) print(fm.geometry.crossdeffile.definition) # Or convert it first to a dataframe df_def = pd.DataFrame([f.__dict__ for f in fm.geometry.crossdeffile.definition]) print(df_def[['frictionids']]) Note that YZ profiles can refer to multiple frictionIds, since the friction can vary over the cross-section. Hence the frictionId is given in a List() . This means indirectly that multiple FrictionModels can be added to one D-Flow FM model. The created FrictionModel should therefore been added in a List() to the D-Flow FM model. In [ ]: Copied! # Specify frictionId(s) for the FrictionModel(s) friction_name = 'channels' # Specify for each FrictionModel a global type and value global_type = FrictionType . manning # Options are chezy,debosbijkerk, manning, strickler, stricklernikuradse, wallawnikuradse, whitecolebrook global_value = 0.023 # Create empty friction model and assign filepath roughness = FrictionModel () roughness . filepath = \"roughness-channels.ini\" # often we specify the filenames as \"roughness-frictionId.ini\" # Create global friction model and add it to frictionmodel roughness . global_ = FrictGlobal ( frictionId = friction_name , frictionType = global_type , frictionValue = global_value ) # Add friction from branches function_type = 'constant' # This model uses constant friction per branch df_friction = branches [[ 'Name' , 'fric_type' , 'fric_value' , 'chainage' ]] df_friction . columns = [ 'branchId' , 'frictionType' , 'frictionValues' , 'chainage' ] df_friction = df_friction . assign ( frictionValues = [[ i ] for i in df_friction . frictionValues . values ]) df_friction = df_friction . assign ( functionType = function_type ) df_friction = df_friction . assign ( chainage = [[ i ] for i in df_friction . chainage . values ]) df_friction = df_friction . assign ( numlocations = 1 ) # you can specify multiple location along the branch with different friction values. roughness . branch = df_friction . to_dict ( 'records' ) # the dataframe is converted to FrictBranch models at once # Add frictionmodel to the D-Flow FM model. fm . geometry . frictfile = [ roughness ] # frictfile is a list of frictionModels # Specify frictionId(s) for the FrictionModel(s) friction_name = 'channels' # Specify for each FrictionModel a global type and value global_type = FrictionType.manning # Options are chezy,debosbijkerk, manning, strickler, stricklernikuradse, wallawnikuradse, whitecolebrook global_value = 0.023 # Create empty friction model and assign filepath roughness = FrictionModel() roughness.filepath = \"roughness-channels.ini\" # often we specify the filenames as \"roughness-frictionId.ini\" # Create global friction model and add it to frictionmodel roughness.global_ = FrictGlobal(frictionId=friction_name,frictionType=global_type,frictionValue=global_value) # Add friction from branches function_type = 'constant' # This model uses constant friction per branch df_friction = branches[['Name', 'fric_type', 'fric_value', 'chainage']] df_friction.columns = ['branchId','frictionType','frictionValues', 'chainage'] df_friction = df_friction.assign(frictionValues = [[i] for i in df_friction.frictionValues.values]) df_friction = df_friction.assign(functionType=function_type) df_friction = df_friction.assign(chainage = [[i] for i in df_friction.chainage.values]) df_friction = df_friction.assign(numlocations=1) # you can specify multiple location along the branch with different friction values. roughness.branch = df_friction.to_dict('records') # the dataframe is converted to FrictBranch models at once # Add frictionmodel to the D-Flow FM model. fm.geometry.frictfile = [roughness] # frictfile is a list of frictionModels EX5 : Let's build another frictionmodel with frictionId dique representing the friction in Canal del Dique. This frictionmodel assumes Chezy as global friction type and has a friction value of 45. In [ ]: Copied! # Answer to EX5 # Specify frictionId(s) for the FrictionModel(s) friction_id2 = 'dique' # Specify for each FrictionModel a global type and value global_type2 = FrictionType . chezy global_value2 = 45.0 # Create empty friction model and assign filepath roughness_dique = FrictionModel () roughness_dique . filepath = 'roughness-dique.ini' # Create global friction model and add it to frictionmodel roughness_dique . global_ = FrictGlobal ( frictionId = friction_id2 , frictionType = global_type2 , frictionValue = global_value2 ) # Add frictionmodels to the D-Flow FM model. fm . geometry . frictfile = [ roughness , roughness_dique ] # Note that the other friction needs to be added to the list. # Answer to EX5 # Specify frictionId(s) for the FrictionModel(s) friction_id2 = 'dique' # Specify for each FrictionModel a global type and value global_type2 = FrictionType.chezy global_value2 = 45.0 # Create empty friction model and assign filepath roughness_dique = FrictionModel() roughness_dique.filepath = 'roughness-dique.ini' # Create global friction model and add it to frictionmodel roughness_dique.global_ = FrictGlobal(frictionId=friction_id2,frictionType=global_type2,frictionValue=global_value2) # Add frictionmodels to the D-Flow FM model. fm.geometry.frictfile = [roughness, roughness_dique] # Note that the other friction needs to be added to the list. The cross-sections on the Canal del Dique (Channel_1D_1) do not refer to this new frictionId. Please uncomment the code below to change this after completion of exercise 5. In [ ]: Copied! # Convert crosssection defintions from D-Flow FM model to dataframe df_def = pd . DataFrame ([ f . __dict__ for f in fm . geometry . crossdeffile . definition ]) print ( df_def ) # Check which cross-section locations are located on Channel_1D_1 df_loc = pd . DataFrame ([ f . __dict__ for f in fm . geometry . crosslocfile . crosssection ]) print ( df_loc . loc [:,[ 'id' , 'branchid' , 'definitionid' ]]) # To which definition do these locations refer: defs = df_loc . loc [ df_loc . index [ df_loc . branchid == 'Channel_1D_1' ], 'definitionid' ] . values # Change the Frictionids to dique for Channel_1D_1 index_defs = df_def . index [ df_def . id . isin ( defs )] for i in index_defs : df_def . loc [ i , 'frictionids' ] = [ 'dique' ] # Overwrite the definitions in D-Flow FM model with the changes in the dataframe fm . geometry . crossdeffile . definition = df_def . to_dict ( \"records\" ) # Convert crosssection defintions from D-Flow FM model to dataframe df_def = pd.DataFrame([f.__dict__ for f in fm.geometry.crossdeffile.definition]) print(df_def) # Check which cross-section locations are located on Channel_1D_1 df_loc = pd.DataFrame([f.__dict__ for f in fm.geometry.crosslocfile.crosssection]) print(df_loc.loc[:,['id','branchid','definitionid']]) # To which definition do these locations refer: defs = df_loc.loc[df_loc.index[df_loc.branchid=='Channel_1D_1'],'definitionid'].values # Change the Frictionids to dique for Channel_1D_1 index_defs = df_def.index[df_def.id.isin(defs)] for i in index_defs: df_def.loc[i, 'frictionids'] = ['dique'] # Overwrite the definitions in D-Flow FM model with the changes in the dataframe fm.geometry.crossdeffile.definition = df_def.to_dict(\"records\") Add boundary conditions to the model \u00b6 Fluvial floods occur when water levels in the river are too high. These high water levels in the rivers can result from several factors. One of those is the occurence of heavy rainfall in the upstream catchment. These heavy rainstorm can lead to a high discharge wave entering the upstream boundary of the river. In this tutorial you will model such a high discharge wave (time series) at the upstream 1D boundary (node id = '521410.278872_1056811.761107'). For the two downstream boundaries (node ids = [wkt_geom Name BridgeCount CrossSectio CulvertCoun GateCount GeometryLen IsLengthCus LateralSour Length LongName OrderNumber PumpCount Source StructureCo Target WeirCount fric_type fric_value chainage]) a constant water level of 0 m AD is assumed. Note that this are tidal boundaries in reality. In order to apply boundary conditions on a model you need two components: Forcing (.bc) file ForcingModel : This model contains the forcing value, time series, astronomical tide, realtime connection with other modules (D-RR) or QHtable. The first two options are created in this tutorial. External Forcing (.ext) file ExtModel : The external forcing specifies the location and type of forcing. Types of forcing are Boundary , Lateral and meteo. In [ ]: Copied! # Get node ids of branches node_ids = fm . geometry . netfile . network . _mesh1d . network1d_node_id print ( node_ids ) # Specify the node ids node_upstream = node_ids [ 0 ] # discharge time series node nodes_downstream = node_ids [ 2 :] # water level nodes # Create an empty external forcing model and forcing model ext = ExtModel () ext . filepath = 'boundary_new.ext' bc = ForcingModel () #bc.filepath = inputdir / 'BoundaryConditions.bc' # Read the upstream boundary time series from excel discharge_file = inputdir / '1D_BoundaryConditions.xlsx' discharge = pd . read_excel ( discharge_file , sheet_name = [ 0 ]) # Create the timeseries bc_up = TimeSeries ( name = node_upstream , nodeid = node_upstream , timeinterpolation = TimeInterpolation . linear , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2012-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], datablock = [[ time , dis ] for [ time , dis ] in discharge [ 0 ] . values ] ) # Create downstream constant boundaries bc_dn1 = Constant ( name = nodes_downstream [ 0 ], nodeid = nodes_downstream [ 0 ], quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], datablock = [[ \"0.0\" ]] ) bc_dn2 = Constant ( name = nodes_downstream [ 1 ], nodeid = nodes_downstream [ 1 ], quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], datablock = [[ \"0.0\" ]] ) # Add the forcing to ForcingModel bc . forcing . extend ([ bc_up , bc_dn1 , bc_dn2 ]) # Create boundary locations in ExtModel ext_up = Boundary ( quantity = 'dischargebnd' , nodeid = node_upstream , forcingfile = bc ) ext_dn1 = Boundary ( quantity = 'waterlevelbnd' , nodeid = nodes_downstream [ 0 ], forcingfile = bc ) ext_dn2 = Boundary ( quantity = 'waterlevelbnd' , nodeid = nodes_downstream [ 1 ], forcingfile = bc ) # Add the boundaries to ExtModel ext . boundary . extend ([ ext_up , ext_dn1 , ext_dn2 ]) # Add the ExtModel to D-Flow FM model fm . external_forcing . extforcefilenew = ext # Get node ids of branches node_ids = fm.geometry.netfile.network._mesh1d.network1d_node_id print(node_ids) # Specify the node ids node_upstream = node_ids[0] # discharge time series node nodes_downstream = node_ids[2:] # water level nodes # Create an empty external forcing model and forcing model ext = ExtModel() ext.filepath = 'boundary_new.ext' bc = ForcingModel() #bc.filepath = inputdir / 'BoundaryConditions.bc' # Read the upstream boundary time series from excel discharge_file = inputdir / '1D_BoundaryConditions.xlsx' discharge = pd.read_excel(discharge_file, sheet_name=[0]) # Create the timeseries bc_up = TimeSeries( name = node_upstream, nodeid = node_upstream, timeinterpolation = TimeInterpolation.linear, quantityunitpair = [QuantityUnitPair(quantity = 'time', unit = 'minutes since 2012-01-01 00:00:00'), QuantityUnitPair(quantity = 'dischargebnd', unit = 'm\u00b3/s')], datablock = [[time, dis] for [time,dis] in discharge[0].values] ) # Create downstream constant boundaries bc_dn1 = Constant( name = nodes_downstream[0], nodeid = nodes_downstream[0], quantityunitpair = [QuantityUnitPair(quantity = 'waterlevelbnd', unit = 'm')], datablock = [[\"0.0\"]] ) bc_dn2 = Constant( name = nodes_downstream[1], nodeid = nodes_downstream[1], quantityunitpair = [QuantityUnitPair(quantity = 'waterlevelbnd', unit = 'm')], datablock = [[\"0.0\"]] ) # Add the forcing to ForcingModel bc.forcing.extend([bc_up,bc_dn1,bc_dn2]) # Create boundary locations in ExtModel ext_up = Boundary( quantity = 'dischargebnd', nodeid = node_upstream, forcingfile = bc ) ext_dn1 = Boundary( quantity = 'waterlevelbnd', nodeid = nodes_downstream[0], forcingfile = bc ) ext_dn2 = Boundary( quantity = 'waterlevelbnd', nodeid = nodes_downstream[1], forcingfile = bc ) # Add the boundaries to ExtModel ext.boundary.extend([ext_up,ext_dn1,ext_dn2]) # Add the ExtModel to D-Flow FM model fm.external_forcing.extforcefilenew = ext Add initial conditions \u00b6 For this model an initial water depth of 1.0 meter is assumed in the 1D model. Below you can see how this initial waterdepth is added to the D-Flow FM model using the following steps: Creating 1D initial conditions field ( 1DField ), which contains the actual waterdepths on each branch. Note that the file is seperately saved from the rest of the model. Creating IniFieldModel (= Initial and parameter field files) in which we collect the initial condition specified in step 1, so that it can be added to the FMModel . In [ ]: Copied! # Create 1D initial conditions field ini_1d = OneDFieldModel () ini_1d . global_ = OneDFieldGlobal ( quantity = 'waterdepth' , unit = 'm' , value = 1.0 ) # only global values are needed in this case, but you could also specify it per branch. ini_1d . filepath = 'initialwaterdepth.ini' ini_1d . save ( outputdir / ini_1d . filepath ) # 1D field ini files needs to be saved seperately from the model save. # Create initial field file ini_field = IniFieldModel () ini_field . filepath = 'inifield.ini' ini_field . initial = InitialField ( quantity = 'waterdepth' , datafile = ini_1d . filepath , datafiletype = DataFileType . onedfield ) fm . geometry . inifieldfile = ini_field # Create 1D initial conditions field ini_1d = OneDFieldModel() ini_1d.global_ = OneDFieldGlobal(quantity='waterdepth', unit='m', value=1.0) # only global values are needed in this case, but you could also specify it per branch. ini_1d.filepath = 'initialwaterdepth.ini' ini_1d.save(outputdir / ini_1d.filepath) # 1D field ini files needs to be saved seperately from the model save. # Create initial field file ini_field = IniFieldModel() ini_field.filepath = 'inifield.ini' ini_field.initial = InitialField(quantity='waterdepth',datafile=ini_1d.filepath, datafiletype=DataFileType.onedfield) fm.geometry.inifieldfile = ini_field Add a weir to the model \u00b6 Many lakes occur close along Canal del Dique. See figure below. This tutorial assumes that these lakes can function as extra storage for the floods from the river. Hence a weir structure, functioning as a small dam, is added downstream of the lakes. This weir structure has the following conditions: It is located at 70 km from the upstream node of the branch. The crestlevel is 4.0 m AD. The crest width is 105.0 m. The flow over the dam is in both directions.

    In [ ]: Copied! # Create weir structure weir = Weir ( id = 'fictive_dam' , name = 'fictive_dam' , branchId = 'Channel_1D_1' , chainage = 70000.0 , allowedFlowDir = FlowDirection . both , crestLevel = 4.0 , crestWidth = 105.0 , corrCoeff = 1.000 , useVelocityHeight = True ) # Create structure model struc = StructureModel () struc . filepath = 'structure.ini' # Append weir to structure struc . structure . append ( weir ) # Assign structure model to D-Flow FM model fm . geometry . structurefile = [ struc ] # Create weir structure weir = Weir( id='fictive_dam', name = 'fictive_dam', branchId='Channel_1D_1', chainage=70000.0, allowedFlowDir=FlowDirection.both, crestLevel=4.0, crestWidth=105.0, corrCoeff=1.000, useVelocityHeight=True ) # Create structure model struc = StructureModel() struc.filepath = 'structure.ini' # Append weir to structure struc.structure.append(weir) # Assign structure model to D-Flow FM model fm.geometry.structurefile = [struc] EX6 : You found out that the dam should be significantly higher. Hence you increase the crestlevel to 10.0 m AD. Your client also decided that flow can only occur from upstream to downstream. Please change the weir above. In [ ]: Copied! # Answer EX6: # Create weir structure weir = Weir ( id = 'fictive_dam' , name = 'fictive_dam' , branchId = 'Channel_1D_1' , chainage = 70000.0 , allowedFlowDir = FlowDirection . positive , crestLevel = 10.0 , crestWidth = 105.0 , corrCoeff = 1.000 , useVelocityHeight = True ) # Create structure model struc = StructureModel () struc . filepath = 'structure.ini' # Append weir to structure struc . structure . append ( weir ) # Assign structure model to D-Flow FM model fm . geometry . structurefile = [ struc ] # Answer EX6: # Create weir structure weir = Weir( id='fictive_dam', name = 'fictive_dam', branchId='Channel_1D_1', chainage=70000.0, allowedFlowDir=FlowDirection.positive, crestLevel=10.0, crestWidth=105.0, corrCoeff=1.000, useVelocityHeight=True ) # Create structure model struc = StructureModel() struc.filepath = 'structure.ini' # Append weir to structure struc.structure.append(weir) # Assign structure model to D-Flow FM model fm.geometry.structurefile = [struc] Save 1D model \u00b6 The 1D model is now finished. The commands below are used to save the model to the correct filepath (specified for the MDU-file). Note that the recurse is set to True to make sure all underlying model files are written to the directory. Else the MDU-file will be the only file written to the directory. In [ ]: Copied! # Change some time settings fm . time . refdate = '20120101' fm . time . dtuser = 60. # seconds fm . time . tstart = 43200. fm . time . tstop = 561600. # Save the 1D model. fm . general . autostart = AutoStartOption . no # This is a workaround for a bug in hydrolib-core 0.3.1 fm . save ( recurse = True ) # Change some time settings fm.time.refdate = '20120101' fm.time.dtuser = 60. # seconds fm.time.tstart = 43200. fm.time.tstop = 561600. # Save the 1D model. fm.general.autostart = AutoStartOption.no # This is a workaround for a bug in hydrolib-core 0.3.1 fm.save(recurse=True) PART 2: Extend to a 1D2D Delft3D FM model \u00b6 We will now continue with the model fm from part 1, and add a 2D mesh to it, as well as 1D2D couplings. Create 2D flexible mesh \u00b6 We use a shapefile with the area of interest to define the extent of the new 2D mesh that is to be generated. First, a uniform rectilinear mesh is generated, after which it can be clipped. EX7 : Create a rectangular grid with a cell size of 2500 by 2500 meter. Use create_rectilinear() function. EX8 : Clip the rectangular grid with the clip_geom using clip() function. In [ ]: Copied! # Read grid outline gdf_grid = gpd . read_file ( inputdir / 'outline_2D_grid.shp' ) # Determine the boundary box extent = gdf_grid . geometry [ 0 ] . bounds # Create uniform rectilinear mesh mesh2d = Mesh2d () # Answer EX7 mesh2d . create_rectilinear ( extent = extent , dx = 2500.0 , dy = 2500.0 ) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np . array ( gdf_grid . geometry [ 0 ] . exterior . xy ) clip_geom = GeometryList ( clip_polygon [ 0 ], clip_polygon [ 1 ]) # Answer EX8 mesh2d . clip ( clip_geom ) fm . geometry . netfile . network . _mesh2d = mesh2d fm . geometry . netfile . filepath = \"FlowFM_1D2D_net.nc\" # Read grid outline gdf_grid = gpd.read_file(inputdir / 'outline_2D_grid.shp') # Determine the boundary box extent = gdf_grid.geometry[0].bounds # Create uniform rectilinear mesh mesh2d = Mesh2d() # Answer EX7 mesh2d.create_rectilinear( extent=extent, dx=2500.0, dy=2500.0 ) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np.array(gdf_grid.geometry[0].exterior.xy) clip_geom = GeometryList(clip_polygon[0],clip_polygon[1]) # Answer EX8 mesh2d.clip(clip_geom) fm.geometry.netfile.network._mesh2d = mesh2d fm.geometry.netfile.filepath = \"FlowFM_1D2D_net.nc\" The cell below produces a basic plot of the 1D + 2D mesh. In [ ]: Copied! # Create a plot mesh2d_mk = network . _mesh2d . get_mesh2d () mesh1d_mk = network . _mesh1d . _get_mesh1d () figure , ax = plt . subplots () ax . set_aspect ( 'equal' ) plt . rcParams [ \"figure.figsize\" ] = 10 , 10 ax . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) # Plot the 1D2D network mesh2d_mk . plot_edges ( ax = ax , color = \"orange\" ) mesh1d_mk . plot_edges ( ax = ax , color = 'blue' ) # Create a plot mesh2d_mk = network._mesh2d.get_mesh2d() mesh1d_mk = network._mesh1d._get_mesh1d() figure, ax = plt.subplots() ax.set_aspect('equal') plt.rcParams[\"figure.figsize\"]=10,10 ax.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) # Plot the 1D2D network mesh2d_mk.plot_edges(ax=ax, color=\"orange\") mesh1d_mk.plot_edges(ax=ax, color='blue') Local refinement of the 2D mesh \u00b6 One of the key functionalities of Delft3D Flexible Mesh is that you can refine the 2D grid locally. The cell below shows how the grid is locally refined around the river by executing the refinement algorithm once ( level=1 ). In [ ]: Copied! # Create empty mesh2d object mesh2d = Mesh2d () # Create rectangular grid mesh2d . create_rectilinear ( extent = extent , dx = 2500.0 , dy = 2500.0 ) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np . array ( gdf_grid . geometry [ 0 ] . exterior . xy ) clip_geom = GeometryList ( clip_polygon [ 0 ], clip_polygon [ 1 ]) mesh2d . clip ( clip_geom ) # Refine the coarse uniform grid in a buffer region around the rivers gdf_refine = gpd . read_file ( inputdir / 'buffer_around_river_proj.shp' ) refine_polygon = np . array ( gdf_refine . geometry [ 0 ] . exterior . xy ) refine_geom = GeometryList ( refine_polygon [ 0 ], refine_polygon [ 1 ]) mesh2d . refine ( refine_geom , level = 1 ) fm . geometry . netfile . network . _mesh2d = mesh2d fm . geometry . netfile . filepath = \"FlowFM_1D2D_refined_net.nc\" # Create empty mesh2d object mesh2d = Mesh2d() # Create rectangular grid mesh2d.create_rectilinear( extent=extent, dx=2500.0, dy=2500.0 ) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np.array(gdf_grid.geometry[0].exterior.xy) clip_geom = GeometryList(clip_polygon[0],clip_polygon[1]) mesh2d.clip(clip_geom) # Refine the coarse uniform grid in a buffer region around the rivers gdf_refine = gpd.read_file(inputdir / 'buffer_around_river_proj.shp') refine_polygon = np.array(gdf_refine.geometry[0].exterior.xy) refine_geom = GeometryList(refine_polygon[0], refine_polygon[1]) mesh2d.refine(refine_geom, level=1) fm.geometry.netfile.network._mesh2d = mesh2d fm.geometry.netfile.filepath = \"FlowFM_1D2D_refined_net.nc\" In [ ]: Copied! # Create a plot mesh2d_mk = network . _mesh2d . get_mesh2d () mesh1d_mk = network . _mesh1d . _get_mesh1d () figure , ax = plt . subplots () ax . set_aspect ( 'equal' ) plt . rcParams [ \"figure.figsize\" ] = 10 , 10 ax . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) # Plot the 1D2D network mesh2d_mk . plot_edges ( ax = ax , color = \"orange\" ) mesh1d_mk . plot_edges ( ax = ax , color = 'blue' ) # Create a plot mesh2d_mk = network._mesh2d.get_mesh2d() mesh1d_mk = network._mesh1d._get_mesh1d() figure, ax = plt.subplots() ax.set_aspect('equal') plt.rcParams[\"figure.figsize\"]=10,10 ax.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) # Plot the 1D2D network mesh2d_mk.plot_edges(ax=ax, color=\"orange\") mesh1d_mk.plot_edges(ax=ax, color='blue') Save 1D2D model \u00b6 The 1D2D model is now finished. The commands below are used to save the model to the correct filepath (specified for the MDU-file). Note that the recurse is set to True to make sure all underlying model files are written to the directory. Else the MDU-file will be the only file written to the directory. Note that the 1D2D links will be generated in the Delft3D FM 1D2D software. Future releases of HYDROLIB-core will consist of 1D2D functionalities. In [ ]: Copied! # Change fm outputdir_1d2d = root / '1D2D_model' fm . filepath = outputdir_1d2d / 'Magdalena_1D2D.mdu' fm . general . autostart = AutoStartOption . no fm . save ( recurse = True ) # Change fm outputdir_1d2d = root / '1D2D_model' fm.filepath = outputdir_1d2d / 'Magdalena_1D2D.mdu' fm.general.autostart = AutoStartOption.no fm.save(recurse=True)","title":"Tutorial Delft3D FM 1D2D fluvial flood model of Magdalena river"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#tutorial-delft3d-fm-1d2d-fluvial-flood-model-of-magdalena-river","text":"This notebook is an introduction on how to use HYDROLIB-core functionalities to create and adjust a Delft3D FM Suite 1D2D fluvial flood model of the Magdalena river in Columbia. First a 1D river model of the Magdalena river and Canal del Dique will be created, shown in the left figure. This model will be extended with a 2D Flexible Mesh, with a uniform roughness field. Adding a DTM on that 2D mesh is currently not part of this tutorial, but normally this is of course indispensible to mimic the fluvial flood patterns. Running the model or importing the model in the Delft3D FM Suite 1D2D is not shown in this tutorial. Note that the model and tutorial are created for educational purposes and consist partially of fictive/unvalidated model data. HYDROLIB-core is the core library of Python wrappers around the D-HYDRO Suite 1D2D model files (input and output) and model engines (kernel libraries). HYDROLIB is a Python package with tools for pre-processing, post-processing and analysis of hydrodynamical data and simulation results, currently focused on Delft3D Suite 1D2D. HYDROLIB builds upon the basic HYDROLIB-core functionalities. The goal of this tutorial is to familiarize modelers with how to apply HYDROLIB-core functionalities in their modelling procedures for building new models or adjusting existing models. As mentioned above, you will create an 1D2D fluvial flood model from scratch using the D-Flow FM HYDROLIB-core functionalities and the underlying functions from mesh generation ( MeshKernelPy ). The building of the model is done by the following steps Loading libraries Connect to data folder Create empty D-Flow FM model Read branches Create computational grid Add cross-sections Add roughness Add boundary conditions Add initial conditions Add a weir to the model Save 1D model Create 2D flexible mesh Add 2D DTM to model Save 1D2D model Note that HYDROLIB-core also contains functionalities to setup lumped rainfall runoff models ( D-RR ) and to apply real-time control at structures ( D-RTC ), but these are not covered in this tutorial.","title":"Tutorial Delft3D FM 1D2D fluvial flood model of Magdalena river"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#installation","text":"To run this notebook a simple Python environment with the following packages is required: - python=3.9 - pandas - geopandas - pyogrio - matplotlib - numpy - jupyter - xarray - openpyxl - pip - pip: - hydrolib-core==0.3.1 - meshkernel==1.0.0 Note that all participants received an e-mail to download the material from the Deltares download portal and to create a Conda environment with the packages automatically installed from environment.yml . Furthermore, a dummy model is provided at the download portal to test the environment.","title":"Installation"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#tips-for-working-in-the-jupyter-notebook","text":"Tab : Auto-complete on code Shift + Tab : Tooltip Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell Ctrl + Shift + P : Open command palette Let's get started!","title":"Tips for working in the Jupyter Notebook:"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#loading-libraries","text":"Several Python packages are required to run the notebook. These packages are imported below. Please consult the HYDROLIB-core documentation if you want to import additional HYDROLIB-core functionalities later. The import of HYDROLIB-core packages will be simplied in future HYDROLIB-core release (> 0.3.1) In [ ]: Copied! # basic packages import numpy as np import pandas as pd import matplotlib.pyplot as plt # I/O from pathlib import Path # vector/polygon packages import geopandas as gpd from shapely import wkt from shapely.geometry import box # HYDROLIB-core libraries from hydrolib.core.mdu.models import FMModel , AutoStartOption from hydrolib.core.net.models import * from hydrolib.core.crosssection.models import CrossLocModel , CrossDefModel , CrossSection , YZCrsDef from hydrolib.core.friction.models import * from hydrolib.core.bc.models import * from hydrolib.core.ext.models import * from hydrolib.core.inifield.models import * from hydrolib.core.onedfield.models import * from hydrolib.core.structure.models import Weir , FlowDirection , StructureModel # basic packages import numpy as np import pandas as pd import matplotlib.pyplot as plt # I/O from pathlib import Path # vector/polygon packages import geopandas as gpd from shapely import wkt from shapely.geometry import box # HYDROLIB-core libraries from hydrolib.core.mdu.models import FMModel, AutoStartOption from hydrolib.core.net.models import * from hydrolib.core.crosssection.models import CrossLocModel, CrossDefModel, CrossSection, YZCrsDef from hydrolib.core.friction.models import * from hydrolib.core.bc.models import * from hydrolib.core.ext.models import * from hydrolib.core.inifield.models import * from hydrolib.core.onedfield.models import * from hydrolib.core.structure.models import Weir, FlowDirection, StructureModel","title":"Loading libraries"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#connect-to-data","text":"The data for this tutorial is provided via the download portal. EX1 : Change the inputdir to the path of your unzipped data folder. In [ ]: Copied! # Get the directory of the notebook location root = Path . cwd () # Answer EX1 # Specify the path to the data folder inputdir = root / 'data' #inputdir = Path(r\"c:\\checkouts\\HYDROLIB-data_git\\magdalena\") # Get the directory of the notebook location root = Path.cwd() # Answer EX1 # Specify the path to the data folder inputdir = root / 'data' #inputdir = Path(r\"c:\\checkouts\\HYDROLIB-data_git\\magdalena\")","title":"Connect to data"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#create-empty-d-flow-fm-model","text":"To start a model from scratch you need to create first an empty model without data and assign a filepath to the model. In this case a D-Flow FM model is created. The MDU file (master definition file) is the main file of the D-Flow FM model. This is created with the FMModel() function. The fm model object is only created in memory. To save the actual model file, call fm.save() . EX2 : Set the outputdir of the model and give it a name. Verify that an MDU file has been written in your output directory. In [ ]: Copied! # Create empty D-Flow FM model fm = FMModel () # Answer EX2 # Assign filepath to the D-Flow FM model outputdir = root / '1D_model' fm . filepath = outputdir / 'Magdalena_1D.mdu' fm . save () # Create empty D-Flow FM model fm = FMModel() # Answer EX2 # Assign filepath to the D-Flow FM model outputdir = root / '1D_model' fm.filepath = outputdir / 'Magdalena_1D.mdu' fm.save()","title":"Create empty D-Flow FM model"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#part-1-set-up-a-1d-delft3d-fm-model","text":"In this part we will build up the complete 1D model schematization step by step. At the end you should have a complete set of model input files for a 1D calculation.","title":"PART 1: Set up a 1D Delft3D FM model"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#read-branches","text":"The model will include the lower part of the Magadalena from Cordoba Teton to the river mouth Baranquilla and the Canal del Dique. EX2 : Please investigate the branches variable and answer the following questions for yourself: How many river branches does the model have? What are their names? Which friction type and values are used for each branch? In [ ]: Copied! # Read the branches branches = gpd . read_file ( filename = inputdir / 'branches_Branches.shp' ) # Answer EX3 print ( branches . head ()) # To show the first part of the dataframe print ( branches . Name ) # To get the names of the branches # The model consist of 3 branches # The names of these branches are Channel_1D_1_A, Channel_1D_1_B and Channel_1D_1. # Manning is used as friction type. Branches Channel_1D_1_B and Channel_1D_1 have a friction value of 0.02. Branch Channel_1D_1_A has a value of 0.03. # Read the branches branches = gpd.read_file(filename = inputdir / 'branches_Branches.shp') # Answer EX3 print(branches.head()) # To show the first part of the dataframe print(branches.Name) # To get the names of the branches # The model consist of 3 branches # The names of these branches are Channel_1D_1_A, Channel_1D_1_B and Channel_1D_1. # Manning is used as friction type. Branches Channel_1D_1_B and Channel_1D_1 have a friction value of 0.02. Branch Channel_1D_1_A has a value of 0.03.","title":"Read branches"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#create-1d-computational-grid","text":"In the previous step you read the geometry and attributes of the branches into the notebook. These branches will become the network input to our FMModel . The cell below shows how the geometry and name of the branches are assigned to the network. In addition a 1D computational grid ( mesh1d ) with gridpoint every 1000 meter is created on top of this network. Since the network does not yet exist, you need to create an empty network model . Assign the geometry of the branches followed by the generation of the computational grid. The network model should be added to the D-Flow FM model ( fm variable in this notebook) as network in the netfile parameter in the section geometry . Note that you have to specify a filepath for the networkfile. Note that the network model can consist of 1D, 2D flexible mesh ( mesh2d ) and 1D2D links ( links1d2d ). In [ ]: Copied! # Specify 1D computational grid distance dx = 1000.0 # Create an empty network network = Network () # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch in branches . iterrows (): xy = np . transpose ( branch . geometry . xy ) branch_new = Branch ( geometry = xy ) branch_new . generate_nodes ( mesh1d_edge_length = dx ) network . mesh1d_add_branch ( branch_new , name = branch . Name ) # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm . geometry . netfile . network = network fm . geometry . netfile . filepath = \"FlowFM_net.nc\" # Specify 1D computational grid distance dx = 1000.0 # Create an empty network network = Network() # Assign geometry of the branches and generate the computational grid on top of the branches. for index,branch in branches.iterrows(): xy = np.transpose(branch.geometry.xy) branch_new = Branch(geometry=xy) branch_new.generate_nodes(mesh1d_edge_length=dx) network.mesh1d_add_branch(branch_new, name=branch.Name) # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm.geometry.netfile.network = network fm.geometry.netfile.filepath = \"FlowFM_net.nc\" EX3 : Please change the computational grid distance of each branch accordingly: Branch name dx [m] Channel_1D_1_A 1000 Channel_1D_1_B 1000 Channel_1D 500 Tip : Do not forget to create a new network. In [ ]: Copied! # Answer EX3 # Specify 1D computational grid distance dx = [ 1000. , 1000. , 500. ] # Create an empty network network = Network () # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch in branches . iterrows (): xy = np . transpose ( branch . geometry . xy ) branch_new = Branch ( geometry = xy ) branch_new . generate_nodes ( mesh1d_edge_length = dx [ index ]) network . mesh1d_add_branch ( branch_new , name = branch . Name ) network . _mesh1d . _set_mesh1d () # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm . geometry . netfile . network = network fm . geometry . netfile . filepath = \"FlowFM_EX3_net.nc\" # Answer EX3 # Specify 1D computational grid distance dx = [1000., 1000., 500.] # Create an empty network network = Network() # Assign geometry of the branches and generate the computational grid on top of the branches. for index,branch in branches.iterrows(): xy = np.transpose(branch.geometry.xy) branch_new = Branch(geometry=xy) branch_new.generate_nodes(mesh1d_edge_length=dx[index]) network.mesh1d_add_branch(branch_new, name=branch.Name) network._mesh1d._set_mesh1d() # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm.geometry.netfile.network = network fm.geometry.netfile.filepath = \"FlowFM_EX3_net.nc\" The 1D branches are plotted on a map in the figure below. Also, the computational grid points in the mesh1d definition are shown. In [ ]: Copied! # Create a figure with the flowlinks of the model figure , ( ax1 , ax2 ) = plt . subplots ( ncols = 2 ) img = plt . imread ( inputdir / \"osm_background.png\" ) mesh1d_meshkernel = network . _mesh1d . _get_mesh1d () ax1 . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) mesh1d_meshkernel . plot_edges ( ax = ax1 , color = 'red' ) # Add some annotation of branches: for index , branch in branches . iterrows (): middleIndex = int (( len ( branch [ 'geometry' ] . coords ) - 1 ) / 2 ) ax1 . text ( branch [ 'geometry' ] . xy [ 0 ][ middleIndex ], branch [ 'geometry' ] . xy [ 1 ][ middleIndex ], branch [ 'Name' ], ha = 'right' ) # Make a second plot with a zoom-in view of the computational grid points near the junction ax2 . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) ax2 . set_xlim ([ 500000 , 525000 ]) ax2 . set_ylim ([ 1125000 , 1150000 ]) mesh1d_meshkernel . plot_edges ( ax = ax2 , color = 'red' , marker = '.' , markeredgecolor = 'k' , markersize = 1 ) # Create a figure with the flowlinks of the model figure, (ax1, ax2) = plt.subplots(ncols=2) img = plt.imread(inputdir/\"osm_background.png\") mesh1d_meshkernel = network._mesh1d._get_mesh1d() ax1.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) mesh1d_meshkernel.plot_edges(ax=ax1, color='red') # Add some annotation of branches: for index,branch in branches.iterrows(): middleIndex = int((len(branch['geometry'].coords) - 1)/2) ax1.text(branch['geometry'].xy[0][middleIndex], branch['geometry'].xy[1][middleIndex], branch['Name'], ha='right') # Make a second plot with a zoom-in view of the computational grid points near the junction ax2.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) ax2.set_xlim([500000, 525000]) ax2.set_ylim([1125000 ,1150000]) mesh1d_meshkernel.plot_edges(ax=ax2, color='red',marker='.',markeredgecolor='k',markersize=1)","title":"Create 1D computational grid"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#add-cross-sections","text":"In order to determine the flow area of the 1D model during the computation, you need cross-sections. These cross-sections consist of two components: Cross-section locations ( crosslocfile ): The crosslocfile contains the location of the cross-section on the branches. This is indicated with branchId chainage , where branchId is the name of the branch and chainage the distance to the upstream node. The figure below shows the cross-section locations in grey. In addition the cross-section location consist of the cross-section definition used at that location and a vertical shift of the profile. The latter is mainly used to create a good longitudinal slope over the 1D model (in case of shared cross-sections).

    Cross-section definitions ( crossdeffile ): The crossdeffile has the cross-section definitions in it. These definitions describe the shape of the profile. There are multiple types available: circle, rectangle, ZW- (tabulated), YZ- and XYZ-profiles. Depending on what type of watersystem you try to model you decide which cross-section to use. We recommend to use ZW- or YZ-profiles for rivers.

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In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: #111111; --jp-inverse-layout-color1: var(--md-grey-900); --jp-inverse-layout-color2: var(--md-grey-800); --jp-inverse-layout-color3: var(--md-grey-700); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-900); --jp-brand-color1: var(--md-blue-700); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-900); --jp-accent-color1: var(--md-green-700); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-900); --jp-warn-color1: var(--md-orange-700); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-900); --jp-error-color1: var(--md-red-700); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-900); --jp-success-color1: var(--md-green-700); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-900); --jp-info-color1: var(--md-cyan-700); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--md-grey-100); --jp-cell-editor-border-color: var(--md-grey-300); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 0.5; --jp-cell-prompt-not-active-font-color: var(--md-grey-700); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: var(--md-blue-50); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: #fdd; --jp-rendermime-table-row-background: var(--md-grey-100); --jp-rendermime-table-row-hover-background: var(--md-light-blue-50); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.25); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color1); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.24); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--md-grey-300); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color1); --jp-input-hover-background: var(--jp-layout-color1); --jp-input-background: var(--md-grey-100); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: #d9d9d9; --jp-editor-selected-focused-background: #d7d4f0; --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: #008000; --jp-mirror-editor-atom-color: #88f; --jp-mirror-editor-number-color: #080; --jp-mirror-editor-def-color: #00f; --jp-mirror-editor-variable-color: var(--md-grey-900); --jp-mirror-editor-variable-2-color: #05a; --jp-mirror-editor-variable-3-color: #085; --jp-mirror-editor-punctuation-color: #05a; --jp-mirror-editor-property-color: #05a; --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ba2121; --jp-mirror-editor-string-2-color: #708; --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: #008000; --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: #170; --jp-mirror-editor-attribute-color: #00c; --jp-mirror-editor-header-color: blue; --jp-mirror-editor-quote-color: #090; --jp-mirror-editor-link-color: #00c; --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: white; /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.5; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(245, 200, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } [data-md-color-scheme=\"slate\"] .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ /* The dark theme shadows need a bit of work, but this will probably also require work on the core layout * colors used in the theme as well. */ --jp-shadow-base-lightness: 32; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-700); --jp-border-color1: var(--md-grey-700); --jp-border-color2: var(--md-grey-800); --jp-border-color3: var(--md-grey-900); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(255, 255, 255, 1); --jp-ui-font-color1: rgba(255, 255, 255, 0.87); --jp-ui-font-color2: rgba(255, 255, 255, 0.54); --jp-ui-font-color3: rgba(255, 255, 255, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(0, 0, 0, 1); --jp-ui-inverse-font-color1: rgba(0, 0, 0, 0.8); --jp-ui-inverse-font-color2: rgba(0, 0, 0, 0.5); --jp-ui-inverse-font-color3: rgba(0, 0, 0, 0.3); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(255, 255, 255, 1); --jp-content-font-color1: rgba(255, 255, 255, 1); --jp-content-font-color2: rgba(255, 255, 255, 0.7); --jp-content-font-color3: rgba(255, 255, 255, 0.5); --jp-content-link-color: var(--md-blue-300); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: #111111; --jp-layout-color1: var(--md-grey-900); --jp-layout-color2: var(--md-grey-800); --jp-layout-color3: var(--md-grey-700); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: white; --jp-inverse-layout-color1: white; --jp-inverse-layout-color2: var(--md-grey-200); --jp-inverse-layout-color3: var(--md-grey-400); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-700); --jp-brand-color1: var(--md-blue-500); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-700); --jp-accent-color1: var(--md-green-500); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-700); --jp-warn-color1: var(--md-orange-500); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-700); --jp-error-color1: var(--md-red-500); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-700); --jp-success-color1: var(--md-green-500); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-700); --jp-info-color1: var(--md-cyan-500); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--jp-layout-color1); --jp-cell-editor-border-color: var(--md-grey-700); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 1; --jp-cell-prompt-not-active-font-color: var(--md-grey-300); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: rgba(33, 150, 243, 0.24); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: rgba(244, 67, 54, 0.28); --jp-rendermime-table-row-background: var(--md-grey-900); --jp-rendermime-table-row-hover-background: rgba(3, 169, 244, 0.2); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.6); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color2); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.8); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--jp-layout-color0); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color0); --jp-input-hover-background: var(--jp-layout-color2); --jp-input-background: var(--md-grey-800); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: var(--jp-layout-color2); --jp-editor-selected-focused-background: rgba(33, 150, 243, 0.24); --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: var(--md-green-500); --jp-mirror-editor-atom-color: var(--md-blue-300); --jp-mirror-editor-number-color: var(--md-green-400); --jp-mirror-editor-def-color: var(--md-blue-600); --jp-mirror-editor-variable-color: var(--md-grey-300); --jp-mirror-editor-variable-2-color: var(--md-blue-400); --jp-mirror-editor-variable-3-color: var(--md-green-600); --jp-mirror-editor-punctuation-color: var(--md-blue-400); --jp-mirror-editor-property-color: var(--md-blue-400); --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ff7070; --jp-mirror-editor-string-2-color: var(--md-purple-300); --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: var(--md-green-600); --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: var(--md-green-700); --jp-mirror-editor-attribute-color: var(--md-blue-700); --jp-mirror-editor-header-color: var(--md-blue-500); --jp-mirror-editor-quote-color: var(--md-green-300); --jp-mirror-editor-link-color: var(--md-blue-700); --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: var(--md-grey-400); /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.6; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(255, 225, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* scrollbar related styles. Supports every browser except Edge. */ /* colors based on JetBrain's Darcula theme */ --jp-scrollbar-background-color: #3f4244; --jp-scrollbar-thumb-color: 88, 96, 97; /* need to specify thumb color as an RGB triplet */ --jp-scrollbar-endpad: 3px; /* the minimum gap between the thumb and the ends of a scrollbar */ /* hacks for setting the thumb shape. These do nothing in Firefox */ --jp-scrollbar-thumb-margin: 3.5px; /* the space in between the sides of the thumb and the track */ --jp-scrollbar-thumb-radius: 9px; /* set to a large-ish value for rounded endcaps on the thumb */ /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } :root{--md-red-50: #ffebee;--md-red-100: #ffcdd2;--md-red-200: #ef9a9a;--md-red-300: #e57373;--md-red-400: #ef5350;--md-red-500: #f44336;--md-red-600: #e53935;--md-red-700: #d32f2f;--md-red-800: #c62828;--md-red-900: #b71c1c;--md-red-A100: #ff8a80;--md-red-A200: #ff5252;--md-red-A400: #ff1744;--md-red-A700: #d50000;--md-pink-50: #fce4ec;--md-pink-100: #f8bbd0;--md-pink-200: #f48fb1;--md-pink-300: #f06292;--md-pink-400: #ec407a;--md-pink-500: #e91e63;--md-pink-600: #d81b60;--md-pink-700: #c2185b;--md-pink-800: #ad1457;--md-pink-900: #880e4f;--md-pink-A100: #ff80ab;--md-pink-A200: #ff4081;--md-pink-A400: #f50057;--md-pink-A700: #c51162;--md-purple-50: #f3e5f5;--md-purple-100: #e1bee7;--md-purple-200: #ce93d8;--md-purple-300: #ba68c8;--md-purple-400: #ab47bc;--md-purple-500: #9c27b0;--md-purple-600: #8e24aa;--md-purple-700: #7b1fa2;--md-purple-800: #6a1b9a;--md-purple-900: #4a148c;--md-purple-A100: #ea80fc;--md-purple-A200: #e040fb;--md-purple-A400: #d500f9;--md-purple-A700: #aa00ff;--md-deep-purple-50: #ede7f6;--md-deep-purple-100: #d1c4e9;--md-deep-purple-200: #b39ddb;--md-deep-purple-300: #9575cd;--md-deep-purple-400: #7e57c2;--md-deep-purple-500: #673ab7;--md-deep-purple-600: #5e35b1;--md-deep-purple-700: #512da8;--md-deep-purple-800: #4527a0;--md-deep-purple-900: #311b92;--md-deep-purple-A100: #b388ff;--md-deep-purple-A200: #7c4dff;--md-deep-purple-A400: #651fff;--md-deep-purple-A700: #6200ea;--md-indigo-50: #e8eaf6;--md-indigo-100: #c5cae9;--md-indigo-200: #9fa8da;--md-indigo-300: 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sourceMappingURL=mkdocs-jupyter.css.map*/ init_mathjax = function() { if (window.MathJax) { // MathJax loaded MathJax.Hub.Config({ TeX: { equationNumbers: { autoNumber: \"AMS\", useLabelIds: true } }, tex2jax: { inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ], displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ], processEscapes: true, processEnvironments: true }, displayAlign: 'center', CommonHTML: { linebreaks: { automatic: true } } }); MathJax.Hub.Queue([\"Typeset\", MathJax.Hub]); } } init_mathjax(); Build a basic model \u00b6 This Build a basic model tutorial illustrates how to build a simple D-Flow FM model from scratch using HYDROLIB-core . Import HYDROLIB-core functionalities and setup D-Flow FM model \u00b6 The commands below import all needed packages and will prepare a model that will be saved in a subdir testmodel/ within the current working dir. In [ ]: Copied! from hydrolib.core.structure.models import FlowDirection , StructureModel , Weir from hydrolib.core.mdu.models import FMModel from pathlib import Path print ( \"Package import successful!\" ) from hydrolib.core.structure.models import FlowDirection, StructureModel, Weir from hydrolib.core.mdu.models import FMModel from pathlib import Path print(\"Package import successful!\") In [ ]: Copied! workdir = Path ( \"testmodel\" ) mdufile = \"test.mdu\" fm = FMModel () fm . filepath = workdir / mdufile workdir = Path(\"testmodel\") mdufile = \"test.mdu\" fm = FMModel() fm.filepath = workdir / mdufile Add a hydraulic structure; note that this is invalid because the model does not have a 1D network with branches and coordinates yet, but it will work for demo purposes and the network may be added later. In [ ]: Copied! # Add weir to the structure set/model and add this structure set to D-Flow FM model struc = Weir ( branchId = 'someBranch' , chainage = 123.0 , allowedflowdir = FlowDirection . none , crestlevel = 0.0 ) struc . comments . crestlevel = \"This is a comment\" fm . geometry . structurefile = [ StructureModel ( structure = [ struc ])] # Add weir to the structure set/model and add this structure set to D-Flow FM model struc = Weir(branchId='someBranch', chainage = 123.0, allowedflowdir=FlowDirection.none, crestlevel=0.0) struc.comments.crestlevel = \"This is a comment\" fm.geometry.structurefile = [StructureModel(structure=[struc])] Note that the creation of a Weir and other model objects requires several input arguments. A ValidationError will be raised when the model is invalid or incomplete. For instance, in the above example, if the StructureModel had been assigned directly to structurefile instead of as a list, that would have triggered a ValidationError . Setup a DIMR model \u00b6 Now let's add this model to an integrated model (DIMR config) and save it. In [ ]: Copied! from hydrolib.core.dimr.models import DIMR , FMComponent dimr = DIMR () dimr . component . append ( FMComponent ( name = \"test\" , workingDir = workdir , inputfile = mdufile , model = fm ) ) dimr_config = Path ( \"dimr_config.xml\" ) dimr . save ( filepath = dimr_config , recurse = True ) from hydrolib.core.dimr.models import DIMR, FMComponent dimr = DIMR() dimr.component.append( FMComponent(name=\"test\", workingDir=workdir, inputfile=mdufile, model=fm) ) dimr_config = Path(\"dimr_config.xml\") dimr.save(filepath=dimr_config, recurse=True) The model files on disk \u00b6 Now, let's see which model input files were saved: In [ ]: Copied! dimr . show_tree () dimr.show_tree() The save call on the highest-level DIMR object will result in recursive saves of all child models in the model hierarchy, so this results in four files ( dimr_config.xml , network.nc , structures.ini , test.mdu ) in the working directory. Some more in-depth background about recursive saving of a model tree is given in another tutorial: Loading and saving .","title":"Build a basic model"},{"location":"tutorials/build_basic_model/#build-a-basic-model","text":"This Build a basic model tutorial illustrates how to build a simple D-Flow FM model from scratch using HYDROLIB-core .","title":"Build a basic model"},{"location":"tutorials/build_basic_model/#import-hydrolib-core-functionalities-and-setup-d-flow-fm-model","text":"The commands below import all needed packages and will prepare a model that will be saved in a subdir testmodel/ within the current working dir. In [ ]: Copied! from hydrolib.core.structure.models import FlowDirection , StructureModel , Weir from hydrolib.core.mdu.models import FMModel from pathlib import Path print ( \"Package import successful!\" ) from hydrolib.core.structure.models import FlowDirection, StructureModel, Weir from hydrolib.core.mdu.models import FMModel from pathlib import Path print(\"Package import successful!\") In [ ]: Copied! workdir = Path ( \"testmodel\" ) mdufile = \"test.mdu\" fm = FMModel () fm . filepath = workdir / mdufile workdir = Path(\"testmodel\") mdufile = \"test.mdu\" fm = FMModel() fm.filepath = workdir / mdufile Add a hydraulic structure; note that this is invalid because the model does not have a 1D network with branches and coordinates yet, but it will work for demo purposes and the network may be added later. In [ ]: Copied! # Add weir to the structure set/model and add this structure set to D-Flow FM model struc = Weir ( branchId = 'someBranch' , chainage = 123.0 , allowedflowdir = FlowDirection . none , crestlevel = 0.0 ) struc . comments . crestlevel = \"This is a comment\" fm . geometry . structurefile = [ StructureModel ( structure = [ struc ])] # Add weir to the structure set/model and add this structure set to D-Flow FM model struc = Weir(branchId='someBranch', chainage = 123.0, allowedflowdir=FlowDirection.none, crestlevel=0.0) struc.comments.crestlevel = \"This is a comment\" fm.geometry.structurefile = [StructureModel(structure=[struc])] Note that the creation of a Weir and other model objects requires several input arguments. A ValidationError will be raised when the model is invalid or incomplete. For instance, in the above example, if the StructureModel had been assigned directly to structurefile instead of as a list, that would have triggered a ValidationError .","title":"Import HYDROLIB-core functionalities and setup D-Flow FM model"},{"location":"tutorials/build_basic_model/#setup-a-dimr-model","text":"Now let's add this model to an integrated model (DIMR config) and save it. In [ ]: Copied! from hydrolib.core.dimr.models import DIMR , FMComponent dimr = DIMR () dimr . component . append ( FMComponent ( name = \"test\" , workingDir = workdir , inputfile = mdufile , model = fm ) ) dimr_config = Path ( \"dimr_config.xml\" ) dimr . save ( filepath = dimr_config , recurse = True ) from hydrolib.core.dimr.models import DIMR, FMComponent dimr = DIMR() dimr.component.append( FMComponent(name=\"test\", workingDir=workdir, inputfile=mdufile, model=fm) ) dimr_config = Path(\"dimr_config.xml\") dimr.save(filepath=dimr_config, recurse=True)","title":"Setup a DIMR model"},{"location":"tutorials/build_basic_model/#the-model-files-on-disk","text":"Now, let's see which model input files were saved: In [ ]: Copied! dimr . show_tree () dimr.show_tree() The save call on the highest-level DIMR object will result in recursive saves of all child models in the model hierarchy, so this results in four files ( dimr_config.xml , network.nc , structures.ini , test.mdu ) in the working directory. Some more in-depth background about recursive saving of a model tree is given in another tutorial: Loading and saving .","title":"The model files on disk"},{"location":"tutorials/dataframe_handling/","text":"Dataframe handling \u00b6 We can use DataFrame s from pandas together with hydrolib-core. Note that this functionality can only work on files that are in essence tables and are represented by a List of objects in hydrolib-core. Examples of such ParsableFileModel s with their List fields are: - ForcingModel.forcing - CrossDefModel.definition - CrossLocModel.crosssection - ExtModel.boundary - ExtModel.lateral Say we load in a .bc file and want the resulting forcing in a dataframe. from hydrolib.core.dflowfm.bc.models import ForcingModel filepath = ( \"tests/data/input/e02/f101_1D-boundaries/c01_steady-state-flow/BoundaryConditions.bc\" ) m = ForcingModel ( filepath ) m . forcing [ Constant ( comments = None , datablock = [[ 2.5 ]], name = 'T1_Dwn_Bnd' , function = 'constant' , quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], offset = 0.0 , factor = 1.0 ), Constant ( comments = None , datablock = [[ 100.0 ]], name = 'T1_Up_Bnd' , function = 'constant' , quantityunitpair = [ QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], offset = 0.0 , factor = 1.0 ), Constant ( comments = None , datablock = [[ 2.5 ]], name = 'T2_Dwn_Bnd' , function = 'constant' , quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ 0.0 , 0.0 ], [ 1800.0 , 100.0 ], [ 4320.0 , 100.0 ]], name = 'T2_Up_Bnd' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ 0.0 , 0.0 ], [ 1800.0 , 2.5 ], [ 4320.0 , 2.5 ]], name = 'T3_Dwn_Bnd' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), Constant ( comments = None , datablock = [[ 100.0 ]], name = 'T3_Up_Bnd' , function = 'constant' , quantityunitpair = [ QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ 0.0 , 0.0 ], [ 1800.0 , 100.0 ], [ 4320.0 , 100.0 ]], name = 'T4_Up_Bnd' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), QHTable ( comments = None , datablock = [[ 50.0 , 1.25 ], [ 100.0 , 2.5 ], [ 150.0 , 3.75 ]], name = 'T4_Dwn_Bnd' , function = 'qhtable' , quantityunitpair = [ QuantityUnitPair ( quantity = 'qhbnd discharge' , unit = 'm\u00b3/s' ), QuantityUnitPair ( quantity = 'qhbnd waterlevel' , unit = 'm' )]), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'wind_speed' , unit = 'm/s' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'wind_from_direction' , unit = 'degree' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'air_temperature' , unit = 'degrees C' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'humidity' , unit = 'percentage' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'cloudiness' , unit = 'percentage' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 )] We now have a list of forcings that we can convert into a DataFrame. import pandas as pd df = pd . DataFrame ([ f . __dict__ for f in m . forcing ]) comments datablock name function ... offset factor _header timeinterpolation 0 None [[ 2.5 ]] T1_Dwn_Bnd constant ... 0.0 1.0 forcing linear 1 None [[ 100.0 ]] T1_Up_Bnd constant ... 0.0 1.0 forcing linear 2 None [[ 2.5 ]] T2_Dwn_Bnd constant ... 0.0 1.0 forcing linear 3 None [[ 0.0 , 0.0 ], [ 1800.0 , 100.0 ], [ 4320.0 , 100.0 ]] T2_Up_Bnd timeseries ... 0.0 1.0 forcing linear 4 None [[ 0.0 , 0.0 ], [ 1800.0 , 2.5 ], [ 4320.0 , 2.5 ]] T3_Dwn_Bnd timeseries ... 0.0 1.0 forcing linear 5 None [[ 100.0 ]] T3_Up_Bnd constant ... 0.0 1.0 forcing linear 6 None [[ 0.0 , 0.0 ], [ 1800.0 , 100.0 ], [ 4320.0 , 100.0 ]] T4_Up_Bnd timeseries ... 0.0 1.0 forcing linear 7 None [[ 50.0 , 1.25 ], [ 100.0 , 2.5 ], [ 150.0 , 3.75 ]] T4_Dwn_Bnd qhtable ... NaN NaN forcing NaN 8 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear 9 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear 10 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear 11 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear 12 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear [ 13 rows x 10 columns ] Note that because there are several types of forcings, with different fields, some values have become NaN. We can also convert this DataFrame back to a ForcingModel . fm = ForcingModel ( forcing = df . to_dict ( 'records' )) fm . forcing == m . forcing True","title":"Dataframe handling"},{"location":"tutorials/dataframe_handling/#dataframe-handling","text":"We can use DataFrame s from pandas together with hydrolib-core. Note that this functionality can only work on files that are in essence tables and are represented by a List of objects in hydrolib-core. Examples of such ParsableFileModel s with their List fields are: - ForcingModel.forcing - CrossDefModel.definition - CrossLocModel.crosssection - ExtModel.boundary - ExtModel.lateral Say we load in a .bc file and want the resulting forcing in a dataframe. from hydrolib.core.dflowfm.bc.models import ForcingModel filepath = ( \"tests/data/input/e02/f101_1D-boundaries/c01_steady-state-flow/BoundaryConditions.bc\" ) m = ForcingModel ( filepath ) m . forcing [ Constant ( comments = None , datablock = [[ 2.5 ]], name = 'T1_Dwn_Bnd' , function = 'constant' , quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], offset = 0.0 , factor = 1.0 ), Constant ( comments = None , datablock = [[ 100.0 ]], name = 'T1_Up_Bnd' , function = 'constant' , quantityunitpair = [ QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], offset = 0.0 , factor = 1.0 ), Constant ( comments = None , datablock = [[ 2.5 ]], name = 'T2_Dwn_Bnd' , function = 'constant' , quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ 0.0 , 0.0 ], [ 1800.0 , 100.0 ], [ 4320.0 , 100.0 ]], name = 'T2_Up_Bnd' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ 0.0 , 0.0 ], [ 1800.0 , 2.5 ], [ 4320.0 , 2.5 ]], name = 'T3_Dwn_Bnd' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), Constant ( comments = None , datablock = [[ 100.0 ]], name = 'T3_Up_Bnd' , function = 'constant' , quantityunitpair = [ QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ 0.0 , 0.0 ], [ 1800.0 , 100.0 ], [ 4320.0 , 100.0 ]], name = 'T4_Up_Bnd' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), QHTable ( comments = None , datablock = [[ 50.0 , 1.25 ], [ 100.0 , 2.5 ], [ 150.0 , 3.75 ]], name = 'T4_Dwn_Bnd' , function = 'qhtable' , quantityunitpair = [ QuantityUnitPair ( quantity = 'qhbnd discharge' , unit = 'm\u00b3/s' ), QuantityUnitPair ( quantity = 'qhbnd waterlevel' , unit = 'm' )]), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'wind_speed' , unit = 'm/s' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'wind_from_direction' , unit = 'degree' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'air_temperature' , unit = 'degrees C' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'humidity' , unit = 'percentage' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'cloudiness' , unit = 'percentage' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 )] We now have a list of forcings that we can convert into a DataFrame. import pandas as pd df = pd . DataFrame ([ f . __dict__ for f in m . forcing ]) comments datablock name function ... offset factor _header timeinterpolation 0 None [[ 2.5 ]] T1_Dwn_Bnd constant ... 0.0 1.0 forcing linear 1 None [[ 100.0 ]] T1_Up_Bnd constant ... 0.0 1.0 forcing linear 2 None [[ 2.5 ]] T2_Dwn_Bnd constant ... 0.0 1.0 forcing linear 3 None [[ 0.0 , 0.0 ], [ 1800.0 , 100.0 ], [ 4320.0 , 100.0 ]] T2_Up_Bnd timeseries ... 0.0 1.0 forcing linear 4 None [[ 0.0 , 0.0 ], [ 1800.0 , 2.5 ], [ 4320.0 , 2.5 ]] T3_Dwn_Bnd timeseries ... 0.0 1.0 forcing linear 5 None [[ 100.0 ]] T3_Up_Bnd constant ... 0.0 1.0 forcing linear 6 None [[ 0.0 , 0.0 ], [ 1800.0 , 100.0 ], [ 4320.0 , 100.0 ]] T4_Up_Bnd timeseries ... 0.0 1.0 forcing linear 7 None [[ 50.0 , 1.25 ], [ 100.0 , 2.5 ], [ 150.0 , 3.75 ]] T4_Dwn_Bnd qhtable ... NaN NaN forcing NaN 8 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear 9 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear 10 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear 11 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear 12 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear [ 13 rows x 10 columns ] Note that because there are several types of forcings, with different fields, some values have become NaN. We can also convert this DataFrame back to a ForcingModel . fm = ForcingModel ( forcing = df . to_dict ( 'records' )) fm . forcing == m . forcing True","title":"Dataframe handling"},{"location":"tutorials/loading_and_saving_a_model/","text":"Loading and saving a model \u00b6 In this article we will look at loading and saving a model. First we will load a model, and store it in a new location. Then make adjustments to one of the sub models, and store the model in place. Lastly, we will look at some caveats of saving and loading models. If you do not have a DIMR model, you can use the example model in the test data . Load the model \u00b6 We can load a model by constructing a new DIMR model by calling the DIMR with the file path to this model: # assuming the DIMR model is stored in your current working directory. model_path = Path ( \"./dimr_config.xml\" ) dimr_model = DIMR ( filepath = model_path ) It is also possible to not recursively load models: dimr_model = DIMR ( filepath = model_path , recurse = False ) This will only load a DIMR model without its underlying child file models, such as the Flow FM model. Save the model in a new location \u00b6 If we want to store the full model in a different location we can use the save function: # Adjust this new_path to a path convenient for you. new_path = Path ( \"some/other/path/dimr_config.xml\" ) dimr_model . save ( filepath = new_path , recurse = True ) By setting recurse to True we will ensure all files (which are supported by HYDROLIB-core) are written to the new location, relative to the file path of the root model. Providing the filepath argument has the same result as first setting the filepath, and then calling save: new_path = Path ( \"some/other/path/dimr_config.xml\" ) dimr_model . filepath = new_path dimr_model . save ( recurse = True ) As such, when calling filepath after save it should be the same as new_path . Once save has been called all files (supported by HYDROLIB-core) should be located in the parent folder. Adjust the model in a update it on disk \u00b6 Now that we have written our model in a different location, we can make some adjustments to it. We can retrieve the FM sub model as follows: fm_component = dimr_model . component [ 1 ] # Index 0 corresponds with the RRComponent. fm_model = fm_component . model We can adjust the model, by for example changing some of the properties. For example let's change the MapInterval from 60 to 30: fm_model . output . mapinterval = 30.0 With that change made we can go ahead and save just this specific sub model, in order to update the values on disk: fm_model . save () By default, if no filepath is selected, it will be stored in the current save_location . This should correspond with the place where it was last stored on disk. Furthermore, by default recurse is set to False , as such we will only rewrite the .mdu file. If we now inspect the .mdu file, we should see that the MapInterval in the output header has been set to 30: ... [output] ... MapInterval = 30.0 ... Loading models on case-sensitive systems \u00b6 Model files may contain references to other model files of which the casing does not match with the file on disk. On Windows, loading a model with differently cased references will work just fine, since Windows is case-insensitive. However on Linux, the referenced file cannot be found and will raise an error. To aid users in migrating their models, HYDROLIB-core offers a feature to resolve the casing of referenced files and supports three operating systems: Windows, Linux and MacOS. Consider an MDU model file that references a network file: Network/flowfm_net.nc . The file on disk is actually called network/FlowFM_net.nc . To load the model and simultaneously repair the file references in the in-memory model: from hydrolib.core.dflowfm.mdu.models import FMModel model = FMModel ( \"FlowFM.mdu\" , resolve_casing = True ) # assert that file reference has been updated from Network/flowfm_net.nc to network/FlowFM_net.nc assert model . geometry . netfile . filepath == Path ( \"network/FlowFM_net.nc\" ) The resolve_casing argument is by default False . Using the resolve_casing functionality might heavily influence the performance of model loading depending on the model size, the file tree structure and the operating system. Saving and loading models between different operating systems \u00b6 In certain cases, it may be necessary to switch effortlessly between operating systems (OS) using the same model. This allows the model to be loaded seamlessly on both Unix and Windows systems. However, it is important to note that the file paths look different for both OSs. Absolute file paths on Unix have a leading slash, while on Windows systems they start with a drive letter. Additionally, Unix systems don't allow backward slashes, whereas Windows supports both forward and backward slashes in file paths. These unique differences may cause issues when attempting to interpret files references within the model on another OS. Fortunately, HYDROLIB-core features a functionality that allows the conversion of file paths from one OS path style to another. This resolves the issue and ensures that the model functions seamlessly on both Unix and Windows systems. Examples \u00b6 Loading a model with Unix file paths on Windows: model = FMModel ( filepath = Path ( \"p:/model/FlowFM.mdu\" ), path_style = \"unix\" ) Loading a model with Windows file paths on Linux/MacOS: model = FMModel ( filepath = Path ( \"/p/model/FlowFM.mdu\" ), path_style = \"windows\" ) In the two examples mentioned above, the path_style option specifies the path style that is used in the model files to be loaded. This information allows HYDROLIB-core to accurately convert the file paths to match the path style of the running operating system and interpret them correctly. Saving a model with Unix file paths on Windows: model . save ( filepath = Path ( \"p:/model/FlowFM.mdu\" ), recurse = True , path_style = \"unix\" ) Saving a model with Windows file paths on Linux/MacOS: model . save ( filepath = Path ( \"/p/model/FlowFM.mdu\" ), recurse = True , path_style = \"windows\" ) In the two examples mentioned above, the path_style option specifies the preferred path style of the saved model files. However, if this option is not specified when initializing or saving the model, it will default to the path style of the current operating system. The path_style option supports these three values: * None (will default to either \"windows\" or \"unix\" depending on the running OS) * \"windows\" * \"unix\" Other values are not supported and an error will be raised. Caveats when saving models \u00b6 There are some caveats to take into account when saving models. Filepath changes do not automatically propagate \u00b6 When changing the filepath property of a parent model, the changes in save_location will not automatically propagate. As such, when saving a child model with a relative path, if the parent model's filepath has been changed, the child model will still be saved at its original save location. In order to update the save location, synchronize_filepaths should be called on the root model. Synchronizing filepaths is relative to the model it is called upon \u00b6 synchronize_filepaths will only update the file paths of child models. As such it will not propagate changes mode in a parent model: dimr_model.filepath = Path(\"some/other/path/dimr_config.xml\") fm_model.synchronize_filepaths() # This has no effect. Because the save_location of the fm_model has not been changed, none of the child models will change either. Furthermore, extra care needs to be taken when dealing with FM models with the pathsRelativeToParent set to False . This option will make all relative paths of child models relative to the .mdu . If synchronize_filepaths is called on a child model of the fm model, it will instead make all save_locations relative to this child model, which is incorrect. It is recommended to not use pathsRelativeToParent set to False .","title":"Loading and saving a model"},{"location":"tutorials/loading_and_saving_a_model/#loading-and-saving-a-model","text":"In this article we will look at loading and saving a model. First we will load a model, and store it in a new location. Then make adjustments to one of the sub models, and store the model in place. Lastly, we will look at some caveats of saving and loading models. If you do not have a DIMR model, you can use the example model in the test data .","title":"Loading and saving a model"},{"location":"tutorials/loading_and_saving_a_model/#load-the-model","text":"We can load a model by constructing a new DIMR model by calling the DIMR with the file path to this model: # assuming the DIMR model is stored in your current working directory. model_path = Path ( \"./dimr_config.xml\" ) dimr_model = DIMR ( filepath = model_path ) It is also possible to not recursively load models: dimr_model = DIMR ( filepath = model_path , recurse = False ) This will only load a DIMR model without its underlying child file models, such as the Flow FM model.","title":"Load the model"},{"location":"tutorials/loading_and_saving_a_model/#save-the-model-in-a-new-location","text":"If we want to store the full model in a different location we can use the save function: # Adjust this new_path to a path convenient for you. new_path = Path ( \"some/other/path/dimr_config.xml\" ) dimr_model . save ( filepath = new_path , recurse = True ) By setting recurse to True we will ensure all files (which are supported by HYDROLIB-core) are written to the new location, relative to the file path of the root model. Providing the filepath argument has the same result as first setting the filepath, and then calling save: new_path = Path ( \"some/other/path/dimr_config.xml\" ) dimr_model . filepath = new_path dimr_model . save ( recurse = True ) As such, when calling filepath after save it should be the same as new_path . Once save has been called all files (supported by HYDROLIB-core) should be located in the parent folder.","title":"Save the model in a new location"},{"location":"tutorials/loading_and_saving_a_model/#adjust-the-model-in-a-update-it-on-disk","text":"Now that we have written our model in a different location, we can make some adjustments to it. We can retrieve the FM sub model as follows: fm_component = dimr_model . component [ 1 ] # Index 0 corresponds with the RRComponent. fm_model = fm_component . model We can adjust the model, by for example changing some of the properties. For example let's change the MapInterval from 60 to 30: fm_model . output . mapinterval = 30.0 With that change made we can go ahead and save just this specific sub model, in order to update the values on disk: fm_model . save () By default, if no filepath is selected, it will be stored in the current save_location . This should correspond with the place where it was last stored on disk. Furthermore, by default recurse is set to False , as such we will only rewrite the .mdu file. If we now inspect the .mdu file, we should see that the MapInterval in the output header has been set to 30: ... [output] ... MapInterval = 30.0 ...","title":"Adjust the model in a update it on disk"},{"location":"tutorials/loading_and_saving_a_model/#loading-models-on-case-sensitive-systems","text":"Model files may contain references to other model files of which the casing does not match with the file on disk. On Windows, loading a model with differently cased references will work just fine, since Windows is case-insensitive. However on Linux, the referenced file cannot be found and will raise an error. To aid users in migrating their models, HYDROLIB-core offers a feature to resolve the casing of referenced files and supports three operating systems: Windows, Linux and MacOS. Consider an MDU model file that references a network file: Network/flowfm_net.nc . The file on disk is actually called network/FlowFM_net.nc . To load the model and simultaneously repair the file references in the in-memory model: from hydrolib.core.dflowfm.mdu.models import FMModel model = FMModel ( \"FlowFM.mdu\" , resolve_casing = True ) # assert that file reference has been updated from Network/flowfm_net.nc to network/FlowFM_net.nc assert model . geometry . netfile . filepath == Path ( \"network/FlowFM_net.nc\" ) The resolve_casing argument is by default False . Using the resolve_casing functionality might heavily influence the performance of model loading depending on the model size, the file tree structure and the operating system.","title":"Loading models on case-sensitive systems"},{"location":"tutorials/loading_and_saving_a_model/#saving-and-loading-models-between-different-operating-systems","text":"In certain cases, it may be necessary to switch effortlessly between operating systems (OS) using the same model. This allows the model to be loaded seamlessly on both Unix and Windows systems. However, it is important to note that the file paths look different for both OSs. Absolute file paths on Unix have a leading slash, while on Windows systems they start with a drive letter. Additionally, Unix systems don't allow backward slashes, whereas Windows supports both forward and backward slashes in file paths. These unique differences may cause issues when attempting to interpret files references within the model on another OS. Fortunately, HYDROLIB-core features a functionality that allows the conversion of file paths from one OS path style to another. This resolves the issue and ensures that the model functions seamlessly on both Unix and Windows systems.","title":"Saving and loading models between different operating systems"},{"location":"tutorials/loading_and_saving_a_model/#examples","text":"Loading a model with Unix file paths on Windows: model = FMModel ( filepath = Path ( \"p:/model/FlowFM.mdu\" ), path_style = \"unix\" ) Loading a model with Windows file paths on Linux/MacOS: model = FMModel ( filepath = Path ( \"/p/model/FlowFM.mdu\" ), path_style = \"windows\" ) In the two examples mentioned above, the path_style option specifies the path style that is used in the model files to be loaded. This information allows HYDROLIB-core to accurately convert the file paths to match the path style of the running operating system and interpret them correctly. Saving a model with Unix file paths on Windows: model . save ( filepath = Path ( \"p:/model/FlowFM.mdu\" ), recurse = True , path_style = \"unix\" ) Saving a model with Windows file paths on Linux/MacOS: model . save ( filepath = Path ( \"/p/model/FlowFM.mdu\" ), recurse = True , path_style = \"windows\" ) In the two examples mentioned above, the path_style option specifies the preferred path style of the saved model files. However, if this option is not specified when initializing or saving the model, it will default to the path style of the current operating system. The path_style option supports these three values: * None (will default to either \"windows\" or \"unix\" depending on the running OS) * \"windows\" * \"unix\" Other values are not supported and an error will be raised.","title":"Examples"},{"location":"tutorials/loading_and_saving_a_model/#caveats-when-saving-models","text":"There are some caveats to take into account when saving models.","title":"Caveats when saving models"},{"location":"tutorials/loading_and_saving_a_model/#filepath-changes-do-not-automatically-propagate","text":"When changing the filepath property of a parent model, the changes in save_location will not automatically propagate. As such, when saving a child model with a relative path, if the parent model's filepath has been changed, the child model will still be saved at its original save location. In order to update the save location, synchronize_filepaths should be called on the root model.","title":"Filepath changes do not automatically propagate"},{"location":"tutorials/loading_and_saving_a_model/#synchronizing-filepaths-is-relative-to-the-model-it-is-called-upon","text":"synchronize_filepaths will only update the file paths of child models. As such it will not propagate changes mode in a parent model: dimr_model.filepath = Path(\"some/other/path/dimr_config.xml\") fm_model.synchronize_filepaths() # This has no effect. Because the save_location of the fm_model has not been changed, none of the child models will change either. Furthermore, extra care needs to be taken when dealing with FM models with the pathsRelativeToParent set to False . This option will make all relative paths of child models relative to the .mdu . If synchronize_filepaths is called on a child model of the fm model, it will instead make all save_locations relative to this child model, which is incorrect. It is recommended to not use pathsRelativeToParent set to False .","title":"Synchronizing filepaths is relative to the model it is called upon"},{"location":"tutorials/plotting_a_network/","text":"Plotting a network \u00b6 We can visualise a Network with the following code: from hydrolib.core.dflowfm.net.models import Network import matplotlib from matplotlib.collections import LineCollection import numpy as np def plot ( network : Network , ax : matplotlib . axes . _subplots . AxesSubplot , mesh1d_kwargs : dict = None , mesh2d_kwargs : dict = None , links1d2d_kwargs : dict = None , ) -> None : if mesh1d_kwargs is None : mesh1d_kwargs = { \"color\" : \"C3\" , \"lw\" : 1.0 } if mesh2d_kwargs is None : mesh2d_kwargs = { \"color\" : \"C0\" , \"lw\" : 0.5 } if links1d2d_kwargs is None : links1d2d_kwargs = { \"color\" : \"k\" , \"lw\" : 1.0 } # Mesh 1d if not network . _mesh1d . is_empty (): nodes1d = np . stack ( [ network . _mesh1d . mesh1d_node_x , network . _mesh1d . mesh1d_node_y ], axis = 1 ) edge_nodes = network . _mesh1d . mesh1d_edge_nodes lc_mesh1d = LineCollection ( nodes1d [ edge_nodes ], ** mesh1d_kwargs ) ax . add_collection ( lc_mesh1d ) # Mesh 2d if not network . _mesh2d . is_empty (): nodes2d = np . stack ( [ network . _mesh2d . mesh2d_node_x , network . _mesh2d . mesh2d_node_y ], axis = 1 ) edge_nodes = network . _mesh2d . mesh2d_edge_nodes lc_mesh2d = LineCollection ( nodes2d [ edge_nodes ], ** mesh2d_kwargs ) ax . add_collection ( lc_mesh2d ) # Links if not network . _link1d2d . is_empty (): faces2d = np . stack ( [ network . _mesh2d . mesh2d_face_x , network . _mesh2d . mesh2d_face_y ], axis = 1 ) link_coords = np . stack ( [ nodes1d [ network . _link1d2d . link1d2d [:, 0 ]], faces2d [ network . _link1d2d . link1d2d [:, 1 ]], ], axis = 1 , ) lc_link1d2d = LineCollection ( link_coords , ** links1d2d_kwargs ) ax . add_collection ( lc_link1d2d )","title":"Plotting a network"},{"location":"tutorials/plotting_a_network/#plotting-a-network","text":"We can visualise a Network with the following code: from hydrolib.core.dflowfm.net.models import Network import matplotlib from matplotlib.collections import LineCollection import numpy as np def plot ( network : Network , ax : matplotlib . axes . _subplots . AxesSubplot , mesh1d_kwargs : dict = None , mesh2d_kwargs : dict = None , links1d2d_kwargs : dict = None , ) -> None : if mesh1d_kwargs is None : mesh1d_kwargs = { \"color\" : \"C3\" , \"lw\" : 1.0 } if mesh2d_kwargs is None : mesh2d_kwargs = { \"color\" : \"C0\" , \"lw\" : 0.5 } if links1d2d_kwargs is None : links1d2d_kwargs = { \"color\" : \"k\" , \"lw\" : 1.0 } # Mesh 1d if not network . _mesh1d . is_empty (): nodes1d = np . stack ( [ network . _mesh1d . mesh1d_node_x , network . _mesh1d . mesh1d_node_y ], axis = 1 ) edge_nodes = network . _mesh1d . mesh1d_edge_nodes lc_mesh1d = LineCollection ( nodes1d [ edge_nodes ], ** mesh1d_kwargs ) ax . add_collection ( lc_mesh1d ) # Mesh 2d if not network . _mesh2d . is_empty (): nodes2d = np . stack ( [ network . _mesh2d . mesh2d_node_x , network . _mesh2d . mesh2d_node_y ], axis = 1 ) edge_nodes = network . _mesh2d . mesh2d_edge_nodes lc_mesh2d = LineCollection ( nodes2d [ edge_nodes ], ** mesh2d_kwargs ) ax . add_collection ( lc_mesh2d ) # Links if not network . _link1d2d . is_empty (): faces2d = np . stack ( [ network . _mesh2d . mesh2d_face_x , network . _mesh2d . mesh2d_face_y ], axis = 1 ) link_coords = np . stack ( [ nodes1d [ network . _link1d2d . link1d2d [:, 0 ]], faces2d [ network . _link1d2d . link1d2d [:, 1 ]], ], axis = 1 , ) lc_link1d2d = LineCollection ( link_coords , ** links1d2d_kwargs ) ax . add_collection ( lc_link1d2d )","title":"Plotting a network"},{"location":"tutorials/tutorials/","text":"Introduction to tutorials \u00b6 The tutorials below can help you becoming familiar with the basics as well as the more advanced use of HYDROLIB-core: Tutorial: Build a basic model - iPython notebook Tutorial: Loading and saving a model Tutorial: Dataframe handling Tutorial: Plotting a network To run these examples on your local machine you need a copy of the repository and an installation of HYDROLIB-core including some additional packages. The installation of HYDROLIB-core is explained in Installation . The tutorials are then located in docs/tutorials/ .","title":"Introduction to tutorials"},{"location":"tutorials/tutorials/#introduction-to-tutorials","text":"The tutorials below can help you becoming familiar with the basics as well as the more advanced use of HYDROLIB-core: Tutorial: Build a basic model - iPython notebook Tutorial: Loading and saving a model Tutorial: Dataframe handling Tutorial: Plotting a network To run these examples on your local machine you need a copy of the repository and an installation of HYDROLIB-core including some additional packages. The installation of HYDROLIB-core is explained in Installation . 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When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(0, 0, 0, 1); --jp-content-font-color1: rgba(0, 0, 0, 0.87); --jp-content-font-color2: rgba(0, 0, 0, 0.54); --jp-content-font-color3: rgba(0, 0, 0, 0.38); --jp-content-link-color: var(--md-blue-700); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: white; --jp-layout-color1: white; --jp-layout-color2: var(--md-grey-200); --jp-layout-color3: var(--md-grey-400); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: #111111; --jp-inverse-layout-color1: var(--md-grey-900); --jp-inverse-layout-color2: var(--md-grey-800); --jp-inverse-layout-color3: var(--md-grey-700); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-900); --jp-brand-color1: var(--md-blue-700); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-900); --jp-accent-color1: var(--md-green-700); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-900); --jp-warn-color1: var(--md-orange-700); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-900); --jp-error-color1: var(--md-red-700); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-900); --jp-success-color1: var(--md-green-700); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-900); --jp-info-color1: var(--md-cyan-700); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--md-grey-100); --jp-cell-editor-border-color: var(--md-grey-300); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 0.5; --jp-cell-prompt-not-active-font-color: var(--md-grey-700); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: var(--md-blue-50); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: #fdd; --jp-rendermime-table-row-background: var(--md-grey-100); --jp-rendermime-table-row-hover-background: var(--md-light-blue-50); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.25); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color1); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.24); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--md-grey-300); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color1); --jp-input-hover-background: var(--jp-layout-color1); --jp-input-background: var(--md-grey-100); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: #d9d9d9; --jp-editor-selected-focused-background: #d7d4f0; --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: #008000; --jp-mirror-editor-atom-color: #88f; --jp-mirror-editor-number-color: #080; --jp-mirror-editor-def-color: #00f; --jp-mirror-editor-variable-color: var(--md-grey-900); --jp-mirror-editor-variable-2-color: #05a; --jp-mirror-editor-variable-3-color: #085; --jp-mirror-editor-punctuation-color: #05a; --jp-mirror-editor-property-color: #05a; --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ba2121; --jp-mirror-editor-string-2-color: #708; --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: #008000; --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: #170; --jp-mirror-editor-attribute-color: #00c; --jp-mirror-editor-header-color: blue; --jp-mirror-editor-quote-color: #090; --jp-mirror-editor-link-color: #00c; --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: white; /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.5; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(245, 200, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } [data-md-color-scheme=\"slate\"] .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ /* The dark theme shadows need a bit of work, but this will probably also require work on the core layout * colors used in the theme as well. */ --jp-shadow-base-lightness: 32; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-700); --jp-border-color1: var(--md-grey-700); --jp-border-color2: var(--md-grey-800); --jp-border-color3: var(--md-grey-900); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(255, 255, 255, 1); --jp-ui-font-color1: rgba(255, 255, 255, 0.87); --jp-ui-font-color2: rgba(255, 255, 255, 0.54); --jp-ui-font-color3: rgba(255, 255, 255, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(0, 0, 0, 1); --jp-ui-inverse-font-color1: rgba(0, 0, 0, 0.8); --jp-ui-inverse-font-color2: rgba(0, 0, 0, 0.5); --jp-ui-inverse-font-color3: rgba(0, 0, 0, 0.3); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(255, 255, 255, 1); --jp-content-font-color1: rgba(255, 255, 255, 1); --jp-content-font-color2: rgba(255, 255, 255, 0.7); --jp-content-font-color3: rgba(255, 255, 255, 0.5); --jp-content-link-color: var(--md-blue-300); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: #111111; --jp-layout-color1: var(--md-grey-900); --jp-layout-color2: var(--md-grey-800); --jp-layout-color3: var(--md-grey-700); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: white; --jp-inverse-layout-color1: white; --jp-inverse-layout-color2: var(--md-grey-200); --jp-inverse-layout-color3: var(--md-grey-400); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-700); --jp-brand-color1: var(--md-blue-500); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-700); --jp-accent-color1: var(--md-green-500); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-700); --jp-warn-color1: var(--md-orange-500); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-700); --jp-error-color1: var(--md-red-500); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-700); --jp-success-color1: var(--md-green-500); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-700); --jp-info-color1: var(--md-cyan-500); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--jp-layout-color1); --jp-cell-editor-border-color: var(--md-grey-700); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 1; --jp-cell-prompt-not-active-font-color: var(--md-grey-300); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: rgba(33, 150, 243, 0.24); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: rgba(244, 67, 54, 0.28); --jp-rendermime-table-row-background: var(--md-grey-900); --jp-rendermime-table-row-hover-background: rgba(3, 169, 244, 0.2); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.6); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color2); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.8); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--jp-layout-color0); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color0); --jp-input-hover-background: var(--jp-layout-color2); --jp-input-background: var(--md-grey-800); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: var(--jp-layout-color2); --jp-editor-selected-focused-background: rgba(33, 150, 243, 0.24); --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: var(--md-green-500); --jp-mirror-editor-atom-color: var(--md-blue-300); --jp-mirror-editor-number-color: var(--md-green-400); --jp-mirror-editor-def-color: var(--md-blue-600); --jp-mirror-editor-variable-color: var(--md-grey-300); --jp-mirror-editor-variable-2-color: var(--md-blue-400); --jp-mirror-editor-variable-3-color: var(--md-green-600); --jp-mirror-editor-punctuation-color: var(--md-blue-400); --jp-mirror-editor-property-color: var(--md-blue-400); --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ff7070; --jp-mirror-editor-string-2-color: var(--md-purple-300); --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: var(--md-green-600); --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: var(--md-green-700); --jp-mirror-editor-attribute-color: var(--md-blue-700); --jp-mirror-editor-header-color: var(--md-blue-500); --jp-mirror-editor-quote-color: var(--md-green-300); --jp-mirror-editor-link-color: var(--md-blue-700); --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: var(--md-grey-400); /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.6; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(255, 225, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* scrollbar related styles. Supports every browser except Edge. */ /* colors based on JetBrain's Darcula theme */ --jp-scrollbar-background-color: #3f4244; --jp-scrollbar-thumb-color: 88, 96, 97; /* need to specify thumb color as an RGB triplet */ --jp-scrollbar-endpad: 3px; /* the minimum gap between the thumb and the ends of a scrollbar */ /* hacks for setting the thumb shape. 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sourceMappingURL=mkdocs-jupyter.css.map*/ init_mathjax = function() { if (window.MathJax) { // MathJax loaded MathJax.Hub.Config({ TeX: { equationNumbers: { autoNumber: \"AMS\", useLabelIds: true } }, tex2jax: { inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ], displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ], processEscapes: true, processEnvironments: true }, displayAlign: 'center', CommonHTML: { linebreaks: { automatic: true } } }); MathJax.Hub.Queue([\"Typeset\", MathJax.Hub]); } } init_mathjax(); Deltares Software Days 2022: A simple hydrolib-core demo \u00b6 Hydrolib-core is a pip-installable python package. It consists of wrappers around the D-HYDRO model files. Classes in Hydrolib-core are hierarchically organized by file type, and can be accessed via hydrolib.core.io..models . File objects in Hydrolib-core reflect the same structure as the file contents. In this demo, we will load a Flow FM model, make some changes to the model and save it again. \ud83d\udca1 Tips for working in the Jupyter Notebook: Tab : Auto-complete on code Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell Ctrl + Shift + P : Open command palette Step 0) Importing the modules and setting the path variables \u00b6 In [ ]: Copied! from hydrolib.core.dflowfm import ( FMModel , Lateral , Weir , FlowDirection ) from pathlib import Path root = Path . cwd () demo_data_folder = root / \"data\" work_folder = root / \"work\" from hydrolib.core.dflowfm import ( FMModel, Lateral, Weir, FlowDirection ) from pathlib import Path root = Path.cwd() demo_data_folder = root / \"data\" work_folder = root / \"work\" Step 1) Loading a Flow FM model \u00b6 In [ ]: Copied! mdu_file_path = demo_data_folder / \"FlowFM.mdu\" model = FMModel ( filepath = mdu_file_path ) print ( f \"Loaded the model from { model . filepath } \" ) mdu_file_path = demo_data_folder / \"FlowFM.mdu\" model = FMModel(filepath=mdu_file_path) print(f\"Loaded the model from {model.filepath}\") Step 2) Inspecting the model \u00b6 We can see the hierarchy tree of the model by calling the following function: In [ ]: Copied! model . show_tree () model.show_tree() We can also inspect sub-parts of the model, like the structures. Note that a model can have multiple structure files, but this model only has one, so we will get the first and only one. In [ ]: Copied! assert model . geometry . structurefile is not None structure_file = model . geometry . structurefile [ 0 ] # Show the list of all the structures print ( f \"Number of structures: { len ( structure_file . structure ) } \" ) print ( structure_file . structure ) assert model.geometry.structurefile is not None structure_file = model.geometry.structurefile[0] # Show the list of all the structures print(f\"Number of structures: {len(structure_file.structure)}\") print(structure_file.structure) Step 3) Adjusting the model \u00b6 a) Creating a new weir and adding it to the structures \u00b6 In [ ]: Copied! # Create a new weir. weir = Weir ( id = \"DV_1471\" , branchId = \"458\" , chainage = 106.277467 , allowedFlowDir = FlowDirection . both , crestLevel = 0.400 , crestWidth = 40.000 , corrCoeff = 1.000 , useVelocityHeight = True ) # It is also possible to create objects with a dictionary. weir_data = { \"id\" : \"DV_1471\" , \"branchId\" : \"458\" , \"chainage\" : 106.277467 , \"allowedFlowDir\" : FlowDirection . both , \"crestLevel\" : 0.400 , \"crestWidth\" : 40.000 , \"corrCoeff\" : 1.000 , \"useVelocityHeight\" : True } weir = Weir ( ** weir_data ) # Add the weir to the model structure_file . structure . append ( weir ) print ( f \"Number of structures: { len ( structure_file . structure ) } \" ) # Create a new weir. weir = Weir( id=\"DV_1471\", branchId=\"458\", chainage=106.277467, allowedFlowDir=FlowDirection.both, crestLevel=0.400, crestWidth=40.000, corrCoeff=1.000, useVelocityHeight=True ) # It is also possible to create objects with a dictionary. weir_data = { \"id\": \"DV_1471\", \"branchId\": \"458\", \"chainage\": 106.277467, \"allowedFlowDir\": FlowDirection.both, \"crestLevel\": 0.400, \"crestWidth\": 40.000, \"corrCoeff\": 1.000, \"useVelocityHeight\": True } weir = Weir(**weir_data) # Add the weir to the model structure_file.structure.append(weir) print(f\"Number of structures: {len(structure_file.structure)}\") b) Adjusting some parameters of the model \u00b6 In [ ]: Copied! model . physics . backgroundsalinity = 30 # [ppt] model . physics . backgroundwatertemperature = 6 # [\u00b0C] model . time . dtuser = 900 # [s] model.physics.backgroundsalinity = 30 # [ppt] model.physics.backgroundwatertemperature = 6 # [\u00b0C] model.time.dtuser = 900 # [s] Hydrolib-core offers instant validation of objects that are created, either by loading them from file or by manually creating them. This makes it easier for users to create valid models. A lateral, like many other objects, should have a valid location specification, specified by: A node id, A branch id with a chainage, or Coordinates Let's create an invalid Lateral. We \"forget\" to specify a chainage. In [ ]: Copied! try : lateral = Lateral ( id = \"lateral_1\" , name = \"lateral_1\" , branchid = \"branch_a\" , discharge = \"realtime\" ) except ValueError as error : print ( error ) try: lateral = Lateral( id=\"lateral_1\", name=\"lateral_1\", branchid=\"branch_a\", discharge=\"realtime\" ) except ValueError as error: print(error) Now let's create a valid lateral. In [ ]: Copied! lateral = Lateral ( id = \"lateral_1\" , name = \"lateral_1\" , branchid = \"branch_a\" , chainage = 100 , discharge = \"realtime\" ) print ( \"Lateral with branch id and chainage is correct!\" ) lateral = Lateral( id=\"lateral_1\", name=\"lateral_1\", branchid=\"branch_a\", chainage=100, discharge=\"realtime\" ) print(\"Lateral with branch id and chainage is correct!\") Step 5) Saving the model \u00b6 If we save the model now, it will overwrite the current model files. So let's save it in a different location. In [ ]: Copied! print ( f \"The original model is located at { model . filepath } \" ) save_mdu_file_path = work_folder / \"save_model\" / \"FlowFM.mdu\" model . filepath = save_mdu_file_path # Set recurse to True. If it is False, only the MDU file will be saved. model . save ( recurse = True ) print ( f \"The saved model is located at { model . filepath } \" ) print(f\"The original model is located at {model.filepath}\") save_mdu_file_path = work_folder / \"save_model\" / \"FlowFM.mdu\" model.filepath = save_mdu_file_path # Set recurse to True. If it is False, only the MDU file will be saved. model.save(recurse=True) print(f\"The saved model is located at {model.filepath}\") Saving only a sub-part of the model \u00b6 It is also possible to save individual child model files, such as the cross section definition file. In [ ]: Copied! crossdef_file = model . geometry . crossdeffile assert crossdef_file is not None crossdef_file . filepath = work_folder / \"save_crossdef\" / \"crsdef.ini\" crossdef_file . save () print ( f \"The saved cross section definition model is located at { crossdef_file . filepath } \" ) crossdef_file = model.geometry.crossdeffile assert crossdef_file is not None crossdef_file.filepath = work_folder / \"save_crossdef\" / \"crsdef.ini\" crossdef_file.save() print(f\"The saved cross section definition model is located at {crossdef_file.filepath}\") In [ ]: Copied!","title":"Deltares Software Days 2022: A simple hydrolib-core demo"},{"location":"tutorials/dsd_2022_demo/demo_dsd/#deltares-software-days-2022-a-simple-hydrolib-core-demo","text":"Hydrolib-core is a pip-installable python package. It consists of wrappers around the D-HYDRO model files. Classes in Hydrolib-core are hierarchically organized by file type, and can be accessed via hydrolib.core.io..models . File objects in Hydrolib-core reflect the same structure as the file contents. In this demo, we will load a Flow FM model, make some changes to the model and save it again. \ud83d\udca1 Tips for working in the Jupyter Notebook: Tab : Auto-complete on code Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell Ctrl + Shift + P : Open command palette","title":"Deltares Software Days 2022: A simple hydrolib-core demo"},{"location":"tutorials/dsd_2022_demo/demo_dsd/#step-0-importing-the-modules-and-setting-the-path-variables","text":"In [ ]: Copied! from hydrolib.core.dflowfm import ( FMModel , Lateral , Weir , FlowDirection ) from pathlib import Path root = Path . cwd () demo_data_folder = root / \"data\" work_folder = root / \"work\" from hydrolib.core.dflowfm import ( FMModel, Lateral, Weir, FlowDirection ) from pathlib import Path root = Path.cwd() demo_data_folder = root / \"data\" work_folder = root / \"work\"","title":"Step 0) Importing the modules and setting the path variables"},{"location":"tutorials/dsd_2022_demo/demo_dsd/#step-1-loading-a-flow-fm-model","text":"In [ ]: Copied! mdu_file_path = demo_data_folder / \"FlowFM.mdu\" model = FMModel ( filepath = mdu_file_path ) print ( f \"Loaded the model from { model . filepath } \" ) mdu_file_path = demo_data_folder / \"FlowFM.mdu\" model = FMModel(filepath=mdu_file_path) print(f\"Loaded the model from {model.filepath}\")","title":"Step 1) Loading a Flow FM model"},{"location":"tutorials/dsd_2022_demo/demo_dsd/#step-2-inspecting-the-model","text":"We can see the hierarchy tree of the model by calling the following function: In [ ]: Copied! model . show_tree () model.show_tree() We can also inspect sub-parts of the model, like the structures. Note that a model can have multiple structure files, but this model only has one, so we will get the first and only one. In [ ]: Copied! assert model . geometry . structurefile is not None structure_file = model . geometry . structurefile [ 0 ] # Show the list of all the structures print ( f \"Number of structures: { len ( structure_file . structure ) } \" ) print ( structure_file . structure ) assert model.geometry.structurefile is not None structure_file = model.geometry.structurefile[0] # Show the list of all the structures print(f\"Number of structures: {len(structure_file.structure)}\") print(structure_file.structure)","title":"Step 2) Inspecting the model"},{"location":"tutorials/dsd_2022_demo/demo_dsd/#step-3-adjusting-the-model","text":"","title":"Step 3) Adjusting the model"},{"location":"tutorials/dsd_2022_demo/demo_dsd/#a-creating-a-new-weir-and-adding-it-to-the-structures","text":"In [ ]: Copied! # Create a new weir. weir = Weir ( id = \"DV_1471\" , branchId = \"458\" , chainage = 106.277467 , allowedFlowDir = FlowDirection . both , crestLevel = 0.400 , crestWidth = 40.000 , corrCoeff = 1.000 , useVelocityHeight = True ) # It is also possible to create objects with a dictionary. weir_data = { \"id\" : \"DV_1471\" , \"branchId\" : \"458\" , \"chainage\" : 106.277467 , \"allowedFlowDir\" : FlowDirection . both , \"crestLevel\" : 0.400 , \"crestWidth\" : 40.000 , \"corrCoeff\" : 1.000 , \"useVelocityHeight\" : True } weir = Weir ( ** weir_data ) # Add the weir to the model structure_file . structure . append ( weir ) print ( f \"Number of structures: { len ( structure_file . structure ) } \" ) # Create a new weir. weir = Weir( id=\"DV_1471\", branchId=\"458\", chainage=106.277467, allowedFlowDir=FlowDirection.both, crestLevel=0.400, crestWidth=40.000, corrCoeff=1.000, useVelocityHeight=True ) # It is also possible to create objects with a dictionary. weir_data = { \"id\": \"DV_1471\", \"branchId\": \"458\", \"chainage\": 106.277467, \"allowedFlowDir\": FlowDirection.both, \"crestLevel\": 0.400, \"crestWidth\": 40.000, \"corrCoeff\": 1.000, \"useVelocityHeight\": True } weir = Weir(**weir_data) # Add the weir to the model structure_file.structure.append(weir) print(f\"Number of structures: {len(structure_file.structure)}\")","title":"a) Creating a new weir and adding it to the structures"},{"location":"tutorials/dsd_2022_demo/demo_dsd/#b-adjusting-some-parameters-of-the-model","text":"In [ ]: Copied! model . physics . backgroundsalinity = 30 # [ppt] model . physics . backgroundwatertemperature = 6 # [\u00b0C] model . time . dtuser = 900 # [s] model.physics.backgroundsalinity = 30 # [ppt] model.physics.backgroundwatertemperature = 6 # [\u00b0C] model.time.dtuser = 900 # [s] Hydrolib-core offers instant validation of objects that are created, either by loading them from file or by manually creating them. This makes it easier for users to create valid models. A lateral, like many other objects, should have a valid location specification, specified by: A node id, A branch id with a chainage, or Coordinates Let's create an invalid Lateral. We \"forget\" to specify a chainage. In [ ]: Copied! try : lateral = Lateral ( id = \"lateral_1\" , name = \"lateral_1\" , branchid = \"branch_a\" , discharge = \"realtime\" ) except ValueError as error : print ( error ) try: lateral = Lateral( id=\"lateral_1\", name=\"lateral_1\", branchid=\"branch_a\", discharge=\"realtime\" ) except ValueError as error: print(error) Now let's create a valid lateral. In [ ]: Copied! lateral = Lateral ( id = \"lateral_1\" , name = \"lateral_1\" , branchid = \"branch_a\" , chainage = 100 , discharge = \"realtime\" ) print ( \"Lateral with branch id and chainage is correct!\" ) lateral = Lateral( id=\"lateral_1\", name=\"lateral_1\", branchid=\"branch_a\", chainage=100, discharge=\"realtime\" ) print(\"Lateral with branch id and chainage is correct!\")","title":"b) Adjusting some parameters of the model"},{"location":"tutorials/dsd_2022_demo/demo_dsd/#step-5-saving-the-model","text":"If we save the model now, it will overwrite the current model files. So let's save it in a different location. In [ ]: Copied! print ( f \"The original model is located at { model . filepath } \" ) save_mdu_file_path = work_folder / \"save_model\" / \"FlowFM.mdu\" model . filepath = save_mdu_file_path # Set recurse to True. If it is False, only the MDU file will be saved. model . save ( recurse = True ) print ( f \"The saved model is located at { model . filepath } \" ) print(f\"The original model is located at {model.filepath}\") save_mdu_file_path = work_folder / \"save_model\" / \"FlowFM.mdu\" model.filepath = save_mdu_file_path # Set recurse to True. If it is False, only the MDU file will be saved. model.save(recurse=True) print(f\"The saved model is located at {model.filepath}\")","title":"Step 5) Saving the model"},{"location":"tutorials/dsd_2022_demo/demo_dsd/#saving-only-a-sub-part-of-the-model","text":"It is also possible to save individual child model files, such as the cross section definition file. In [ ]: Copied! crossdef_file = model . geometry . crossdeffile assert crossdef_file is not None crossdef_file . filepath = work_folder / \"save_crossdef\" / \"crsdef.ini\" crossdef_file . save () print ( f \"The saved cross section definition model is located at { crossdef_file . filepath } \" ) crossdef_file = model.geometry.crossdeffile assert crossdef_file is not None crossdef_file.filepath = work_folder / \"save_crossdef\" / \"crsdef.ini\" crossdef_file.save() print(f\"The saved cross section definition model is located at {crossdef_file.filepath}\") In [ ]: Copied!","title":"Saving only a sub-part of the model"},{"location":"tutorials/dsd_2023/instructions/","text":"HYDROLIB-core guide for the Delft Software Days 2023 \u00b6 Contents \u00b6 HYDROLIB-core guide for the Delft Software Days 2023 Contents Introduction User guide Requirements Installation Run the demo notebook Cheat sheet Kernel files vs HYDROLIB-core FileModels Commonly used functions of a FileModel Introduction \u00b6 This document contains instructions about the installation and usage of HYDROLIB-core during the Delft Software Days 2023. HYDROLIB-core is a Python package that offers functionality to process D-HYDRO input files. It offers Python-wrapped classes that represent these files and their content. HYDROLIB-core serves as the basis for various pre- and postprocessing tools for a modelling workflow of hydrodynamic simulations in D-HYDRO. User guide \u00b6 Requirements \u00b6 Before getting started with HYDROLIB-core, make sure you have the following software and tools installed: Anaconda : https://www.anaconda.com/download Anaconda is an open-source distribution for Python and contains the package manager \"conda\". (!) Make sure to add Anaconda to your PATH environment variable during installation. Installation \u00b6 Once you've installed the required software, you can create a Python 3.11 environment with HYDROLIB-core 0.5.2, the latest release. Note that the environment that we are creating now contains not only HYDROLIB-core, but also the other packages that are needed today during the breakout sessions. Follow these steps: Open your command line interface Enter the following commands: conda create --name dsd_env python=3.11 git -c conda-forge -y conda activate dsd_env pip install hydromt_delft3dfm[examples] dfm_tools pyogrio openpyxl conda deactivate After executing these commands, an Anaconda environment with the latest HYDROLIB-core is created. After deactivation, you can reactivate this environment at any time by using the following command: conda activate dsd_env If you'd like to remove the environment entirely, call the following command: conda remove -n dsd_env --all This will remove all the packages in the environment and the environment folder itself. Run the demo notebook \u00b6 We'd like to be able to run the provided demo notebook. We can set it up with the following steps: Open a command line in the HYDROLIB-core folder Activate the conda environment: conda activate dsd_env And start Jupyter Notebook: jupyter notebook Open the demo.ipynb inside the demo folder Cheat sheet \u00b6 In HYDROLIB-core, there is a class called FileModel, which is used to represent an individual kernel file. This class has multiple derived implementations, with each one corresponding to a specific kernel file. Every FileModel, except for the root model, is referenced within another FileModel, following the same hierarchy as the kernel files themselves. The table below contains the models relevant for today's exercises. Kernel files vs HYDROLIB-core FileModels \u00b6 Kernel file FileModel File reference Model definition file (*.mdu) FMModel - Network file (*_net.nc) NetworkModel Model definition file > geometry > netFile Cross-section location file (crosloc.ini) CrossLocModel Model definition file > geometry > crossLocFile Cross-section definition file (crosdef.ini) CrossDefModel Model definition file > geometry > crossDefFile Roughness file (roughness-*.ini) FrictionModel Model definition file > geometry > frictFile New external forcing file (*_bnd.ext) ExtModel Model definition file > external forcing > extForceFileNew Boundary conditions file (*.bc) ForcingModel New external forcing file > boundary > forcingFile 1D initial conditions field file (*.ini) OneDFieldModel Initial field file > initial > dataFile Initial field file (*.ini) IniFieldModel Model definition file > geometry > iniFieldFile Structures file (structures.ini) StructureModel Model definition file > geometry > structureFile Commonly used functions of a FileModel \u00b6 Each FileModel offers a set of commonly used functions. init () --- Initialize a new file model instance Parameters (all optional): * filepath (Path) : The file path from which the file model should be loaded. Default to None. * resolve_casing (bool) : Whether or not to resolve the file name references so that they match the case with what is on disk. Defaults to False. * recurse (bool) : Whether or not to recursively load the model. Defaults to True. * path_style (str) : Which path style is used in the loaded files. Options: 'unix', 'windows'. Defaults to the path style that matches the current operating system. save() --- Export the file model data to a file Parameters (all optional): * filepath (Path) : The file path at which this model is saved. If None is specified it defaults to the filepath currently stored in the filemodel. Defaults to None. * recurse (bool) : Whether or not to recursively save all children of this file model, or only save this model. Defaults to False. * path_style (str) : With which file path style to save the model. File references will be written with the specified path style. Options: 'unix', 'windows'. Defaults to the path style used by the current operating system. show_tree() --- Print the file model tree","title":"HYDROLIB-core guide for the Delft Software Days 2023"},{"location":"tutorials/dsd_2023/instructions/#hydrolib-core-guide-for-the-delft-software-days-2023","text":"","title":"HYDROLIB-core guide for the Delft Software Days 2023"},{"location":"tutorials/dsd_2023/instructions/#contents","text":"HYDROLIB-core guide for the Delft Software Days 2023 Contents Introduction User guide Requirements Installation Run the demo notebook Cheat sheet Kernel files vs HYDROLIB-core FileModels Commonly used functions of a FileModel","title":"Contents"},{"location":"tutorials/dsd_2023/instructions/#introduction","text":"This document contains instructions about the installation and usage of HYDROLIB-core during the Delft Software Days 2023. HYDROLIB-core is a Python package that offers functionality to process D-HYDRO input files. It offers Python-wrapped classes that represent these files and their content. HYDROLIB-core serves as the basis for various pre- and postprocessing tools for a modelling workflow of hydrodynamic simulations in D-HYDRO.","title":"Introduction"},{"location":"tutorials/dsd_2023/instructions/#user-guide","text":"","title":"User guide"},{"location":"tutorials/dsd_2023/instructions/#requirements","text":"Before getting started with HYDROLIB-core, make sure you have the following software and tools installed: Anaconda : https://www.anaconda.com/download Anaconda is an open-source distribution for Python and contains the package manager \"conda\". (!) Make sure to add Anaconda to your PATH environment variable during installation.","title":"Requirements"},{"location":"tutorials/dsd_2023/instructions/#installation","text":"Once you've installed the required software, you can create a Python 3.11 environment with HYDROLIB-core 0.5.2, the latest release. Note that the environment that we are creating now contains not only HYDROLIB-core, but also the other packages that are needed today during the breakout sessions. Follow these steps: Open your command line interface Enter the following commands: conda create --name dsd_env python=3.11 git -c conda-forge -y conda activate dsd_env pip install hydromt_delft3dfm[examples] dfm_tools pyogrio openpyxl conda deactivate After executing these commands, an Anaconda environment with the latest HYDROLIB-core is created. After deactivation, you can reactivate this environment at any time by using the following command: conda activate dsd_env If you'd like to remove the environment entirely, call the following command: conda remove -n dsd_env --all This will remove all the packages in the environment and the environment folder itself.","title":"Installation"},{"location":"tutorials/dsd_2023/instructions/#run-the-demo-notebook","text":"We'd like to be able to run the provided demo notebook. We can set it up with the following steps: Open a command line in the HYDROLIB-core folder Activate the conda environment: conda activate dsd_env And start Jupyter Notebook: jupyter notebook Open the demo.ipynb inside the demo folder","title":"Run the demo notebook"},{"location":"tutorials/dsd_2023/instructions/#cheat-sheet","text":"In HYDROLIB-core, there is a class called FileModel, which is used to represent an individual kernel file. This class has multiple derived implementations, with each one corresponding to a specific kernel file. Every FileModel, except for the root model, is referenced within another FileModel, following the same hierarchy as the kernel files themselves. The table below contains the models relevant for today's exercises.","title":"Cheat sheet"},{"location":"tutorials/dsd_2023/instructions/#kernel-files-vs-hydrolib-core-filemodels","text":"Kernel file FileModel File reference Model definition file (*.mdu) FMModel - Network file (*_net.nc) NetworkModel Model definition file > geometry > netFile Cross-section location file (crosloc.ini) CrossLocModel Model definition file > geometry > crossLocFile Cross-section definition file (crosdef.ini) CrossDefModel Model definition file > geometry > crossDefFile Roughness file (roughness-*.ini) FrictionModel Model definition file > geometry > frictFile New external forcing file (*_bnd.ext) ExtModel Model definition file > external forcing > extForceFileNew Boundary conditions file (*.bc) ForcingModel New external forcing file > boundary > forcingFile 1D initial conditions field file (*.ini) OneDFieldModel Initial field file > initial > dataFile Initial field file (*.ini) IniFieldModel Model definition file > geometry > iniFieldFile Structures file (structures.ini) StructureModel Model definition file > geometry > structureFile","title":"Kernel files vs HYDROLIB-core FileModels"},{"location":"tutorials/dsd_2023/instructions/#commonly-used-functions-of-a-filemodel","text":"Each FileModel offers a set of commonly used functions. init () --- Initialize a new file model instance Parameters (all optional): * filepath (Path) : The file path from which the file model should be loaded. Default to None. * resolve_casing (bool) : Whether or not to resolve the file name references so that they match the case with what is on disk. Defaults to False. * recurse (bool) : Whether or not to recursively load the model. Defaults to True. * path_style (str) : Which path style is used in the loaded files. Options: 'unix', 'windows'. Defaults to the path style that matches the current operating system. save() --- Export the file model data to a file Parameters (all optional): * filepath (Path) : The file path at which this model is saved. If None is specified it defaults to the filepath currently stored in the filemodel. Defaults to None. * recurse (bool) : Whether or not to recursively save all children of this file model, or only save this model. Defaults to False. * path_style (str) : With which file path style to save the model. File references will be written with the specified path style. Options: 'unix', 'windows'. Defaults to the path style used by the current operating system. show_tree() --- Print the file model tree","title":"Commonly used functions of a FileModel"},{"location":"tutorials/dsd_2023/demo/demo/","text":"(function (global, factory) { typeof exports === 'object' && typeof module !== 'undefined' ? module.exports = factory() : typeof define === 'function' && define.amd ? define(factory) : (global = global || self, global.ClipboardCopyElement = factory()); }(this, function () { 'use strict'; function createNode(text) { const node = document.createElement('pre'); node.style.width = '1px'; node.style.height = '1px'; node.style.position = 'fixed'; node.style.top = '5px'; node.textContent = text; return node; } function copyNode(node) { if ('clipboard' in navigator) { // eslint-disable-next-line flowtype/no-flow-fix-me-comments // $FlowFixMe Clipboard is not defined in Flow yet. return navigator.clipboard.writeText(node.textContent); } const selection = getSelection(); if (selection == null) { return Promise.reject(new Error()); 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These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ --jp-shadow-base-lightness: 0; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-400); --jp-border-color1: var(--md-grey-400); --jp-border-color2: var(--md-grey-300); --jp-border-color3: var(--md-grey-200); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(0, 0, 0, 1); --jp-ui-font-color1: rgba(0, 0, 0, 0.87); --jp-ui-font-color2: rgba(0, 0, 0, 0.54); --jp-ui-font-color3: rgba(0, 0, 0, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color1: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color2: rgba(255, 255, 255, 0.7); --jp-ui-inverse-font-color3: rgba(255, 255, 255, 0.5); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(0, 0, 0, 1); --jp-content-font-color1: rgba(0, 0, 0, 0.87); --jp-content-font-color2: rgba(0, 0, 0, 0.54); --jp-content-font-color3: rgba(0, 0, 0, 0.38); --jp-content-link-color: var(--md-blue-700); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: white; --jp-layout-color1: white; --jp-layout-color2: var(--md-grey-200); --jp-layout-color3: var(--md-grey-400); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: #111111; --jp-inverse-layout-color1: var(--md-grey-900); --jp-inverse-layout-color2: var(--md-grey-800); --jp-inverse-layout-color3: var(--md-grey-700); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-900); --jp-brand-color1: var(--md-blue-700); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-900); --jp-accent-color1: var(--md-green-700); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-900); --jp-warn-color1: var(--md-orange-700); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-900); --jp-error-color1: var(--md-red-700); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-900); --jp-success-color1: var(--md-green-700); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-900); --jp-info-color1: var(--md-cyan-700); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--md-grey-100); --jp-cell-editor-border-color: var(--md-grey-300); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 0.5; --jp-cell-prompt-not-active-font-color: var(--md-grey-700); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: var(--md-blue-50); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: #fdd; --jp-rendermime-table-row-background: var(--md-grey-100); --jp-rendermime-table-row-hover-background: var(--md-light-blue-50); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.25); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color1); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.24); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--md-grey-300); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color1); --jp-input-hover-background: var(--jp-layout-color1); --jp-input-background: var(--md-grey-100); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: #d9d9d9; --jp-editor-selected-focused-background: #d7d4f0; --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: #008000; --jp-mirror-editor-atom-color: #88f; --jp-mirror-editor-number-color: #080; --jp-mirror-editor-def-color: #00f; --jp-mirror-editor-variable-color: var(--md-grey-900); --jp-mirror-editor-variable-2-color: #05a; --jp-mirror-editor-variable-3-color: #085; --jp-mirror-editor-punctuation-color: #05a; --jp-mirror-editor-property-color: #05a; --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ba2121; --jp-mirror-editor-string-2-color: #708; --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: #008000; --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: #170; --jp-mirror-editor-attribute-color: #00c; --jp-mirror-editor-header-color: blue; --jp-mirror-editor-quote-color: #090; --jp-mirror-editor-link-color: #00c; --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: white; /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.5; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(245, 200, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } [data-md-color-scheme=\"slate\"] .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ /* The dark theme shadows need a bit of work, but this will probably also require work on the core layout * colors used in the theme as well. */ --jp-shadow-base-lightness: 32; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-700); --jp-border-color1: var(--md-grey-700); --jp-border-color2: var(--md-grey-800); --jp-border-color3: var(--md-grey-900); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(255, 255, 255, 1); --jp-ui-font-color1: rgba(255, 255, 255, 0.87); --jp-ui-font-color2: rgba(255, 255, 255, 0.54); --jp-ui-font-color3: rgba(255, 255, 255, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(0, 0, 0, 1); --jp-ui-inverse-font-color1: rgba(0, 0, 0, 0.8); --jp-ui-inverse-font-color2: rgba(0, 0, 0, 0.5); --jp-ui-inverse-font-color3: rgba(0, 0, 0, 0.3); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(255, 255, 255, 1); --jp-content-font-color1: rgba(255, 255, 255, 1); --jp-content-font-color2: rgba(255, 255, 255, 0.7); --jp-content-font-color3: rgba(255, 255, 255, 0.5); --jp-content-link-color: var(--md-blue-300); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: #111111; --jp-layout-color1: var(--md-grey-900); --jp-layout-color2: var(--md-grey-800); --jp-layout-color3: var(--md-grey-700); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: white; --jp-inverse-layout-color1: white; --jp-inverse-layout-color2: var(--md-grey-200); --jp-inverse-layout-color3: var(--md-grey-400); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-700); --jp-brand-color1: var(--md-blue-500); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-700); --jp-accent-color1: var(--md-green-500); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-700); --jp-warn-color1: var(--md-orange-500); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-700); --jp-error-color1: var(--md-red-500); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-700); --jp-success-color1: var(--md-green-500); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-700); --jp-info-color1: var(--md-cyan-500); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--jp-layout-color1); --jp-cell-editor-border-color: var(--md-grey-700); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 1; --jp-cell-prompt-not-active-font-color: var(--md-grey-300); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: rgba(33, 150, 243, 0.24); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: rgba(244, 67, 54, 0.28); --jp-rendermime-table-row-background: var(--md-grey-900); --jp-rendermime-table-row-hover-background: rgba(3, 169, 244, 0.2); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.6); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color2); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.8); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--jp-layout-color0); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color0); --jp-input-hover-background: var(--jp-layout-color2); --jp-input-background: var(--md-grey-800); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: var(--jp-layout-color2); --jp-editor-selected-focused-background: rgba(33, 150, 243, 0.24); --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: var(--md-green-500); --jp-mirror-editor-atom-color: var(--md-blue-300); --jp-mirror-editor-number-color: var(--md-green-400); --jp-mirror-editor-def-color: var(--md-blue-600); --jp-mirror-editor-variable-color: var(--md-grey-300); --jp-mirror-editor-variable-2-color: var(--md-blue-400); --jp-mirror-editor-variable-3-color: var(--md-green-600); --jp-mirror-editor-punctuation-color: var(--md-blue-400); --jp-mirror-editor-property-color: var(--md-blue-400); --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ff7070; --jp-mirror-editor-string-2-color: var(--md-purple-300); --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: var(--md-green-600); --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: var(--md-green-700); --jp-mirror-editor-attribute-color: var(--md-blue-700); --jp-mirror-editor-header-color: var(--md-blue-500); --jp-mirror-editor-quote-color: var(--md-green-300); --jp-mirror-editor-link-color: var(--md-blue-700); --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: var(--md-grey-400); /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.6; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(255, 225, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* scrollbar related styles. Supports every browser except Edge. */ /* colors based on JetBrain's Darcula theme */ --jp-scrollbar-background-color: #3f4244; --jp-scrollbar-thumb-color: 88, 96, 97; /* need to specify thumb color as an RGB triplet */ --jp-scrollbar-endpad: 3px; /* the minimum gap between the thumb and the ends of a scrollbar */ /* hacks for setting the thumb shape. These do nothing in Firefox */ --jp-scrollbar-thumb-margin: 3.5px; /* the space in between the sides of the thumb and the track */ --jp-scrollbar-thumb-radius: 9px; /* set to a large-ish value for rounded endcaps on the thumb */ /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } :root{--md-red-50: #ffebee;--md-red-100: #ffcdd2;--md-red-200: #ef9a9a;--md-red-300: #e57373;--md-red-400: #ef5350;--md-red-500: #f44336;--md-red-600: #e53935;--md-red-700: #d32f2f;--md-red-800: #c62828;--md-red-900: #b71c1c;--md-red-A100: #ff8a80;--md-red-A200: #ff5252;--md-red-A400: #ff1744;--md-red-A700: #d50000;--md-pink-50: #fce4ec;--md-pink-100: #f8bbd0;--md-pink-200: #f48fb1;--md-pink-300: #f06292;--md-pink-400: #ec407a;--md-pink-500: #e91e63;--md-pink-600: #d81b60;--md-pink-700: #c2185b;--md-pink-800: 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#7986cb;--md-indigo-400: #5c6bc0;--md-indigo-500: #3f51b5;--md-indigo-600: #3949ab;--md-indigo-700: #303f9f;--md-indigo-800: #283593;--md-indigo-900: #1a237e;--md-indigo-A100: #8c9eff;--md-indigo-A200: #536dfe;--md-indigo-A400: #3d5afe;--md-indigo-A700: #304ffe;--md-blue-50: #e3f2fd;--md-blue-100: #bbdefb;--md-blue-200: #90caf9;--md-blue-300: #64b5f6;--md-blue-400: #42a5f5;--md-blue-500: #2196f3;--md-blue-600: #1e88e5;--md-blue-700: #1976d2;--md-blue-800: #1565c0;--md-blue-900: #0d47a1;--md-blue-A100: #82b1ff;--md-blue-A200: #448aff;--md-blue-A400: #2979ff;--md-blue-A700: #2962ff;--md-light-blue-50: #e1f5fe;--md-light-blue-100: #b3e5fc;--md-light-blue-200: #81d4fa;--md-light-blue-300: #4fc3f7;--md-light-blue-400: #29b6f6;--md-light-blue-500: #03a9f4;--md-light-blue-600: #039be5;--md-light-blue-700: #0288d1;--md-light-blue-800: #0277bd;--md-light-blue-900: #01579b;--md-light-blue-A100: #80d8ff;--md-light-blue-A200: #40c4ff;--md-light-blue-A400: #00b0ff;--md-light-blue-A700: #0091ea;--md-cyan-50: #e0f7fa;--md-cyan-100: #b2ebf2;--md-cyan-200: #80deea;--md-cyan-300: #4dd0e1;--md-cyan-400: #26c6da;--md-cyan-500: #00bcd4;--md-cyan-600: #00acc1;--md-cyan-700: #0097a7;--md-cyan-800: #00838f;--md-cyan-900: #006064;--md-cyan-A100: #84ffff;--md-cyan-A200: #18ffff;--md-cyan-A400: #00e5ff;--md-cyan-A700: #00b8d4;--md-teal-50: #e0f2f1;--md-teal-100: #b2dfdb;--md-teal-200: #80cbc4;--md-teal-300: #4db6ac;--md-teal-400: #26a69a;--md-teal-500: #009688;--md-teal-600: #00897b;--md-teal-700: #00796b;--md-teal-800: #00695c;--md-teal-900: #004d40;--md-teal-A100: #a7ffeb;--md-teal-A200: #64ffda;--md-teal-A400: #1de9b6;--md-teal-A700: #00bfa5;--md-green-50: #e8f5e9;--md-green-100: #c8e6c9;--md-green-200: #a5d6a7;--md-green-300: #81c784;--md-green-400: #66bb6a;--md-green-500: #4caf50;--md-green-600: #43a047;--md-green-700: #388e3c;--md-green-800: #2e7d32;--md-green-900: #1b5e20;--md-green-A100: #b9f6ca;--md-green-A200: #69f0ae;--md-green-A400: #00e676;--md-green-A700: #00c853;--md-light-green-50: #f1f8e9;--md-light-green-100: #dcedc8;--md-light-green-200: #c5e1a5;--md-light-green-300: #aed581;--md-light-green-400: #9ccc65;--md-light-green-500: #8bc34a;--md-light-green-600: #7cb342;--md-light-green-700: #689f38;--md-light-green-800: #558b2f;--md-light-green-900: #33691e;--md-light-green-A100: #ccff90;--md-light-green-A200: #b2ff59;--md-light-green-A400: #76ff03;--md-light-green-A700: #64dd17;--md-lime-50: #f9fbe7;--md-lime-100: #f0f4c3;--md-lime-200: #e6ee9c;--md-lime-300: #dce775;--md-lime-400: #d4e157;--md-lime-500: #cddc39;--md-lime-600: #c0ca33;--md-lime-700: #afb42b;--md-lime-800: #9e9d24;--md-lime-900: #827717;--md-lime-A100: #f4ff81;--md-lime-A200: #eeff41;--md-lime-A400: #c6ff00;--md-lime-A700: #aeea00;--md-yellow-50: #fffde7;--md-yellow-100: #fff9c4;--md-yellow-200: #fff59d;--md-yellow-300: #fff176;--md-yellow-400: #ffee58;--md-yellow-500: #ffeb3b;--md-yellow-600: #fdd835;--md-yellow-700: #fbc02d;--md-yellow-800: #f9a825;--md-yellow-900: #f57f17;--md-yellow-A100: #ffff8d;--md-yellow-A200: #ffff00;--md-yellow-A400: #ffea00;--md-yellow-A700: #ffd600;--md-amber-50: #fff8e1;--md-amber-100: #ffecb3;--md-amber-200: #ffe082;--md-amber-300: #ffd54f;--md-amber-400: #ffca28;--md-amber-500: #ffc107;--md-amber-600: #ffb300;--md-amber-700: #ffa000;--md-amber-800: #ff8f00;--md-amber-900: #ff6f00;--md-amber-A100: #ffe57f;--md-amber-A200: #ffd740;--md-amber-A400: #ffc400;--md-amber-A700: #ffab00;--md-orange-50: #fff3e0;--md-orange-100: #ffe0b2;--md-orange-200: #ffcc80;--md-orange-300: #ffb74d;--md-orange-400: #ffa726;--md-orange-500: #ff9800;--md-orange-600: #fb8c00;--md-orange-700: #f57c00;--md-orange-800: #ef6c00;--md-orange-900: #e65100;--md-orange-A100: #ffd180;--md-orange-A200: #ffab40;--md-orange-A400: #ff9100;--md-orange-A700: #ff6d00;--md-deep-orange-50: #fbe9e7;--md-deep-orange-100: #ffccbc;--md-deep-orange-200: #ffab91;--md-deep-orange-300: #ff8a65;--md-deep-orange-400: #ff7043;--md-deep-orange-500: 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sourceMappingURL=mkdocs-jupyter.css.map*/ init_mathjax = function() { if (window.MathJax) { // MathJax loaded MathJax.Hub.Config({ TeX: { equationNumbers: { autoNumber: \"AMS\", useLabelIds: true } }, tex2jax: { inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ], displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ], processEscapes: true, processEnvironments: true }, displayAlign: 'center', CommonHTML: { linebreaks: { automatic: true } } }); MathJax.Hub.Queue([\"Typeset\", MathJax.Hub]); } } init_mathjax(); Deltares Software Days 2023: A simple hydrolib-core demo \u00b6 Hydrolib-core is a pip-installable python package. It consists of wrappers around the D-HYDRO model files. Classes in Hydrolib-core are hierarchically organized by file type, and can be accessed via hydrolib.core.io..models . File objects in Hydrolib-core reflect the same structure as the file contents. In this demo, we will load a Flow FM model, make some changes to the model and save it again. \ud83d\udca1 Tips for working in the Jupyter Notebook: Tab : Auto-complete on code Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell 0. Importing the modules and setting the path variables \u00b6 In [ ]: Copied! from hydrolib.core.dflowfm import ( FMModel , Lateral , Weir , FlowDirection ) from pathlib import Path root = Path . cwd () demo_data_folder = root / \"data\" export_folder = root / \"export\" from hydrolib.core.dflowfm import ( FMModel, Lateral, Weir, FlowDirection ) from pathlib import Path root = Path.cwd() demo_data_folder = root / \"data\" export_folder = root / \"export\" 1. Loading a Flow FM model \u00b6 In [ ]: Copied! mdu_file_path = demo_data_folder / \"FlowFM.mdu\" model = FMModel ( filepath = mdu_file_path ) print ( f \"Loaded the model from { model . filepath } \" ) mdu_file_path = demo_data_folder / \"FlowFM.mdu\" model = FMModel(filepath=mdu_file_path) print(f\"Loaded the model from {model.filepath}\") 2. Inspecting the model \u00b6 We can see the hierarchy tree of the model by calling the following function: In [ ]: Copied! model . show_tree () model.show_tree() We can also inspect sub-parts of the model, like the structures. Note that a model can have multiple structure files, but this model only has one, so we will get the first and only one. In [ ]: Copied! assert model . geometry . structurefile is not None structure_file = model . geometry . structurefile [ 0 ] # Show the list of all the structures print ( f \"Number of structures: { len ( structure_file . structure ) } \" ) print ( structure_file . structure ) assert model.geometry.structurefile is not None structure_file = model.geometry.structurefile[0] # Show the list of all the structures print(f\"Number of structures: {len(structure_file.structure)}\") print(structure_file.structure) 3. Adjusting the model \u00b6 a. Creating a new weir and adding it to the structures** \u00b6 In [ ]: Copied! # Create a new weir. weir = Weir ( id = \"DV_1471\" , branchId = \"458\" , chainage = 106.277467 , allowedFlowDir = FlowDirection . both , crestLevel = 0.400 , crestWidth = 40.000 , corrCoeff = 1.000 , useVelocityHeight = True ) # It is also possible to create objects with a dictionary. weir_data = { \"id\" : \"DV_1471\" , \"branchId\" : \"458\" , \"chainage\" : 106.277467 , \"allowedFlowDir\" : FlowDirection . both , \"crestLevel\" : 0.400 , \"crestWidth\" : 40.000 , \"corrCoeff\" : 1.000 , \"useVelocityHeight\" : True } weir = Weir ( ** weir_data ) # Add the weir to the model structure_file . structure . append ( weir ) print ( f \"Number of structures: { len ( structure_file . structure ) } \" ) # Create a new weir. weir = Weir( id=\"DV_1471\", branchId=\"458\", chainage=106.277467, allowedFlowDir=FlowDirection.both, crestLevel=0.400, crestWidth=40.000, corrCoeff=1.000, useVelocityHeight=True ) # It is also possible to create objects with a dictionary. weir_data = { \"id\": \"DV_1471\", \"branchId\": \"458\", \"chainage\": 106.277467, \"allowedFlowDir\": FlowDirection.both, \"crestLevel\": 0.400, \"crestWidth\": 40.000, \"corrCoeff\": 1.000, \"useVelocityHeight\": True } weir = Weir(**weir_data) # Add the weir to the model structure_file.structure.append(weir) print(f\"Number of structures: {len(structure_file.structure)}\") b. Adjusting some parameters of the model \u00b6 In [ ]: Copied! model . physics . backgroundsalinity = 30 # [ppt] model . physics . backgroundwatertemperature = 6 # [\u00b0C] model . time . dtuser = 900 # [s] model.physics.backgroundsalinity = 30 # [ppt] model.physics.backgroundwatertemperature = 6 # [\u00b0C] model.time.dtuser = 900 # [s] Hydrolib-core offers instant validation of objects that are created, either by loading them from file or by manually creating them. This makes it easier for users to create valid models. A lateral, like many other objects, should have a valid location specification, specified by: A node id, A branch id with a chainage, or Coordinates Let's create an invalid Lateral. We \"forget\" to specify a chainage. In [ ]: Copied! try : lateral = Lateral ( id = \"lateral_1\" , name = \"lateral_1\" , branchid = \"branch_a\" , discharge = \"realtime\" ) except ValueError as error : print ( error ) try: lateral = Lateral( id=\"lateral_1\", name=\"lateral_1\", branchid=\"branch_a\", discharge=\"realtime\" ) except ValueError as error: print(error) Now let's create a valid lateral. In [ ]: Copied! lateral = Lateral ( id = \"lateral_1\" , name = \"lateral_1\" , branchid = \"branch_a\" , chainage = 100 , discharge = \"realtime\" ) print ( \"Lateral with branch id and chainage is correct!\" ) lateral = Lateral( id=\"lateral_1\", name=\"lateral_1\", branchid=\"branch_a\", chainage=100, discharge=\"realtime\" ) print(\"Lateral with branch id and chainage is correct!\") 5. Saving the model \u00b6 If we save the model now, it will overwrite the current model files. So let's save it in a different location. In [ ]: Copied! print ( f \"The original model is located at { model . filepath } \" ) save_mdu_file_path = export_folder / \"save_model\" / \"FlowFM.mdu\" model . filepath = save_mdu_file_path # Set recurse to True. If it is False, only the MDU file will be saved. model . save ( recurse = True ) print ( f \"The saved model is located at { model . filepath } \" ) print(f\"The original model is located at {model.filepath}\") save_mdu_file_path = export_folder / \"save_model\" / \"FlowFM.mdu\" model.filepath = save_mdu_file_path # Set recurse to True. If it is False, only the MDU file will be saved. model.save(recurse=True) print(f\"The saved model is located at {model.filepath}\") 6. Saving only a sub-part of the model \u00b6 It is also possible to save individual child model files, such as the cross section definition file. In [ ]: Copied! crossdef_file = model . geometry . crossdeffile assert crossdef_file is not None crossdef_file . filepath = export_folder / \"save_crossdef\" / \"crsdef.ini\" crossdef_file . save () print ( f \"The saved cross section definition model is located at { crossdef_file . filepath } \" ) crossdef_file = model.geometry.crossdeffile assert crossdef_file is not None crossdef_file.filepath = export_folder / \"save_crossdef\" / \"crsdef.ini\" crossdef_file.save() print(f\"The saved cross section definition model is located at {crossdef_file.filepath}\")","title":"Deltares Software Days 2023: A simple hydrolib-core demo"},{"location":"tutorials/dsd_2023/demo/demo/#deltares-software-days-2023-a-simple-hydrolib-core-demo","text":"Hydrolib-core is a pip-installable python package. It consists of wrappers around the D-HYDRO model files. Classes in Hydrolib-core are hierarchically organized by file type, and can be accessed via hydrolib.core.io..models . File objects in Hydrolib-core reflect the same structure as the file contents. In this demo, we will load a Flow FM model, make some changes to the model and save it again. \ud83d\udca1 Tips for working in the Jupyter Notebook: Tab : Auto-complete on code Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell","title":"Deltares Software Days 2023: A simple hydrolib-core demo"},{"location":"tutorials/dsd_2023/demo/demo/#0-importing-the-modules-and-setting-the-path-variables","text":"In [ ]: Copied! from hydrolib.core.dflowfm import ( FMModel , Lateral , Weir , FlowDirection ) from pathlib import Path root = Path . cwd () demo_data_folder = root / \"data\" export_folder = root / \"export\" from hydrolib.core.dflowfm import ( FMModel, Lateral, Weir, FlowDirection ) from pathlib import Path root = Path.cwd() demo_data_folder = root / \"data\" export_folder = root / \"export\"","title":"0. Importing the modules and setting the path variables"},{"location":"tutorials/dsd_2023/demo/demo/#1-loading-a-flow-fm-model","text":"In [ ]: Copied! mdu_file_path = demo_data_folder / \"FlowFM.mdu\" model = FMModel ( filepath = mdu_file_path ) print ( f \"Loaded the model from { model . filepath } \" ) mdu_file_path = demo_data_folder / \"FlowFM.mdu\" model = FMModel(filepath=mdu_file_path) print(f\"Loaded the model from {model.filepath}\")","title":"1. Loading a Flow FM model"},{"location":"tutorials/dsd_2023/demo/demo/#2-inspecting-the-model","text":"We can see the hierarchy tree of the model by calling the following function: In [ ]: Copied! model . show_tree () model.show_tree() We can also inspect sub-parts of the model, like the structures. Note that a model can have multiple structure files, but this model only has one, so we will get the first and only one. In [ ]: Copied! assert model . geometry . structurefile is not None structure_file = model . geometry . structurefile [ 0 ] # Show the list of all the structures print ( f \"Number of structures: { len ( structure_file . structure ) } \" ) print ( structure_file . structure ) assert model.geometry.structurefile is not None structure_file = model.geometry.structurefile[0] # Show the list of all the structures print(f\"Number of structures: {len(structure_file.structure)}\") print(structure_file.structure)","title":"2. Inspecting the model"},{"location":"tutorials/dsd_2023/demo/demo/#3-adjusting-the-model","text":"","title":"3. Adjusting the model"},{"location":"tutorials/dsd_2023/demo/demo/#a-creating-a-new-weir-and-adding-it-to-the-structures","text":"In [ ]: Copied! # Create a new weir. weir = Weir ( id = \"DV_1471\" , branchId = \"458\" , chainage = 106.277467 , allowedFlowDir = FlowDirection . both , crestLevel = 0.400 , crestWidth = 40.000 , corrCoeff = 1.000 , useVelocityHeight = True ) # It is also possible to create objects with a dictionary. weir_data = { \"id\" : \"DV_1471\" , \"branchId\" : \"458\" , \"chainage\" : 106.277467 , \"allowedFlowDir\" : FlowDirection . both , \"crestLevel\" : 0.400 , \"crestWidth\" : 40.000 , \"corrCoeff\" : 1.000 , \"useVelocityHeight\" : True } weir = Weir ( ** weir_data ) # Add the weir to the model structure_file . structure . append ( weir ) print ( f \"Number of structures: { len ( structure_file . structure ) } \" ) # Create a new weir. weir = Weir( id=\"DV_1471\", branchId=\"458\", chainage=106.277467, allowedFlowDir=FlowDirection.both, crestLevel=0.400, crestWidth=40.000, corrCoeff=1.000, useVelocityHeight=True ) # It is also possible to create objects with a dictionary. weir_data = { \"id\": \"DV_1471\", \"branchId\": \"458\", \"chainage\": 106.277467, \"allowedFlowDir\": FlowDirection.both, \"crestLevel\": 0.400, \"crestWidth\": 40.000, \"corrCoeff\": 1.000, \"useVelocityHeight\": True } weir = Weir(**weir_data) # Add the weir to the model structure_file.structure.append(weir) print(f\"Number of structures: {len(structure_file.structure)}\")","title":"a. Creating a new weir and adding it to the structures**"},{"location":"tutorials/dsd_2023/demo/demo/#b-adjusting-some-parameters-of-the-model","text":"In [ ]: Copied! model . physics . backgroundsalinity = 30 # [ppt] model . physics . backgroundwatertemperature = 6 # [\u00b0C] model . time . dtuser = 900 # [s] model.physics.backgroundsalinity = 30 # [ppt] model.physics.backgroundwatertemperature = 6 # [\u00b0C] model.time.dtuser = 900 # [s] Hydrolib-core offers instant validation of objects that are created, either by loading them from file or by manually creating them. This makes it easier for users to create valid models. A lateral, like many other objects, should have a valid location specification, specified by: A node id, A branch id with a chainage, or Coordinates Let's create an invalid Lateral. We \"forget\" to specify a chainage. In [ ]: Copied! try : lateral = Lateral ( id = \"lateral_1\" , name = \"lateral_1\" , branchid = \"branch_a\" , discharge = \"realtime\" ) except ValueError as error : print ( error ) try: lateral = Lateral( id=\"lateral_1\", name=\"lateral_1\", branchid=\"branch_a\", discharge=\"realtime\" ) except ValueError as error: print(error) Now let's create a valid lateral. In [ ]: Copied! lateral = Lateral ( id = \"lateral_1\" , name = \"lateral_1\" , branchid = \"branch_a\" , chainage = 100 , discharge = \"realtime\" ) print ( \"Lateral with branch id and chainage is correct!\" ) lateral = Lateral( id=\"lateral_1\", name=\"lateral_1\", branchid=\"branch_a\", chainage=100, discharge=\"realtime\" ) print(\"Lateral with branch id and chainage is correct!\")","title":"b. Adjusting some parameters of the model"},{"location":"tutorials/dsd_2023/demo/demo/#5-saving-the-model","text":"If we save the model now, it will overwrite the current model files. So let's save it in a different location. In [ ]: Copied! print ( f \"The original model is located at { model . filepath } \" ) save_mdu_file_path = export_folder / \"save_model\" / \"FlowFM.mdu\" model . filepath = save_mdu_file_path # Set recurse to True. If it is False, only the MDU file will be saved. model . save ( recurse = True ) print ( f \"The saved model is located at { model . filepath } \" ) print(f\"The original model is located at {model.filepath}\") save_mdu_file_path = export_folder / \"save_model\" / \"FlowFM.mdu\" model.filepath = save_mdu_file_path # Set recurse to True. If it is False, only the MDU file will be saved. model.save(recurse=True) print(f\"The saved model is located at {model.filepath}\")","title":"5. Saving the model"},{"location":"tutorials/dsd_2023/demo/demo/#6-saving-only-a-sub-part-of-the-model","text":"It is also possible to save individual child model files, such as the cross section definition file. In [ ]: Copied! crossdef_file = model . geometry . crossdeffile assert crossdef_file is not None crossdef_file . filepath = export_folder / \"save_crossdef\" / \"crsdef.ini\" crossdef_file . save () print ( f \"The saved cross section definition model is located at { crossdef_file . filepath } \" ) crossdef_file = model.geometry.crossdeffile assert crossdef_file is not None crossdef_file.filepath = export_folder / \"save_crossdef\" / \"crsdef.ini\" crossdef_file.save() print(f\"The saved cross section definition model is located at {crossdef_file.filepath}\")","title":"6. 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When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(0, 0, 0, 1); --jp-content-font-color1: rgba(0, 0, 0, 0.87); --jp-content-font-color2: rgba(0, 0, 0, 0.54); --jp-content-font-color3: rgba(0, 0, 0, 0.38); --jp-content-link-color: var(--md-blue-700); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: white; --jp-layout-color1: white; --jp-layout-color2: var(--md-grey-200); --jp-layout-color3: var(--md-grey-400); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: #111111; --jp-inverse-layout-color1: var(--md-grey-900); --jp-inverse-layout-color2: var(--md-grey-800); --jp-inverse-layout-color3: var(--md-grey-700); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-900); --jp-brand-color1: var(--md-blue-700); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-900); --jp-accent-color1: var(--md-green-700); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-900); --jp-warn-color1: var(--md-orange-700); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-900); --jp-error-color1: var(--md-red-700); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-900); --jp-success-color1: var(--md-green-700); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-900); --jp-info-color1: var(--md-cyan-700); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--md-grey-100); --jp-cell-editor-border-color: var(--md-grey-300); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 0.5; --jp-cell-prompt-not-active-font-color: var(--md-grey-700); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: var(--md-blue-50); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: #fdd; --jp-rendermime-table-row-background: var(--md-grey-100); --jp-rendermime-table-row-hover-background: var(--md-light-blue-50); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.25); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color1); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.24); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--md-grey-300); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color1); --jp-input-hover-background: var(--jp-layout-color1); --jp-input-background: var(--md-grey-100); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: #d9d9d9; --jp-editor-selected-focused-background: #d7d4f0; --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: #008000; --jp-mirror-editor-atom-color: #88f; --jp-mirror-editor-number-color: #080; --jp-mirror-editor-def-color: #00f; --jp-mirror-editor-variable-color: var(--md-grey-900); --jp-mirror-editor-variable-2-color: #05a; --jp-mirror-editor-variable-3-color: #085; --jp-mirror-editor-punctuation-color: #05a; --jp-mirror-editor-property-color: #05a; --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ba2121; --jp-mirror-editor-string-2-color: #708; --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: #008000; --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: #170; --jp-mirror-editor-attribute-color: #00c; --jp-mirror-editor-header-color: blue; --jp-mirror-editor-quote-color: #090; --jp-mirror-editor-link-color: #00c; --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: white; /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.5; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(245, 200, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } [data-md-color-scheme=\"slate\"] .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ /* The dark theme shadows need a bit of work, but this will probably also require work on the core layout * colors used in the theme as well. */ --jp-shadow-base-lightness: 32; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-700); --jp-border-color1: var(--md-grey-700); --jp-border-color2: var(--md-grey-800); --jp-border-color3: var(--md-grey-900); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(255, 255, 255, 1); --jp-ui-font-color1: rgba(255, 255, 255, 0.87); --jp-ui-font-color2: rgba(255, 255, 255, 0.54); --jp-ui-font-color3: rgba(255, 255, 255, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(0, 0, 0, 1); --jp-ui-inverse-font-color1: rgba(0, 0, 0, 0.8); --jp-ui-inverse-font-color2: rgba(0, 0, 0, 0.5); --jp-ui-inverse-font-color3: rgba(0, 0, 0, 0.3); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(255, 255, 255, 1); --jp-content-font-color1: rgba(255, 255, 255, 1); --jp-content-font-color2: rgba(255, 255, 255, 0.7); --jp-content-font-color3: rgba(255, 255, 255, 0.5); --jp-content-link-color: var(--md-blue-300); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: #111111; --jp-layout-color1: var(--md-grey-900); --jp-layout-color2: var(--md-grey-800); --jp-layout-color3: var(--md-grey-700); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: white; --jp-inverse-layout-color1: white; --jp-inverse-layout-color2: var(--md-grey-200); --jp-inverse-layout-color3: var(--md-grey-400); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-700); --jp-brand-color1: var(--md-blue-500); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-700); --jp-accent-color1: var(--md-green-500); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-700); --jp-warn-color1: var(--md-orange-500); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-700); --jp-error-color1: var(--md-red-500); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-700); --jp-success-color1: var(--md-green-500); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-700); --jp-info-color1: var(--md-cyan-500); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--jp-layout-color1); --jp-cell-editor-border-color: var(--md-grey-700); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 1; --jp-cell-prompt-not-active-font-color: var(--md-grey-300); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: rgba(33, 150, 243, 0.24); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: rgba(244, 67, 54, 0.28); --jp-rendermime-table-row-background: var(--md-grey-900); --jp-rendermime-table-row-hover-background: rgba(3, 169, 244, 0.2); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.6); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color2); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.8); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--jp-layout-color0); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color0); --jp-input-hover-background: var(--jp-layout-color2); --jp-input-background: var(--md-grey-800); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: var(--jp-layout-color2); --jp-editor-selected-focused-background: rgba(33, 150, 243, 0.24); --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: var(--md-green-500); --jp-mirror-editor-atom-color: var(--md-blue-300); --jp-mirror-editor-number-color: var(--md-green-400); --jp-mirror-editor-def-color: var(--md-blue-600); --jp-mirror-editor-variable-color: var(--md-grey-300); --jp-mirror-editor-variable-2-color: var(--md-blue-400); --jp-mirror-editor-variable-3-color: var(--md-green-600); --jp-mirror-editor-punctuation-color: var(--md-blue-400); --jp-mirror-editor-property-color: var(--md-blue-400); --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ff7070; --jp-mirror-editor-string-2-color: var(--md-purple-300); --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: var(--md-green-600); --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: var(--md-green-700); --jp-mirror-editor-attribute-color: var(--md-blue-700); --jp-mirror-editor-header-color: var(--md-blue-500); --jp-mirror-editor-quote-color: var(--md-green-300); --jp-mirror-editor-link-color: var(--md-blue-700); --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: var(--md-grey-400); /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.6; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(255, 225, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* scrollbar related styles. Supports every browser except Edge. */ /* colors based on JetBrain's Darcula theme */ --jp-scrollbar-background-color: #3f4244; --jp-scrollbar-thumb-color: 88, 96, 97; /* need to specify thumb color as an RGB triplet */ --jp-scrollbar-endpad: 3px; /* the minimum gap between the thumb and the ends of a scrollbar */ /* hacks for setting the thumb shape. 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sourceMappingURL=mkdocs-jupyter.css.map*/ init_mathjax = function() { if (window.MathJax) { // MathJax loaded MathJax.Hub.Config({ TeX: { equationNumbers: { autoNumber: \"AMS\", useLabelIds: true } }, tex2jax: { inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ], displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ], processEscapes: true, processEnvironments: true }, displayAlign: 'center', CommonHTML: { linebreaks: { automatic: true } } }); MathJax.Hub.Queue([\"Typeset\", MathJax.Hub]); } } init_mathjax(); Creating a Delft3D FM 1D2D fluvial flood model of Magdalena river \u00b6 The exercises in this notebook will serve as introduction on how to use HYDROLIB-core functionalities. We will create and adjust a Delft3D FM Suite 1D2D fluvial flood model of the Magdalena river in Columbia. First a 1D river model of the Magdalena river and Canal del Dique will be created, shown in the left figure. This model will be extended with a 2D Flexible Mesh, with a uniform roughness field. Adding a Digital Terrain Model (DTM) on that 2D mesh is currently not part of this tutorial, but in practice this is indispensible to mimic the fluvial flood patterns. Note that the model that will be created is for educational purposes and consists partially of fictive or unvalidated model data. Using HYDROLIB-core to build models \u00b6 HYDROLIB-core is a Python package that offers functionality to process D-HYDRO input files. It offers Python-wrapped classes that represent these files and their content. HYDROLIB-core serves as the basis for various pre- and postprocessing tools for a modelling workflow of hydrodynamic simulations in D-HYDRO. It can easily be used to build models and export the model files that can aftewards be run by dflowfm or other supported D-HYDRO kernels. Content of the tutorial \u00b6 The goal of this tutorial is to familiarize modelers with applying HYDROLIB-core functionalities in their modelling procedures for building new models or adjusting existing models. As mentioned above, you will create an 1D2D fluvial flood model from scratch using the D-Flow FM HYDROLIB-core functionalities and the underlying functions from mesh generation ( MeshKernelPy ). We will walk through the following steps to build the model: Selecting the data location Creating an empty D-Flow FM model Reading the branch data from a shape file Creating and assigning a 1D computational grid to the model Adding cross-sections to the branches Adding cross-section definitions Adding roughness to the model Adding boundary conditions to the model Adding initial water depths Adding a weir to a branch Finishing up and saving the model Creating a 2D flexible mesh Refining the 2D grid locally Saving the 1D2D model \ud83d\udca1 Tips for working in the Jupyter Notebook \u00b6 Tab : Auto-complete on code Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell Import the needed modules \u00b6 Several Python packages are required to run the notebook. These packages are imported below. Please consult the HYDROLIB-core documentation if you want to use additional HYDROLIB-core functionalities later. In [ ]: Copied! # General import geopandas as gpd import matplotlib.pyplot as plt import numpy as np import pandas as pd from pathlib import Path # MeshKernel import meshkernel as mk from meshkernel import GeometryList , MakeGridParameters # HYDROLIB-core from hydrolib.core.dflowfm.mdu import FMModel , AutoStartOption from hydrolib.core.dflowfm.net.models import * from hydrolib.core.dflowfm.crosssection.models import CrossLocModel , CrossDefModel , YZCrsDef from hydrolib.core.dflowfm.friction.models import * from hydrolib.core.dflowfm.bc.models import * from hydrolib.core.dflowfm.ext.models import * from hydrolib.core.dflowfm.inifield.models import * from hydrolib.core.dflowfm.onedfield.models import * from hydrolib.core.dflowfm.structure.models import Weir , FlowDirection , StructureModel print ( \"Imports were successful!\" ) # General import geopandas as gpd import matplotlib.pyplot as plt import numpy as np import pandas as pd from pathlib import Path # MeshKernel import meshkernel as mk from meshkernel import GeometryList, MakeGridParameters # HYDROLIB-core from hydrolib.core.dflowfm.mdu import FMModel, AutoStartOption from hydrolib.core.dflowfm.net.models import * from hydrolib.core.dflowfm.crosssection.models import CrossLocModel, CrossDefModel, YZCrsDef from hydrolib.core.dflowfm.friction.models import * from hydrolib.core.dflowfm.bc.models import * from hydrolib.core.dflowfm.ext.models import * from hydrolib.core.dflowfm.inifield.models import * from hydrolib.core.dflowfm.onedfield.models import * from hydrolib.core.dflowfm.structure.models import Weir, FlowDirection, StructureModel print(\"Imports were successful!\") Here starts the tutorial \u00b6 1. Selecting the data location \u00b6 Exercise \ud83e\udde9: Create a variable that contains the Path to the data folder. In [ ]: Copied! data_dir = ... print ( f \"Data location: { data_dir } \" ) data_dir = ... print(f\"Data location: {data_dir}\") 2. Creating an empty D-Flow FM model \u00b6 To start a model from scratch, you first need to create an empty model without data. In this tutorial we will create a D-Flow FM model. The MDU file (master definition file) is the main input file of the D-Flow FM model. A new D-Flow FM model is constructed with the FMModel initializer. Exercise \ud83e\udde9 Create a variable containing a new FMModel object. Create a variable containing the export directory Export the D-Flow FM model to an MDU file inside the export directory API references: FMModel FileModel.filepath FileModel.save() In [ ]: Copied! model = ... export_dir = ... model . filepath = ... # Save the MDU file ... print ( f \"MDU file saved: { model . filepath } \" ) model = ... export_dir = ... model.filepath = ... # Save the MDU file ... print(f\"MDU file saved: {model.filepath}\") Part 1: Setting up a 1D Delft3D FM model \u00b6 In this part we will build up the complete 1D model schematization step by step. At the end you should have a complete set of model input files for a 1D calculation. 3. Reading the branch data from a shape file \u00b6 The model will include the lower part of the Magadalena from Cordoba Teton to the river mouth Baranquilla and the Canal del Dique. Exercise \ud83e\udde9 Read the branch data from the branches_Branches.shp file Print the branch data, such that we can answer the following questions: How many river branches does the model have? What are their names? Which friction type and friction value is used for each branch? API references: gpd.read_file In [ ]: Copied! # Read the branches ... # Print the data ... # Answers: # * ... # * ... # * ... # Read the branches ... # Print the data ... # Answers: # * ... # * ... # * ... 4. Creating and assigning a 1D computational grid to the model \u00b6 In the previous step we read the geometry and attributes of the branches from the shape file. This branch data will become the network input for our D-Flow FM model. Since the model does not have a network yet, we need to create a new network object and assign it to the model. A network may contain a 1D network, a 2D mesh and 1D2D links. Exercise \ud83e\udde9 Create a new network Assign the network to the model and assign a (relative) file path for the net file The new network should contain the data that we read from the shape file: Three Branch objects will need to be added to the network. For each branch, the name, geometry and computational grid points should be provided. The computational points are not included in the data, we will need to generate those with a grid point distance as specified: Branch name dx [m] Channel_1D_1_A 1000 Channel_1D_1_B 1000 Channel_1D_1 500 Hint \ud83d\udca1: The MDU file contains a [Geometry] section which has the network file reference, e.g.: [Geometry] netFile = FlowFM_net.nc ... API references: Network NetworkModel Branch Branch.generate_nodes() Network.mesh1d_add_branch() (undocumented): Adds a branch to the 1D network. The function needs two arguments: Branch : the branch to be added str : The name of the branch that is added In [ ]: Copied! # Assign a new network to the D-Flow FM model and specify the file path network = ... # Specify 1D computational grid point distance per branch dx_per_branch = { \"Channel_1D_1_A\" : 1000 , \"Channel_1D_1_B\" : 1000 , \"Channel_1D_1\" : 500 , } # Assign geometry of the branches and generate the computational grid on top of the branches. # Add each branch to the network for index , branch_data in branches_gdf . iterrows (): branch_geometry = np . transpose ( branch_data . geometry . xy ) ... network . _mesh1d . _set_mesh1d () # Assign a new network to the D-Flow FM model and specify the file path network = ... # Specify 1D computational grid point distance per branch dx_per_branch = { \"Channel_1D_1_A\" : 1000, \"Channel_1D_1_B\" : 1000, \"Channel_1D_1\" : 500, } # Assign geometry of the branches and generate the computational grid on top of the branches. # Add each branch to the network for index, branch_data in branches_gdf.iterrows(): branch_geometry = np.transpose(branch_data.geometry.xy) ... network._mesh1d._set_mesh1d() We can plot the branches onto a background: In [ ]: Copied! # Create a figure with the 1D network figure , axis = plt . subplots ( ncols = 1 ) img = plt . imread ( data_dir / \"osm_background.png\" ) # Add branch names to the plot for branch_name , branch in network . _mesh1d . branches . items (): middle = int (( len ( branch . geometry ) - 1 ) / 2 ) xy = branch . geometry [ middle ] axis . text ( xy [ 0 ], xy [ 1 ], branch_name , ha = 'center' ) axis . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) network . _mesh1d . _get_mesh1d () . plot_edges ( ax = axis , color = 'blue' ) # Create a figure with the 1D network figure, axis = plt.subplots(ncols=1) img = plt.imread(data_dir / \"osm_background.png\") # Add branch names to the plot for branch_name, branch in network._mesh1d.branches.items(): middle = int((len(branch.geometry) - 1)/2) xy = branch.geometry[middle] axis.text(xy[0], xy[1], branch_name, ha='center') axis.imshow(img, extent=[440000, 531544.97964175534434617, 1057000, 1228644.01383191486820579]) network._mesh1d._get_mesh1d().plot_edges(ax=axis, color='blue') 5. Adding cross-sections to the branches \u00b6 In order to determine the flow area of the 1D model during the computation, you need cross-sections. These cross-sections are defined by two components: Cross-section locations Cross-section definitions The cross-section locations and cross-section definitions are exported to their own file. A cross-section location is defined by the following information: The cross-section ID A location, specified by a branch ID and a chainage. A shift, the vertical shift of the cross section profile. This is mainly used to create a good longitudinal slope over the 1D model (in case of shared cross-sections). A reference to the cross-section definition that is used at this location.

    A cross-section definition is defined by the following information: The cross-section definition ID The cross-section type: circle, rectangle, ZW river, ZW, YZ, XYZ Depending on the type of cross-section, a set of properties describing the properties of the profile shape

    In our data folder, there is a CSV file containing the cross-section locations. We want to convert this data to HYDROLIB-core cross-section location objects and add them to the D-Flow FM model. The columns in the CSV correspond exactly with the field names of a CrossSection class, making the conversion easy. Exercise \ud83e\udde9 Read the data from the CSV file Print the cross-section location data, to answer the following questions: How many cross-section does the model contain in total, and how many does each branch have? Do the cross-section have shared cross-section definitions? A shared cross-section definition is a definition used by more than one cross-section. Convert the CSV data (a pd.DataFrame) into HYDROLIB-core CrossSection objects Assign the cross section locations to the model Hint \ud83d\udca1: The MDU file contains a [Geometry] section which has the crossDefFile and crossLocFile reference, e.g.: [Geometry] crossDefFile = crsdef.ini crossLocFile = crsloc.ini ... API references: pd.read_csv() pd.to_dict() CrossLocModel CrossSection In [ ]: Copied! # Read the cross-sections from the CSV cross_section_data_file = ... cross_section_df = ... # Print the data ... # Answers: # * ... # * ... # Assign the data to the model ... # Read the cross-sections from the CSV cross_section_data_file = ... cross_section_df = ... # Print the data ... # Answers: # * ... # * ... # Assign the data to the model ... 6. Adding cross-section definitions \u00b6 In the following exercise we will add the cross-section definitions to the D-Flow FM model. These belong to the cross-sections we added in the previous step. These cross-sections all have YZ-profiles in order to define a natural shape of the river. Please finish the code below. Exercise \ud83e\udde9 Create a new cross-section definition model with the defined properties Create an YZ profile for each profile from the excel file Append each YZ profile to the cross-section definition model Make sure the data is assigned to the D-Flow FM model API references: CrossDefModel YZCrsDef In [ ]: Copied! profiles_file = data_dir / '1D_YZ_CrossSections.xlsx' profile_excel_data = pd . read_excel ( profiles_file , sheet_name = None ) profile_names = list ( profile_excel_data ) print ( f \"Profile names: { profile_names } \" ) # Create a new cross-section definition model and assign to the model ... # Properties for each YZ profile type_crs = 'yz' thalweg = 0.0 single_valued_z = 'yes' conveyance = 'segmented' sectionCount = 1 friction_ids = 'channels' # Create the YZ profiles and append them to the CrossDefModel for profile_name in profile_names : profile_data = profile_excel_data [ profile_name ] num_coords = len ( profile_data . values ) y_coords = profile_data . y . to_list () z_coords = profile_data . z . to_list () # Define friction positions at begin and end of profile friction_positions = [ profile_data . y [ 0 ], profile_data . y [ num_coords - 1 ]] # Create an YZ profile and add it to the cross-section definition model ... profiles_file = data_dir / '1D_YZ_CrossSections.xlsx' profile_excel_data = pd.read_excel(profiles_file, sheet_name=None) profile_names = list(profile_excel_data) print(f\"Profile names: {profile_names}\") # Create a new cross-section definition model and assign to the model ... # Properties for each YZ profile type_crs = 'yz' thalweg = 0.0 single_valued_z = 'yes' conveyance = 'segmented' sectionCount = 1 friction_ids = 'channels' # Create the YZ profiles and append them to the CrossDefModel for profile_name in profile_names: profile_data = profile_excel_data[profile_name] num_coords = len(profile_data.values) y_coords = profile_data.y.to_list() z_coords = profile_data.z.to_list() # Define friction positions at begin and end of profile friction_positions = [profile_data.y[0], profile_data.y[num_coords-1]] # Create an YZ profile and add it to the cross-section definition model ... 7. Adding roughness to the model \u00b6 Our 1D D-Flow FM model now has a network topology, computational grid points and cross-sections. Friction is a component that should be added to the model to get the proper bed roughness and channel conveyance. For each branch, we will add a friction type and value at the upstream location. We will also specify a global roughness section. This will be used when there is no friction defined for a branch. It also contains a friction ID. In the cross-section definitions we created above, a reference is made to this friction ID (='channels'). YZ profiles can refer to multiple friction IDs, since the friction can vary within the cross-section. This also means that multiple friction definition files can be added to one D-Flow FM model. In [ ]: Copied! channel_friction_id = 'channels' channel_global_type = FrictionType . manning channel_global_value = 0.023 channel_friction_model = FrictionModel () channel_friction_model . filepath = \"roughness-channels.ini\" # It is conventional to specify the file names as \"roughness-[friction ID].ini\" model . geometry . frictfile = [ channel_friction_model ] # Create global friction model and add it to frictionmodel channel_global_friction = FrictGlobal ( frictionId = channel_friction_id , frictionType = channel_global_type , frictionValue = channel_global_value ) channel_friction_model . global_ = channel_global_friction function_type = 'constant' # Create friction definition per branch for index , branch_data in branches_gdf . iterrows (): friction_per_branch = FrictBranch ( branchId = branch_data . Name , frictionType = branch_data . fric_type , frictionValues = [ branch_data . fric_value ], chainage = [ branch_data . chainage ], numLocations = 1 , functionType = function_type ) channel_friction_model . branch . append ( friction_per_branch ) channel_friction_id = 'channels' channel_global_type = FrictionType.manning channel_global_value = 0.023 channel_friction_model = FrictionModel() channel_friction_model.filepath = \"roughness-channels.ini\" # It is conventional to specify the file names as \"roughness-[friction ID].ini\" model.geometry.frictfile = [channel_friction_model] # Create global friction model and add it to frictionmodel channel_global_friction = FrictGlobal(frictionId=channel_friction_id, frictionType=channel_global_type, frictionValue=channel_global_value) channel_friction_model.global_ = channel_global_friction function_type = 'constant' # Create friction definition per branch for index, branch_data in branches_gdf.iterrows(): friction_per_branch = FrictBranch(branchId=branch_data.Name, frictionType=branch_data.fric_type, frictionValues=[branch_data.fric_value], chainage=[branch_data.chainage], numLocations=1, functionType=function_type) channel_friction_model.branch.append(friction_per_branch) We want to define another global friction definition for the Canal del Dique. This friction model assumes Chezy as global friction type and a friction value of 45.0. You can use the code above as an example. Exercise \ud83e\udde9 Create a new friction model for Canal del Dique Specify a global friction definition Make sure the new friction model is added to the D-Flow FM model API references: FrictionType FrictionModel FrictGlobal In [ ]: Copied! ... ... The cross-sections on the Canal del Dique (Channel_1D_1) do not refer to this new friction ID yet. Exercise \ud83e\udde9 Use the cross-section locations and definitions in the D-Flow FM model to find the cross-sections on the Channel_1D_1 branch Reassign the friction ID of the correct cross sections to the one used for the Canal del Dique In [ ]: Copied! ... ... 8. Adding boundary conditions to the model \u00b6 Fluvial floods occur when water levels in the river are too high. These high water levels in the rivers can result from several factors. One of those is the occurence of heavy rainfall in the upstream catchment. These heavy rainstorms can lead to a high discharge wave entering the upstream boundary of the river. In order to apply boundary conditions on a model you need data from two files: External forcing file (*.ext) : specifies the location and type of forcing. Boundary conditions file (*.bc) : contains the forcing values, e.g. a time series or a constant value In this tutorial you will model such a high discharge wave (time series) at the upstream 1D boundary. For the two downstream boundaries a constant water level of 0 m AD is assumed. Note that this are tidal boundaries in reality. Exercise \ud83e\udde9 Complete the code below by adding the boundary locations to the external forcing model. For each boundary location (3), the correct boundary object should be created with a quantity, node ID and forcing file. The quantity keys for discharge and water level are 'dischargebnd' and 'waterlevelbnd', respectively. API references: Boundary In [ ]: Copied! ext_model = ExtModel () # External forcing file (.ext) bc_model = ForcingModel () # Boundary conditions file (.bc) model . external_forcing . extforcefilenew = ext_model # Read the upstream boundary time series from excel discharge_file = data_dir / '1D_BoundaryConditions.xlsx' discharge_excel_df = pd . read_excel ( discharge_file , sheet_name = [ 0 ]) node_ids = model . geometry . netfile . network . _mesh1d . network1d_node_id print ( node_ids ) node_upstream = node_ids [ 0 ] # time series discharge node nodes_downstream = node_ids [ 2 :] # constant water level nodes # Create the discharge timeseries bc_upstream = TimeSeries ( name = node_upstream , nodeid = node_upstream , timeinterpolation = TimeInterpolation . linear , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2012-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], datablock = [[ time , dis ] for [ time , dis ] in discharge_excel_df [ 0 ] . values ]) bc_model . forcing . append ( bc_upstream ) # Create the constant water level for node_downstream in nodes_downstream : bc_downstream = Constant ( name = node_downstream , nodeid = node_downstream , quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], datablock = [[ \"0.0\" ]]) bc_model . forcing . append ( bc_downstream ) # Create the boundary locations for the discharge and the water level ... ext_model = ExtModel() # External forcing file (.ext) bc_model = ForcingModel() # Boundary conditions file (.bc) model.external_forcing.extforcefilenew = ext_model # Read the upstream boundary time series from excel discharge_file = data_dir / '1D_BoundaryConditions.xlsx' discharge_excel_df = pd.read_excel(discharge_file, sheet_name=[0]) node_ids = model.geometry.netfile.network._mesh1d.network1d_node_id print(node_ids) node_upstream = node_ids[0] # time series discharge node nodes_downstream = node_ids[2:] # constant water level nodes # Create the discharge timeseries bc_upstream = TimeSeries( name = node_upstream, nodeid = node_upstream, timeinterpolation = TimeInterpolation.linear, quantityunitpair = [QuantityUnitPair(quantity = 'time', unit = 'minutes since 2012-01-01 00:00:00'), QuantityUnitPair(quantity = 'dischargebnd', unit = 'm\u00b3/s')], datablock = [[time, dis] for [time,dis] in discharge_excel_df[0].values]) bc_model.forcing.append(bc_upstream) # Create the constant water level for node_downstream in nodes_downstream: bc_downstream = Constant( name = node_downstream, nodeid = node_downstream, quantityunitpair = [QuantityUnitPair(quantity = 'waterlevelbnd', unit = 'm')], datablock = [[\"0.0\"]]) bc_model.forcing.append(bc_downstream) # Create the boundary locations for the discharge and the water level ... 9. Adding initial water depths \u00b6 For this model an initial water depth of 1.0 meter is assumed in the 1D model. Below we add an initial water depth to the model with the following steps: Creating global 1D initial conditions field, containing an initial water depth of 1.0. Note that it is also possible to define the initial water depth per branch. Creating an initial field file containing the initial water depth data for our 1D network In [ ]: Copied! # Create 1D initial conditions field file ini_1d = OneDFieldModel () ini_1d . global_ = OneDFieldGlobal ( quantity = 'waterdepth' , unit = 'm' , value = 1.0 ) ini_1d . filepath = 'initialwaterdepth.ini' ini_1d . save ( export_dir / ini_1d . filepath ) # 1D field ini files needs to be saved seperately, because it is not completely supported yet) # Create initial field file ini_field_model = IniFieldModel () ini_field_model . filepath = 'inifield.ini' ini_field_model . initial = InitialField ( quantity = 'waterdepth' , datafile = ini_1d . filepath , datafiletype = DataFileType . onedfield ) # Assign data to the model model . geometry . inifieldfile = ini_field_model # Create 1D initial conditions field file ini_1d = OneDFieldModel() ini_1d.global_ = OneDFieldGlobal(quantity='waterdepth', unit='m', value=1.0) ini_1d.filepath = 'initialwaterdepth.ini' ini_1d.save(export_dir / ini_1d.filepath) # 1D field ini files needs to be saved seperately, because it is not completely supported yet) # Create initial field file ini_field_model = IniFieldModel() ini_field_model.filepath = 'inifield.ini' ini_field_model.initial = InitialField(quantity='waterdepth',datafile=ini_1d.filepath, datafiletype=DataFileType.onedfield) # Assign data to the model model.geometry.inifieldfile = ini_field_model 10. Adding a weir to a branch \u00b6 Many lakes occur close along Canal del Dique. See figure below. This tutorial assumes that these lakes can function as extra storage for the floods from the river. Hence a weir structure, functioning as a small dam, is added downstream of the lakes. This weir structure has the following conditions: It is located at 70 km from the upstream node of the branch (Channel_1D_1). The crest level is 4.0 m AD. The crest width is 105.0 m. The flow over the dam is in both directions.

    Exercise \ud83e\udde9 Create a new weir object with the described properties Create a new structure model and add the new weir to it Assign the data to the D-Flow FM model In [ ]: Copied! # Create weir structure weir = ... # Create structure model ... # Append weir to structure ... # Assign structure model to D-Flow FM model ... # Create weir structure weir = ... # Create structure model ... # Append weir to structure ... # Assign structure model to D-Flow FM model ... After creating the weir, you want to adjust some values. You found out that the dam should be significantly higher. Exercise \ud83e\udde9 Increase the crest level to 10.0 Change the flow direction to positive (from upstream to downstream) In [ ]: Copied! ... ... 11. Finishing up and saving the model \u00b6 The 1D model is almost finished now. We first change some time settings and then save the model. Exercise \ud83e\udde9 Export the full model to the export folder API references: FileModel.save() In [ ]: Copied! # Change some time settings model . time . refdate = '20120101' model . time . dtuser = 60. # seconds model . time . tstart = 43200. model . time . tstop = 561600. # Save the model ... # Change some time settings model.time.refdate = '20120101' model.time.dtuser = 60. # seconds model.time.tstart = 43200. model.time.tstop = 561600. # Save the model ... Part 2: Extending the 1D model to a 1D2D model \u00b6 We will now continue with the 1D model and add a 2D mesh to it. We won't add 1D2D coupling, but in practice they should be added to create a true 1D2D model. 12. Creating a 2D flexible mesh \u00b6 Here, we demonstrate how to create a 2D mesh using MeshKernel. \u26a0\ufe0f Network and mesh functionality in HYDROLIB-core is still in development. We use a shape file with the area of interest to define the extent of the new 2D mesh that is to be generated. First, a uniform rectilinear mesh with a grid cell size of 2500x2500m is generated. Second, we clip the generated mesh. API references: Mesh2d Mesh2d.clip() mk.MakeGridParameters In [ ]: Copied! # Read grid outline gdf_grid = gpd . read_file ( data_dir / 'outline_2D_grid.shp' ) # Determine the boundary box xmin , ymin , xmax , ymax = gdf_grid . geometry [ 0 ] . bounds mesh2d = Mesh2d () mesh_kernel = mesh2d . meshkernel # Define the grid generation parameters dx = 2500.0 dy = 2500.0 num_rows = int (( ymax - ymin ) / dy ) num_columns = int (( xmax - xmin ) / dx ) origin_x = xmin origin_y = ymin block_size_x = dx block_size_y = dy make_grid_parameters = MakeGridParameters () make_grid_parameters . num_columns = num_columns make_grid_parameters . num_rows = num_rows make_grid_parameters . origin_x = origin_x make_grid_parameters . origin_y = origin_y make_grid_parameters . block_size_x = dx make_grid_parameters . block_size_y = dy make_grid_parameters . upper_right_x = xmax make_grid_parameters . upper_right_y = ymax # Create uniform rectilinear mesh mesh_kernel . curvilinear_make_uniform ( make_grid_parameters ) mesh_kernel . curvilinear_convert_to_mesh2d () mesh2d . _process ( mesh2d . get_mesh2d ()) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np . array ( gdf_grid . geometry [ 0 ] . exterior . xy ) clip_geometry_list = GeometryList ( clip_polygon [ 0 ], clip_polygon [ 1 ]) mesh2d . clip ( clip_geometry_list ) model . geometry . netfile . network . _mesh2d = mesh2d model . geometry . netfile . filepath = \"FlowFM_1D2D_net.nc\" # Read grid outline gdf_grid = gpd.read_file(data_dir / 'outline_2D_grid.shp') # Determine the boundary box xmin, ymin, xmax, ymax = gdf_grid.geometry[0].bounds mesh2d = Mesh2d() mesh_kernel = mesh2d.meshkernel # Define the grid generation parameters dx=2500.0 dy=2500.0 num_rows = int((ymax - ymin) / dy) num_columns = int((xmax - xmin) / dx) origin_x = xmin origin_y = ymin block_size_x = dx block_size_y = dy make_grid_parameters = MakeGridParameters() make_grid_parameters.num_columns = num_columns make_grid_parameters.num_rows = num_rows make_grid_parameters.origin_x = origin_x make_grid_parameters.origin_y = origin_y make_grid_parameters.block_size_x = dx make_grid_parameters.block_size_y = dy make_grid_parameters.upper_right_x = xmax make_grid_parameters.upper_right_y = ymax # Create uniform rectilinear mesh mesh_kernel.curvilinear_make_uniform(make_grid_parameters) mesh_kernel.curvilinear_convert_to_mesh2d() mesh2d._process(mesh2d.get_mesh2d()) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np.array(gdf_grid.geometry[0].exterior.xy) clip_geometry_list = GeometryList(clip_polygon[0],clip_polygon[1]) mesh2d.clip(clip_geometry_list) model.geometry.netfile.network._mesh2d = mesh2d model.geometry.netfile.filepath = \"FlowFM_1D2D_net.nc\" The cell below produces a basic plot of the 1D2D network. In [ ]: Copied! # Create a plot mesh2d_mk = network . _mesh2d . get_mesh2d () mesh1d_mk = network . _mesh1d . _get_mesh1d () figure , axis = plt . subplots () axis . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) mesh2d_mk . plot_edges ( ax = axis , color = \"orange\" ) mesh1d_mk . plot_edges ( ax = axis , color = 'blue' ) # Create a plot mesh2d_mk = network._mesh2d.get_mesh2d() mesh1d_mk = network._mesh1d._get_mesh1d() figure, axis = plt.subplots() axis.imshow(img, extent=[440000, 531544.97964175534434617, 1057000, 1228644.01383191486820579]) mesh2d_mk.plot_edges(ax=axis, color=\"orange\") mesh1d_mk.plot_edges(ax=axis, color='blue') 13. Refining the 2D grid locally \u00b6 Here, we want to refine the 2D mesh around the river using MeshKernel functionality. We will do one refinement iteration. Exercise \ud83e\udde9 Refine the 2D mesh using MeshKernel with the provided refinment parameters (see code below) API references: mk.MeshRefinementParameters mk.mesh2d_refine_based_on_polygon() (not documented yet): First argument is a GeometryList containing the polygon geometry of the area to refine Second argument is a MeshRefinementParameters containing all the parameters for refining In [ ]: Copied! # Get the refinement polygon to refine around the river gdf_refine = gpd . read_file ( data_dir / 'buffer_around_river_proj.shp' ) refine_polygon = np . array ( gdf_refine . geometry [ 0 ] . exterior . xy ) refine_geom = GeometryList ( refine_polygon [ 0 ], refine_polygon [ 1 ]) # Set parameters refine_intersected = True use_mass_center_when_refining = False min_edge_size = 10.0 refinement_type = 1 connect_hanging_nodes = True account_for_samples_outside_face = False max_refinement_iterations = 1 # Refine the 2D mesh ... # Set 2D mesh on model mesh2d . _process ( mesh2d . get_mesh2d ()) model . geometry . netfile . network . _mesh2d = mesh2d model . geometry . netfile . filepath = \"FlowFM_1D2D_refined_net.nc\" # Get the refinement polygon to refine around the river gdf_refine = gpd.read_file(data_dir / 'buffer_around_river_proj.shp') refine_polygon = np.array(gdf_refine.geometry[0].exterior.xy) refine_geom = GeometryList(refine_polygon[0], refine_polygon[1]) # Set parameters refine_intersected = True use_mass_center_when_refining = False min_edge_size = 10.0 refinement_type = 1 connect_hanging_nodes = True account_for_samples_outside_face = False max_refinement_iterations = 1 # Refine the 2D mesh ... # Set 2D mesh on model mesh2d._process(mesh2d.get_mesh2d()) model.geometry.netfile.network._mesh2d = mesh2d model.geometry.netfile.filepath = \"FlowFM_1D2D_refined_net.nc\" In [ ]: Copied! # Create a plot mesh2d_mk = network . _mesh2d . get_mesh2d () mesh1d_mk = network . _mesh1d . _get_mesh1d () figure , axis = plt . subplots () axis . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) mesh2d_mk . plot_edges ( ax = axis , color = \"orange\" ) mesh1d_mk . plot_edges ( ax = axis , color = 'blue' ) # Create a plot mesh2d_mk = network._mesh2d.get_mesh2d() mesh1d_mk = network._mesh1d._get_mesh1d() figure, axis = plt.subplots() axis.imshow(img, extent=[440000, 531544.97964175534434617, 1057000, 1228644.01383191486820579]) mesh2d_mk.plot_edges(ax=axis, color=\"orange\") mesh1d_mk.plot_edges(ax=axis, color='blue') 14. Saving the 1D2D model \u00b6 The 1D2D model is now finished. Exercise \ud83e\udde9 Save the model wherever you like Import the D-Flow FM model in the Delft3D FM Suite 1D2D In [ ]: Copied! model . save ( recurse = True ) model.save(recurse=True)","title":"Creating a Delft3D FM 1D2D fluvial flood model of Magdalena river"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#creating-a-delft3d-fm-1d2d-fluvial-flood-model-of-magdalena-river","text":"The exercises in this notebook will serve as introduction on how to use HYDROLIB-core functionalities. We will create and adjust a Delft3D FM Suite 1D2D fluvial flood model of the Magdalena river in Columbia. First a 1D river model of the Magdalena river and Canal del Dique will be created, shown in the left figure. This model will be extended with a 2D Flexible Mesh, with a uniform roughness field. Adding a Digital Terrain Model (DTM) on that 2D mesh is currently not part of this tutorial, but in practice this is indispensible to mimic the fluvial flood patterns. Note that the model that will be created is for educational purposes and consists partially of fictive or unvalidated model data.","title":"Creating a Delft3D FM 1D2D fluvial flood model of Magdalena river"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#using-hydrolib-core-to-build-models","text":"HYDROLIB-core is a Python package that offers functionality to process D-HYDRO input files. It offers Python-wrapped classes that represent these files and their content. HYDROLIB-core serves as the basis for various pre- and postprocessing tools for a modelling workflow of hydrodynamic simulations in D-HYDRO. It can easily be used to build models and export the model files that can aftewards be run by dflowfm or other supported D-HYDRO kernels.","title":"Using HYDROLIB-core to build models"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#content-of-the-tutorial","text":"The goal of this tutorial is to familiarize modelers with applying HYDROLIB-core functionalities in their modelling procedures for building new models or adjusting existing models. As mentioned above, you will create an 1D2D fluvial flood model from scratch using the D-Flow FM HYDROLIB-core functionalities and the underlying functions from mesh generation ( MeshKernelPy ). We will walk through the following steps to build the model: Selecting the data location Creating an empty D-Flow FM model Reading the branch data from a shape file Creating and assigning a 1D computational grid to the model Adding cross-sections to the branches Adding cross-section definitions Adding roughness to the model Adding boundary conditions to the model Adding initial water depths Adding a weir to a branch Finishing up and saving the model Creating a 2D flexible mesh Refining the 2D grid locally Saving the 1D2D model","title":"Content of the tutorial"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#tips-for-working-in-the-jupyter-notebook","text":"Tab : Auto-complete on code Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell","title":"\ud83d\udca1 Tips for working in the Jupyter Notebook"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#import-the-needed-modules","text":"Several Python packages are required to run the notebook. These packages are imported below. Please consult the HYDROLIB-core documentation if you want to use additional HYDROLIB-core functionalities later. In [ ]: Copied! # General import geopandas as gpd import matplotlib.pyplot as plt import numpy as np import pandas as pd from pathlib import Path # MeshKernel import meshkernel as mk from meshkernel import GeometryList , MakeGridParameters # HYDROLIB-core from hydrolib.core.dflowfm.mdu import FMModel , AutoStartOption from hydrolib.core.dflowfm.net.models import * from hydrolib.core.dflowfm.crosssection.models import CrossLocModel , CrossDefModel , YZCrsDef from hydrolib.core.dflowfm.friction.models import * from hydrolib.core.dflowfm.bc.models import * from hydrolib.core.dflowfm.ext.models import * from hydrolib.core.dflowfm.inifield.models import * from hydrolib.core.dflowfm.onedfield.models import * from hydrolib.core.dflowfm.structure.models import Weir , FlowDirection , StructureModel print ( \"Imports were successful!\" ) # General import geopandas as gpd import matplotlib.pyplot as plt import numpy as np import pandas as pd from pathlib import Path # MeshKernel import meshkernel as mk from meshkernel import GeometryList, MakeGridParameters # HYDROLIB-core from hydrolib.core.dflowfm.mdu import FMModel, AutoStartOption from hydrolib.core.dflowfm.net.models import * from hydrolib.core.dflowfm.crosssection.models import CrossLocModel, CrossDefModel, YZCrsDef from hydrolib.core.dflowfm.friction.models import * from hydrolib.core.dflowfm.bc.models import * from hydrolib.core.dflowfm.ext.models import * from hydrolib.core.dflowfm.inifield.models import * from hydrolib.core.dflowfm.onedfield.models import * from hydrolib.core.dflowfm.structure.models import Weir, FlowDirection, StructureModel print(\"Imports were successful!\")","title":"Import the needed modules"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#here-starts-the-tutorial","text":"","title":"Here starts the tutorial"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#1-selecting-the-data-location","text":"Exercise \ud83e\udde9: Create a variable that contains the Path to the data folder. In [ ]: Copied! data_dir = ... print ( f \"Data location: { data_dir } \" ) data_dir = ... print(f\"Data location: {data_dir}\")","title":"1. Selecting the data location"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#2-creating-an-empty-d-flow-fm-model","text":"To start a model from scratch, you first need to create an empty model without data. In this tutorial we will create a D-Flow FM model. The MDU file (master definition file) is the main input file of the D-Flow FM model. A new D-Flow FM model is constructed with the FMModel initializer. Exercise \ud83e\udde9 Create a variable containing a new FMModel object. Create a variable containing the export directory Export the D-Flow FM model to an MDU file inside the export directory API references: FMModel FileModel.filepath FileModel.save() In [ ]: Copied! model = ... export_dir = ... model . filepath = ... # Save the MDU file ... print ( f \"MDU file saved: { model . filepath } \" ) model = ... export_dir = ... model.filepath = ... # Save the MDU file ... print(f\"MDU file saved: {model.filepath}\")","title":"2. Creating an empty D-Flow FM model"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#part-1-setting-up-a-1d-delft3d-fm-model","text":"In this part we will build up the complete 1D model schematization step by step. At the end you should have a complete set of model input files for a 1D calculation.","title":"Part 1: Setting up a 1D Delft3D FM model"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#3-reading-the-branch-data-from-a-shape-file","text":"The model will include the lower part of the Magadalena from Cordoba Teton to the river mouth Baranquilla and the Canal del Dique. Exercise \ud83e\udde9 Read the branch data from the branches_Branches.shp file Print the branch data, such that we can answer the following questions: How many river branches does the model have? What are their names? Which friction type and friction value is used for each branch? API references: gpd.read_file In [ ]: Copied! # Read the branches ... # Print the data ... # Answers: # * ... # * ... # * ... # Read the branches ... # Print the data ... # Answers: # * ... # * ... # * ...","title":"3. Reading the branch data from a shape file"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#4-creating-and-assigning-a-1d-computational-grid-to-the-model","text":"In the previous step we read the geometry and attributes of the branches from the shape file. This branch data will become the network input for our D-Flow FM model. Since the model does not have a network yet, we need to create a new network object and assign it to the model. A network may contain a 1D network, a 2D mesh and 1D2D links. Exercise \ud83e\udde9 Create a new network Assign the network to the model and assign a (relative) file path for the net file The new network should contain the data that we read from the shape file: Three Branch objects will need to be added to the network. For each branch, the name, geometry and computational grid points should be provided. The computational points are not included in the data, we will need to generate those with a grid point distance as specified: Branch name dx [m] Channel_1D_1_A 1000 Channel_1D_1_B 1000 Channel_1D_1 500 Hint \ud83d\udca1: The MDU file contains a [Geometry] section which has the network file reference, e.g.: [Geometry] netFile = FlowFM_net.nc ... API references: Network NetworkModel Branch Branch.generate_nodes() Network.mesh1d_add_branch() (undocumented): Adds a branch to the 1D network. The function needs two arguments: Branch : the branch to be added str : The name of the branch that is added In [ ]: Copied! # Assign a new network to the D-Flow FM model and specify the file path network = ... # Specify 1D computational grid point distance per branch dx_per_branch = { \"Channel_1D_1_A\" : 1000 , \"Channel_1D_1_B\" : 1000 , \"Channel_1D_1\" : 500 , } # Assign geometry of the branches and generate the computational grid on top of the branches. # Add each branch to the network for index , branch_data in branches_gdf . iterrows (): branch_geometry = np . transpose ( branch_data . geometry . xy ) ... network . _mesh1d . _set_mesh1d () # Assign a new network to the D-Flow FM model and specify the file path network = ... # Specify 1D computational grid point distance per branch dx_per_branch = { \"Channel_1D_1_A\" : 1000, \"Channel_1D_1_B\" : 1000, \"Channel_1D_1\" : 500, } # Assign geometry of the branches and generate the computational grid on top of the branches. # Add each branch to the network for index, branch_data in branches_gdf.iterrows(): branch_geometry = np.transpose(branch_data.geometry.xy) ... network._mesh1d._set_mesh1d() We can plot the branches onto a background: In [ ]: Copied! # Create a figure with the 1D network figure , axis = plt . subplots ( ncols = 1 ) img = plt . imread ( data_dir / \"osm_background.png\" ) # Add branch names to the plot for branch_name , branch in network . _mesh1d . branches . items (): middle = int (( len ( branch . geometry ) - 1 ) / 2 ) xy = branch . geometry [ middle ] axis . text ( xy [ 0 ], xy [ 1 ], branch_name , ha = 'center' ) axis . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) network . _mesh1d . _get_mesh1d () . plot_edges ( ax = axis , color = 'blue' ) # Create a figure with the 1D network figure, axis = plt.subplots(ncols=1) img = plt.imread(data_dir / \"osm_background.png\") # Add branch names to the plot for branch_name, branch in network._mesh1d.branches.items(): middle = int((len(branch.geometry) - 1)/2) xy = branch.geometry[middle] axis.text(xy[0], xy[1], branch_name, ha='center') axis.imshow(img, extent=[440000, 531544.97964175534434617, 1057000, 1228644.01383191486820579]) network._mesh1d._get_mesh1d().plot_edges(ax=axis, color='blue')","title":"4. Creating and assigning a 1D computational grid to the model"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#5-adding-cross-sections-to-the-branches","text":"In order to determine the flow area of the 1D model during the computation, you need cross-sections. These cross-sections are defined by two components: Cross-section locations Cross-section definitions The cross-section locations and cross-section definitions are exported to their own file. A cross-section location is defined by the following information: The cross-section ID A location, specified by a branch ID and a chainage. A shift, the vertical shift of the cross section profile. This is mainly used to create a good longitudinal slope over the 1D model (in case of shared cross-sections). A reference to the cross-section definition that is used at this location.

    A cross-section definition is defined by the following information: The cross-section definition ID The cross-section type: circle, rectangle, ZW river, ZW, YZ, XYZ Depending on the type of cross-section, a set of properties describing the properties of the profile shape

    In our data folder, there is a CSV file containing the cross-section locations. We want to convert this data to HYDROLIB-core cross-section location objects and add them to the D-Flow FM model. The columns in the CSV correspond exactly with the field names of a CrossSection class, making the conversion easy. Exercise \ud83e\udde9 Read the data from the CSV file Print the cross-section location data, to answer the following questions: How many cross-section does the model contain in total, and how many does each branch have? Do the cross-section have shared cross-section definitions? A shared cross-section definition is a definition used by more than one cross-section. Convert the CSV data (a pd.DataFrame) into HYDROLIB-core CrossSection objects Assign the cross section locations to the model Hint \ud83d\udca1: The MDU file contains a [Geometry] section which has the crossDefFile and crossLocFile reference, e.g.: [Geometry] crossDefFile = crsdef.ini crossLocFile = crsloc.ini ... API references: pd.read_csv() pd.to_dict() CrossLocModel CrossSection In [ ]: Copied! # Read the cross-sections from the CSV cross_section_data_file = ... cross_section_df = ... # Print the data ... # Answers: # * ... # * ... # Assign the data to the model ... # Read the cross-sections from the CSV cross_section_data_file = ... cross_section_df = ... # Print the data ... # Answers: # * ... # * ... # Assign the data to the model ...","title":"5. 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These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ --jp-shadow-base-lightness: 0; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-400); --jp-border-color1: var(--md-grey-400); --jp-border-color2: var(--md-grey-300); --jp-border-color3: var(--md-grey-200); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(0, 0, 0, 1); --jp-ui-font-color1: rgba(0, 0, 0, 0.87); --jp-ui-font-color2: rgba(0, 0, 0, 0.54); --jp-ui-font-color3: rgba(0, 0, 0, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color1: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color2: rgba(255, 255, 255, 0.7); --jp-ui-inverse-font-color3: rgba(255, 255, 255, 0.5); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(0, 0, 0, 1); --jp-content-font-color1: rgba(0, 0, 0, 0.87); --jp-content-font-color2: rgba(0, 0, 0, 0.54); --jp-content-font-color3: rgba(0, 0, 0, 0.38); --jp-content-link-color: var(--md-blue-700); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: white; --jp-layout-color1: white; --jp-layout-color2: var(--md-grey-200); --jp-layout-color3: var(--md-grey-400); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: #111111; --jp-inverse-layout-color1: var(--md-grey-900); --jp-inverse-layout-color2: var(--md-grey-800); --jp-inverse-layout-color3: var(--md-grey-700); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-900); --jp-brand-color1: var(--md-blue-700); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-900); --jp-accent-color1: var(--md-green-700); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-900); --jp-warn-color1: var(--md-orange-700); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-900); --jp-error-color1: var(--md-red-700); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-900); --jp-success-color1: var(--md-green-700); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-900); --jp-info-color1: var(--md-cyan-700); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--md-grey-100); --jp-cell-editor-border-color: var(--md-grey-300); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 0.5; --jp-cell-prompt-not-active-font-color: var(--md-grey-700); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: var(--md-blue-50); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: #fdd; --jp-rendermime-table-row-background: var(--md-grey-100); --jp-rendermime-table-row-hover-background: var(--md-light-blue-50); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.25); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color1); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.24); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--md-grey-300); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color1); --jp-input-hover-background: var(--jp-layout-color1); --jp-input-background: var(--md-grey-100); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: #d9d9d9; --jp-editor-selected-focused-background: #d7d4f0; --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: #008000; --jp-mirror-editor-atom-color: #88f; --jp-mirror-editor-number-color: #080; --jp-mirror-editor-def-color: #00f; --jp-mirror-editor-variable-color: var(--md-grey-900); --jp-mirror-editor-variable-2-color: #05a; --jp-mirror-editor-variable-3-color: #085; --jp-mirror-editor-punctuation-color: #05a; --jp-mirror-editor-property-color: #05a; --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ba2121; --jp-mirror-editor-string-2-color: #708; --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: #008000; --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: #170; --jp-mirror-editor-attribute-color: #00c; --jp-mirror-editor-header-color: blue; --jp-mirror-editor-quote-color: #090; --jp-mirror-editor-link-color: #00c; --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: white; /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.5; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(245, 200, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } [data-md-color-scheme=\"slate\"] .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ /* The dark theme shadows need a bit of work, but this will probably also require work on the core layout * colors used in the theme as well. */ --jp-shadow-base-lightness: 32; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-700); --jp-border-color1: var(--md-grey-700); --jp-border-color2: var(--md-grey-800); --jp-border-color3: var(--md-grey-900); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(255, 255, 255, 1); --jp-ui-font-color1: rgba(255, 255, 255, 0.87); --jp-ui-font-color2: rgba(255, 255, 255, 0.54); --jp-ui-font-color3: rgba(255, 255, 255, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(0, 0, 0, 1); --jp-ui-inverse-font-color1: rgba(0, 0, 0, 0.8); --jp-ui-inverse-font-color2: rgba(0, 0, 0, 0.5); --jp-ui-inverse-font-color3: rgba(0, 0, 0, 0.3); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(255, 255, 255, 1); --jp-content-font-color1: rgba(255, 255, 255, 1); --jp-content-font-color2: rgba(255, 255, 255, 0.7); --jp-content-font-color3: rgba(255, 255, 255, 0.5); --jp-content-link-color: var(--md-blue-300); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: #111111; --jp-layout-color1: var(--md-grey-900); --jp-layout-color2: var(--md-grey-800); --jp-layout-color3: var(--md-grey-700); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: white; --jp-inverse-layout-color1: white; --jp-inverse-layout-color2: var(--md-grey-200); --jp-inverse-layout-color3: var(--md-grey-400); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-700); --jp-brand-color1: var(--md-blue-500); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-700); --jp-accent-color1: var(--md-green-500); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-700); --jp-warn-color1: var(--md-orange-500); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-700); --jp-error-color1: var(--md-red-500); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-700); --jp-success-color1: var(--md-green-500); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-700); --jp-info-color1: var(--md-cyan-500); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--jp-layout-color1); --jp-cell-editor-border-color: var(--md-grey-700); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 1; --jp-cell-prompt-not-active-font-color: var(--md-grey-300); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: rgba(33, 150, 243, 0.24); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: rgba(244, 67, 54, 0.28); --jp-rendermime-table-row-background: var(--md-grey-900); --jp-rendermime-table-row-hover-background: rgba(3, 169, 244, 0.2); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.6); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color2); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.8); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--jp-layout-color0); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color0); --jp-input-hover-background: var(--jp-layout-color2); --jp-input-background: var(--md-grey-800); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: var(--jp-layout-color2); --jp-editor-selected-focused-background: rgba(33, 150, 243, 0.24); --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: var(--md-green-500); --jp-mirror-editor-atom-color: var(--md-blue-300); --jp-mirror-editor-number-color: var(--md-green-400); --jp-mirror-editor-def-color: var(--md-blue-600); --jp-mirror-editor-variable-color: var(--md-grey-300); --jp-mirror-editor-variable-2-color: var(--md-blue-400); --jp-mirror-editor-variable-3-color: var(--md-green-600); --jp-mirror-editor-punctuation-color: var(--md-blue-400); --jp-mirror-editor-property-color: var(--md-blue-400); --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ff7070; --jp-mirror-editor-string-2-color: var(--md-purple-300); --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: var(--md-green-600); --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: var(--md-green-700); --jp-mirror-editor-attribute-color: var(--md-blue-700); --jp-mirror-editor-header-color: var(--md-blue-500); --jp-mirror-editor-quote-color: var(--md-green-300); --jp-mirror-editor-link-color: var(--md-blue-700); --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: var(--md-grey-400); /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.6; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(255, 225, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* scrollbar related styles. Supports every browser except Edge. */ /* colors based on JetBrain's Darcula theme */ --jp-scrollbar-background-color: #3f4244; --jp-scrollbar-thumb-color: 88, 96, 97; /* need to specify thumb color as an RGB triplet */ --jp-scrollbar-endpad: 3px; /* the minimum gap between the thumb and the ends of a scrollbar */ /* hacks for setting the thumb shape. These do nothing in Firefox */ --jp-scrollbar-thumb-margin: 3.5px; /* the space in between the sides of the thumb and the track */ --jp-scrollbar-thumb-radius: 9px; /* set to a large-ish value for rounded endcaps on the thumb */ /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } :root{--md-red-50: #ffebee;--md-red-100: #ffcdd2;--md-red-200: #ef9a9a;--md-red-300: #e57373;--md-red-400: #ef5350;--md-red-500: #f44336;--md-red-600: #e53935;--md-red-700: #d32f2f;--md-red-800: #c62828;--md-red-900: #b71c1c;--md-red-A100: #ff8a80;--md-red-A200: #ff5252;--md-red-A400: #ff1744;--md-red-A700: #d50000;--md-pink-50: #fce4ec;--md-pink-100: #f8bbd0;--md-pink-200: #f48fb1;--md-pink-300: #f06292;--md-pink-400: #ec407a;--md-pink-500: #e91e63;--md-pink-600: #d81b60;--md-pink-700: #c2185b;--md-pink-800: 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#7986cb;--md-indigo-400: #5c6bc0;--md-indigo-500: #3f51b5;--md-indigo-600: #3949ab;--md-indigo-700: #303f9f;--md-indigo-800: #283593;--md-indigo-900: #1a237e;--md-indigo-A100: #8c9eff;--md-indigo-A200: #536dfe;--md-indigo-A400: #3d5afe;--md-indigo-A700: #304ffe;--md-blue-50: #e3f2fd;--md-blue-100: #bbdefb;--md-blue-200: #90caf9;--md-blue-300: #64b5f6;--md-blue-400: #42a5f5;--md-blue-500: #2196f3;--md-blue-600: #1e88e5;--md-blue-700: #1976d2;--md-blue-800: #1565c0;--md-blue-900: #0d47a1;--md-blue-A100: #82b1ff;--md-blue-A200: #448aff;--md-blue-A400: #2979ff;--md-blue-A700: #2962ff;--md-light-blue-50: #e1f5fe;--md-light-blue-100: #b3e5fc;--md-light-blue-200: #81d4fa;--md-light-blue-300: #4fc3f7;--md-light-blue-400: #29b6f6;--md-light-blue-500: #03a9f4;--md-light-blue-600: #039be5;--md-light-blue-700: #0288d1;--md-light-blue-800: #0277bd;--md-light-blue-900: #01579b;--md-light-blue-A100: #80d8ff;--md-light-blue-A200: #40c4ff;--md-light-blue-A400: #00b0ff;--md-light-blue-A700: #0091ea;--md-cyan-50: #e0f7fa;--md-cyan-100: #b2ebf2;--md-cyan-200: #80deea;--md-cyan-300: #4dd0e1;--md-cyan-400: #26c6da;--md-cyan-500: #00bcd4;--md-cyan-600: #00acc1;--md-cyan-700: #0097a7;--md-cyan-800: #00838f;--md-cyan-900: #006064;--md-cyan-A100: #84ffff;--md-cyan-A200: #18ffff;--md-cyan-A400: #00e5ff;--md-cyan-A700: #00b8d4;--md-teal-50: #e0f2f1;--md-teal-100: #b2dfdb;--md-teal-200: #80cbc4;--md-teal-300: #4db6ac;--md-teal-400: #26a69a;--md-teal-500: #009688;--md-teal-600: #00897b;--md-teal-700: #00796b;--md-teal-800: #00695c;--md-teal-900: #004d40;--md-teal-A100: #a7ffeb;--md-teal-A200: #64ffda;--md-teal-A400: #1de9b6;--md-teal-A700: #00bfa5;--md-green-50: #e8f5e9;--md-green-100: #c8e6c9;--md-green-200: #a5d6a7;--md-green-300: #81c784;--md-green-400: #66bb6a;--md-green-500: #4caf50;--md-green-600: #43a047;--md-green-700: #388e3c;--md-green-800: #2e7d32;--md-green-900: #1b5e20;--md-green-A100: #b9f6ca;--md-green-A200: #69f0ae;--md-green-A400: #00e676;--md-green-A700: #00c853;--md-light-green-50: #f1f8e9;--md-light-green-100: #dcedc8;--md-light-green-200: #c5e1a5;--md-light-green-300: #aed581;--md-light-green-400: #9ccc65;--md-light-green-500: #8bc34a;--md-light-green-600: #7cb342;--md-light-green-700: #689f38;--md-light-green-800: #558b2f;--md-light-green-900: #33691e;--md-light-green-A100: #ccff90;--md-light-green-A200: #b2ff59;--md-light-green-A400: #76ff03;--md-light-green-A700: #64dd17;--md-lime-50: #f9fbe7;--md-lime-100: #f0f4c3;--md-lime-200: #e6ee9c;--md-lime-300: #dce775;--md-lime-400: #d4e157;--md-lime-500: #cddc39;--md-lime-600: #c0ca33;--md-lime-700: #afb42b;--md-lime-800: #9e9d24;--md-lime-900: #827717;--md-lime-A100: #f4ff81;--md-lime-A200: #eeff41;--md-lime-A400: #c6ff00;--md-lime-A700: #aeea00;--md-yellow-50: #fffde7;--md-yellow-100: #fff9c4;--md-yellow-200: #fff59d;--md-yellow-300: #fff176;--md-yellow-400: #ffee58;--md-yellow-500: #ffeb3b;--md-yellow-600: #fdd835;--md-yellow-700: #fbc02d;--md-yellow-800: #f9a825;--md-yellow-900: #f57f17;--md-yellow-A100: #ffff8d;--md-yellow-A200: #ffff00;--md-yellow-A400: #ffea00;--md-yellow-A700: #ffd600;--md-amber-50: #fff8e1;--md-amber-100: #ffecb3;--md-amber-200: #ffe082;--md-amber-300: #ffd54f;--md-amber-400: #ffca28;--md-amber-500: #ffc107;--md-amber-600: #ffb300;--md-amber-700: #ffa000;--md-amber-800: #ff8f00;--md-amber-900: #ff6f00;--md-amber-A100: #ffe57f;--md-amber-A200: #ffd740;--md-amber-A400: #ffc400;--md-amber-A700: #ffab00;--md-orange-50: #fff3e0;--md-orange-100: #ffe0b2;--md-orange-200: #ffcc80;--md-orange-300: #ffb74d;--md-orange-400: #ffa726;--md-orange-500: #ff9800;--md-orange-600: #fb8c00;--md-orange-700: #f57c00;--md-orange-800: #ef6c00;--md-orange-900: #e65100;--md-orange-A100: #ffd180;--md-orange-A200: #ffab40;--md-orange-A400: #ff9100;--md-orange-A700: #ff6d00;--md-deep-orange-50: #fbe9e7;--md-deep-orange-100: #ffccbc;--md-deep-orange-200: #ffab91;--md-deep-orange-300: #ff8a65;--md-deep-orange-400: #ff7043;--md-deep-orange-500: 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sourceMappingURL=mkdocs-jupyter.css.map*/ init_mathjax = function() { if (window.MathJax) { // MathJax loaded MathJax.Hub.Config({ TeX: { equationNumbers: { autoNumber: \"AMS\", useLabelIds: true } }, tex2jax: { inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ], displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ], processEscapes: true, processEnvironments: true }, displayAlign: 'center', CommonHTML: { linebreaks: { automatic: true } } }); MathJax.Hub.Queue([\"Typeset\", MathJax.Hub]); } } init_mathjax(); Creating a Delft3D FM 1D2D fluvial flood model of Magdalena river \u00b6 The exercises in this notebook will serve as introduction on how to use HYDROLIB-core functionalities. We will create and adjust a Delft3D FM Suite 1D2D fluvial flood model of the Magdalena river in Columbia. First a 1D river model of the Magdalena river and Canal del Dique will be created, shown in the left figure. This model will be extended with a 2D Flexible Mesh, with a uniform roughness field. Adding a Digital Terrain Model (DTM) on that 2D mesh is currently not part of this tutorial, but in practice this is indispensible to mimic the fluvial flood patterns. Note that the model that will be created is for educational purposes and consists partially of fictive or unvalidated model data. Using HYDROLIB-core to build models \u00b6 HYDROLIB-core is a Python package that offers functionality to process D-HYDRO input files. It offers Python-wrapped classes that represent these files and their content. HYDROLIB-core serves as the basis for various pre- and postprocessing tools for a modelling workflow of hydrodynamic simulations in D-HYDRO. It can easily be used to build models and export the model files that can aftewards be run by dflowfm or other supported D-HYDRO kernels. Content of the tutorial \u00b6 The goal of this tutorial is to familiarize modelers with applying HYDROLIB-core functionalities in their modelling procedures for building new models or adjusting existing models. As mentioned above, you will create an 1D2D fluvial flood model from scratch using the D-Flow FM HYDROLIB-core functionalities and the underlying functions from mesh generation ( MeshKernelPy ). We will walk through the following steps to build the model: Selecting the data location Creating an empty D-Flow FM model Reading the branch data from a shape file Creating and assigning a 1D computational grid to the model Adding cross-sections to the branches Adding cross-section definitions Adding roughness to the model Adding boundary conditions to the model Adding initial water depths Adding a weir to a branch Finishing up and saving the model Creating a 2D flexible mesh Refining the 2D grid locally Saving the 1D2D model \ud83d\udca1 Tips for working in the Jupyter Notebook \u00b6 Tab : Auto-complete on code Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell Import the needed modules \u00b6 Several Python packages are required to run the notebook. These packages are imported below. Please consult the HYDROLIB-core documentation if you want to use additional HYDROLIB-core functionalities later. In [ ]: Copied! # General import geopandas as gpd import matplotlib.pyplot as plt import numpy as np import pandas as pd from pathlib import Path # MeshKernel import meshkernel as mk from meshkernel import GeometryList , MakeGridParameters # HYDROLIB-core from hydrolib.core.dflowfm.mdu import FMModel , AutoStartOption from hydrolib.core.dflowfm.net.models import * from hydrolib.core.dflowfm.crosssection.models import CrossLocModel , CrossDefModel , YZCrsDef from hydrolib.core.dflowfm.friction.models import * from hydrolib.core.dflowfm.bc.models import * from hydrolib.core.dflowfm.ext.models import * from hydrolib.core.dflowfm.inifield.models import * from hydrolib.core.dflowfm.onedfield.models import * from hydrolib.core.dflowfm.structure.models import Weir , FlowDirection , StructureModel print ( \"Imports were successful!\" ) # General import geopandas as gpd import matplotlib.pyplot as plt import numpy as np import pandas as pd from pathlib import Path # MeshKernel import meshkernel as mk from meshkernel import GeometryList, MakeGridParameters # HYDROLIB-core from hydrolib.core.dflowfm.mdu import FMModel, AutoStartOption from hydrolib.core.dflowfm.net.models import * from hydrolib.core.dflowfm.crosssection.models import CrossLocModel, CrossDefModel, YZCrsDef from hydrolib.core.dflowfm.friction.models import * from hydrolib.core.dflowfm.bc.models import * from hydrolib.core.dflowfm.ext.models import * from hydrolib.core.dflowfm.inifield.models import * from hydrolib.core.dflowfm.onedfield.models import * from hydrolib.core.dflowfm.structure.models import Weir, FlowDirection, StructureModel print(\"Imports were successful!\") Here starts the tutorial \u00b6 1. Selecting the data location \u00b6 Exercise \ud83e\udde9: Create a variable that contains the Path to the data folder. In [ ]: Copied! root = Path . cwd () data_dir = root / 'data' print ( f \"Data location: { data_dir } \" ) root = Path.cwd() data_dir = root / 'data' print(f\"Data location: {data_dir}\") 2. Creating an empty D-Flow FM model \u00b6 To start a model from scratch, you first need to create an empty model without data. In this tutorial we will create a D-Flow FM model. The MDU file (master definition file) is the main input file of the D-Flow FM model. A new D-Flow FM model is constructed with the FMModel initializer. Exercise \ud83e\udde9 Create a variable containing a new FMModel object. Create a variable containing the export directory Export the D-Flow FM model to an MDU file inside the export directory API references: FMModel FileModel.filepath FileModel.save() In [ ]: Copied! model = FMModel () export_dir = root / 'export' model . filepath = export_dir / 'Magdalena_1D.mdu' # Save the MDU file model . save () print ( f \"MDU file saved: { model . filepath } \" ) model = FMModel() export_dir = root / 'export' model.filepath = export_dir / 'Magdalena_1D.mdu' # Save the MDU file model.save() print(f\"MDU file saved: {model.filepath}\") Part 1: Setting up a 1D Delft3D FM model \u00b6 In this part we will build up the complete 1D model schematization step by step. At the end you should have a complete set of model input files for a 1D calculation. 3. Reading the branch data from a shape file \u00b6 The model will include the lower part of the Magadalena from Cordoba Teton to the river mouth Baranquilla and the Canal del Dique. Exercise \ud83e\udde9 Read the branch data from the branches_Branches.shp file Print the branch data, such that we can answer the following questions: How many river branches does the model have? What are their names? Which friction type and friction value is used for each branch? API references: gpd.read_file In [ ]: Copied! # Read the branches branch_shp_file = data_dir / 'branches_Branches.shp' branches_gdf = gpd . read_file ( filename = branch_shp_file ) # Print the data print ( branches_gdf ) # Answers: # * 3 branches # * Channel_1D_1_A, Channel_1D_1_B and Channel_1D_1 # * Channel_1D_1_A: Manning, 0.03 # Channel_1D_1_B: Manning, 0.02 # Channel_1D_1 : Manning, 0.02 # Read the branches branch_shp_file = data_dir / 'branches_Branches.shp' branches_gdf = gpd.read_file(filename = branch_shp_file) # Print the data print(branches_gdf) # Answers: # * 3 branches # * Channel_1D_1_A, Channel_1D_1_B and Channel_1D_1 # * Channel_1D_1_A: Manning, 0.03 # Channel_1D_1_B: Manning, 0.02 # Channel_1D_1 : Manning, 0.02 4. Creating and assigning a 1D computational grid to the model \u00b6 In the previous step we read the geometry and attributes of the branches from the shape file. This branch data will become the network input for our D-Flow FM model. Since the model does not have a network yet, we need to create a new network object and assign it to the model. A network may contain a 1D network, a 2D mesh and 1D2D links. Exercise \ud83e\udde9 Create a new network Assign the network to the model and assign a (relative) file path for the net file The new network should contain the data that we read from the shape file: Three Branch objects will need to be added to the network. For each branch, the name, geometry and computational grid points should be provided. The computational points are not included in the data, we will need to generate those with a grid point distance as specified: Branch name dx [m] Channel_1D_1_A 1000 Channel_1D_1_B 1000 Channel_1D_1 500 Hint \ud83d\udca1: The MDU file contains a [Geometry] section which has the network file reference, e.g.: [Geometry] netFile = FlowFM_net.nc ... API references: Network NetworkModel Branch Branch.generate_nodes() Network.mesh1d_add_branch() (undocumented): Adds a branch to the 1D network. The function needs two arguments: Branch : the branch to be added str : The name of the branch that is added In [ ]: Copied! # Assign a new network to the D-Flow FM model and specify the file path network = Network () model . geometry . netfile . network = network model . geometry . netfile . filepath = \"FlowFM_net.nc\" # Specify 1D computational grid point distance per branch dx_per_branch = { \"Channel_1D_1_A\" : 1000 , \"Channel_1D_1_B\" : 1000 , \"Channel_1D_1\" : 500 , } # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch_data in branches_gdf . iterrows (): branch_geometry = np . transpose ( branch_data . geometry . xy ) branch = Branch ( geometry = branch_geometry ) branch . generate_nodes ( mesh1d_edge_length = dx_per_branch [ branch_data . Name ]) network . mesh1d_add_branch ( branch , name = branch_data . Name ) network . _mesh1d . _set_mesh1d () # Assign a new network to the D-Flow FM model and specify the file path network = Network() model.geometry.netfile.network = network model.geometry.netfile.filepath = \"FlowFM_net.nc\" # Specify 1D computational grid point distance per branch dx_per_branch = { \"Channel_1D_1_A\" : 1000, \"Channel_1D_1_B\" : 1000, \"Channel_1D_1\" : 500, } # Assign geometry of the branches and generate the computational grid on top of the branches. for index, branch_data in branches_gdf.iterrows(): branch_geometry = np.transpose(branch_data.geometry.xy) branch = Branch(geometry=branch_geometry) branch.generate_nodes(mesh1d_edge_length=dx_per_branch[branch_data.Name]) network.mesh1d_add_branch(branch, name=branch_data.Name) network._mesh1d._set_mesh1d() We can plot the branches onto a background: In [ ]: Copied! # Create a figure with the 1D network figure , axis = plt . subplots ( ncols = 1 ) img = plt . imread ( data_dir / \"osm_background.png\" ) # Add branch names to the plot for branch_name , branch in network . _mesh1d . branches . items (): middle = int (( len ( branch . geometry ) - 1 ) / 2 ) xy = branch . geometry [ middle ] axis . text ( xy [ 0 ], xy [ 1 ], branch_name , ha = 'center' ) axis . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) network . _mesh1d . _get_mesh1d () . plot_edges ( ax = axis , color = 'blue' ) # Create a figure with the 1D network figure, axis = plt.subplots(ncols=1) img = plt.imread(data_dir / \"osm_background.png\") # Add branch names to the plot for branch_name, branch in network._mesh1d.branches.items(): middle = int((len(branch.geometry) - 1)/2) xy = branch.geometry[middle] axis.text(xy[0], xy[1], branch_name, ha='center') axis.imshow(img, extent=[440000, 531544.97964175534434617, 1057000, 1228644.01383191486820579]) network._mesh1d._get_mesh1d().plot_edges(ax=axis, color='blue') 5. Adding cross-sections to the branches \u00b6 In order to determine the flow area of the 1D model during the computation, you need cross-sections. These cross-sections are defined by two components: Cross-section locations Cross-section definitions The cross-section locations and cross-section definitions are exported to their own file. A cross-section location is defined by the following information: The cross-section ID A location, specified by a branch ID and a chainage. A shift, the vertical shift of the cross section profile. This is mainly used to create a good longitudinal slope over the 1D model (in case of shared cross-sections). A reference to the cross-section definition that is used at this location.

    A cross-section definition is defined by the following information: The cross-section definition ID The cross-section type: circle, rectangle, ZW river, ZW, YZ, XYZ Depending on the type of cross-section, a set of properties describing the properties of the profile shape

    In our data folder, there is a CSV file containing the cross-section locations. We want to convert this data to HYDROLIB-core cross-section location objects and add them to the D-Flow FM model. The columns in the CSV correspond exactly with the field names of a CrossSection class, making the conversion easy. Exercise \ud83e\udde9 Read the data from the CSV file Print the cross-section location data, to answer the following questions: How many cross-section does the model contain in total, and how many does each branch have? Do the cross-section have shared cross-section definitions? A shared cross-section definition is a definition used by more than one cross-section. Convert the CSV data (a pd.DataFrame) into HYDROLIB-core CrossSection objects Assign the cross section locations to the model Hint \ud83d\udca1: The MDU file contains a [Geometry] section which has the crossDefFile and crossLocFile reference, e.g.: [Geometry] crossDefFile = crsdef.ini crossLocFile = crsloc.ini ... API references: pd.read_csv() pd.to_dict() CrossLocModel CrossSection In [ ]: Copied! # Read the cross-sections from the CSV cross_section_data_file = data_dir / 'cross_section_locations.csv' cross_section_df = pd . read_csv ( cross_section_data_file , index_col = False ) # Print the data print ( cross_section_df ) # Answers: # * There are 6 cross-sections in the model and each branch has two cross-sections # * There are no shared cross-section definitions; each cross-section has a unique definition ID. # Assign the data to the model cross_loc_model = CrossLocModel () model . geometry . crosslocfile = cross_loc_model cross_loc_model . crosssection = cross_section_df . to_dict ( \"records\" ) # Read the cross-sections from the CSV cross_section_data_file = data_dir / 'cross_section_locations.csv' cross_section_df = pd.read_csv(cross_section_data_file, index_col=False) # Print the data print(cross_section_df) # Answers: # * There are 6 cross-sections in the model and each branch has two cross-sections # * There are no shared cross-section definitions; each cross-section has a unique definition ID. # Assign the data to the model cross_loc_model = CrossLocModel() model.geometry.crosslocfile = cross_loc_model cross_loc_model.crosssection = cross_section_df.to_dict(\"records\") 6. Adding cross-section definitions \u00b6 In the following exercise we will add the cross-section definitions to the D-Flow FM model. These belong to the cross-sections we added in the previous step. These cross-sections all have YZ-profiles in order to define a natural shape of the river. Please finish the code below. Exercise \ud83e\udde9 Create a new cross-section definition model with the defined properties Create an YZ profile for each profile from the excel file Append each YZ profile to the cross-section definition model Make sure the data is assigned to the D-Flow FM model API references: CrossDefModel YZCrsDef In [ ]: Copied! profiles_file = data_dir / '1D_YZ_CrossSections.xlsx' profile_excel_data = pd . read_excel ( profiles_file , sheet_name = None ) profile_names = list ( profile_excel_data ) print ( f \"Profile names: { profile_names } \" ) # Create a new cross-section definition model and assign to the model cross_def_model = CrossDefModel () model . geometry . crossdeffile = cross_def_model # Properties for each YZ profile type_crs = 'yz' thalweg = 0.0 single_valued_z = 'yes' conveyance = 'segmented' sectionCount = 1 friction_ids = 'channels' # Create the YZ profiles and append them to the CrossDefModel for profile_name in profile_names : profile_data = profile_excel_data [ profile_name ] num_coords = len ( profile_data . values ) y_coords = profile_data . y . to_list () z_coords = profile_data . z . to_list () # Define friction positions at begin and end of profile friction_positions = [ profile_data . y [ 0 ], profile_data . y [ num_coords - 1 ]] # Create an YZ profile and add it to the cross-section definition model cross_section = YZCrsDef ( id = profile_name , type = type_crs , thalweg = thalweg , singleValuedZ = single_valued_z , conveyance = conveyance , yzCount = num_coords , yCoordinates = y_coords , zCoordinates = z_coords , sectionCount = sectionCount , frictionIds = friction_ids , frictionPositions = friction_positions ) cross_def_model . definition . append ( cross_section ) profiles_file = data_dir / '1D_YZ_CrossSections.xlsx' profile_excel_data = pd.read_excel(profiles_file, sheet_name=None) profile_names = list(profile_excel_data) print(f\"Profile names: {profile_names}\") # Create a new cross-section definition model and assign to the model cross_def_model = CrossDefModel() model.geometry.crossdeffile = cross_def_model # Properties for each YZ profile type_crs = 'yz' thalweg = 0.0 single_valued_z = 'yes' conveyance = 'segmented' sectionCount = 1 friction_ids = 'channels' # Create the YZ profiles and append them to the CrossDefModel for profile_name in profile_names: profile_data = profile_excel_data[profile_name] num_coords = len(profile_data.values) y_coords = profile_data.y.to_list() z_coords = profile_data.z.to_list() # Define friction positions at begin and end of profile friction_positions = [profile_data.y[0], profile_data.y[num_coords-1]] # Create an YZ profile and add it to the cross-section definition model cross_section = YZCrsDef(id=profile_name, type=type_crs, thalweg=thalweg, singleValuedZ=single_valued_z, conveyance=conveyance, yzCount=num_coords, yCoordinates=y_coords, zCoordinates = z_coords, sectionCount = sectionCount, frictionIds = friction_ids, frictionPositions=friction_positions) cross_def_model.definition.append(cross_section) 7. Adding roughness to the model \u00b6 Our 1D D-Flow FM model now has a network topology, computational grid points and cross-sections. Friction is a component that should be added to the model to get the proper bed roughness and channel conveyance. For each branch, we will add a friction type and value at the upstream location. We will also specify a global roughness section. This will be used when there is no friction defined for a branch. It also contains a friction ID. In the cross-section definitions we created above, a reference is made to this friction ID (='channels'). YZ profiles can refer to multiple friction IDs, since the friction can vary within the cross-section. This also means that multiple friction definition files can be added to one D-Flow FM model. In [ ]: Copied! channel_friction_id = 'channels' channel_global_type = FrictionType . manning channel_global_value = 0.023 channel_friction_model = FrictionModel () channel_friction_model . filepath = \"roughness-channels.ini\" # It is conventional to specify the file names as \"roughness-[friction ID].ini\" model . geometry . frictfile = [ channel_friction_model ] # Create global friction model and add it to frictionmodel channel_global_friction = FrictGlobal ( frictionId = channel_friction_id , frictionType = channel_global_type , frictionValue = channel_global_value ) channel_friction_model . global_ = channel_global_friction function_type = 'constant' # Create friction definition per branch for index , branch_data in branches_gdf . iterrows (): friction_per_branch = FrictBranch ( branchId = branch_data . Name , frictionType = branch_data . fric_type , frictionValues = [ branch_data . fric_value ], chainage = [ branch_data . chainage ], numLocations = 1 , functionType = function_type ) channel_friction_model . branch . append ( friction_per_branch ) channel_friction_id = 'channels' channel_global_type = FrictionType.manning channel_global_value = 0.023 channel_friction_model = FrictionModel() channel_friction_model.filepath = \"roughness-channels.ini\" # It is conventional to specify the file names as \"roughness-[friction ID].ini\" model.geometry.frictfile = [channel_friction_model] # Create global friction model and add it to frictionmodel channel_global_friction = FrictGlobal(frictionId=channel_friction_id, frictionType=channel_global_type, frictionValue=channel_global_value) channel_friction_model.global_ = channel_global_friction function_type = 'constant' # Create friction definition per branch for index, branch_data in branches_gdf.iterrows(): friction_per_branch = FrictBranch(branchId=branch_data.Name, frictionType=branch_data.fric_type, frictionValues=[branch_data.fric_value], chainage=[branch_data.chainage], numLocations=1, functionType=function_type) channel_friction_model.branch.append(friction_per_branch) We want to define another global friction definition for the Canal del Dique. This friction model assumes Chezy as global friction type and a friction value of 45.0. You can use the code above as an example. Exercise \ud83e\udde9 Create a new friction model for Canal del Dique Specify a global friction definition Make sure the new friction model is added to the D-Flow FM model API references: FrictionType FrictionModel FrictGlobal In [ ]: Copied! dique_friction_id = 'dique' dique_global_type = FrictionType . chezy dique_global_value = 45.0 dique_friction_model = FrictionModel () dique_friction_model . filepath = 'roughness-dique.ini' model . geometry . frictfile . append ( dique_friction_model ) dique_global_friction = FrictGlobal ( frictionId = dique_friction_id , frictionType = dique_global_type , frictionValue = dique_global_value ) dique_friction_model . global_ = dique_global_friction dique_friction_id = 'dique' dique_global_type = FrictionType.chezy dique_global_value = 45.0 dique_friction_model = FrictionModel() dique_friction_model.filepath = 'roughness-dique.ini' model.geometry.frictfile.append(dique_friction_model) dique_global_friction = FrictGlobal(frictionId=dique_friction_id, frictionType=dique_global_type, frictionValue=dique_global_value) dique_friction_model.global_ = dique_global_friction The cross-sections on the Canal del Dique (Channel_1D_1) do not refer to this new friction ID yet. Exercise \ud83e\udde9 Use the cross-section locations and definitions in the D-Flow FM model to find the cross-sections on the Channel_1D_1 branch Reassign the friction ID of the correct cross sections to the one used for the Canal del Dique In [ ]: Copied! cross_section_definitions = model . geometry . crossdeffile . definition cross_section_locations = model . geometry . crosslocfile . crosssection # Create a dictionary with the definition IDs, for easily finding the correct definition definition_dict = { definition . id : definition for definition in cross_section_definitions } for cross_section in cross_section_locations : if cross_section . branchid == \"Channel_1D_1\" : cross_section_definition = definition_dict [ cross_section . definitionid ] cross_section_definition . frictionids = [ dique_friction_id ] cross_section_definitions = model.geometry.crossdeffile.definition cross_section_locations = model.geometry.crosslocfile.crosssection # Create a dictionary with the definition IDs, for easily finding the correct definition definition_dict = {definition.id: definition for definition in cross_section_definitions} for cross_section in cross_section_locations: if cross_section.branchid == \"Channel_1D_1\": cross_section_definition = definition_dict[cross_section.definitionid] cross_section_definition.frictionids = [dique_friction_id] 8. Adding boundary conditions to the model \u00b6 Fluvial floods occur when water levels in the river are too high. These high water levels in the rivers can result from several factors. One of those is the occurence of heavy rainfall in the upstream catchment. These heavy rainstorms can lead to a high discharge wave entering the upstream boundary of the river. In order to apply boundary conditions on a model you need data from two files: External forcing file (*.ext) : specifies the location and type of forcing. Boundary conditions file (*.bc) : contains the forcing values, e.g. a time series or a constant value In this tutorial you will model such a high discharge wave (time series) at the upstream 1D boundary. For the two downstream boundaries a constant water level of 0 m AD is assumed. Note that this are tidal boundaries in reality. Exercise \ud83e\udde9 Complete the code below by adding the boundary locations to the external forcing model. For each boundary location (3), the correct boundary object should be created with a quantity, node ID and forcing file. The quantity keys for discharge and water level are 'dischargebnd' and 'waterlevelbnd', respectively. API references: Boundary In [ ]: Copied! ext_model = ExtModel () # External forcing file (.ext) bc_model = ForcingModel () # Boundary conditions file (.bc) model . external_forcing . extforcefilenew = ext_model # Read the upstream boundary time series from excel discharge_file = data_dir / '1D_BoundaryConditions.xlsx' discharge_excel_df = pd . read_excel ( discharge_file , sheet_name = [ 0 ]) node_ids = model . geometry . netfile . network . _mesh1d . network1d_node_id print ( node_ids ) node_upstream = node_ids [ 0 ] # time series discharge node nodes_downstream = node_ids [ 2 :] # constant water level nodes # Create the discharge timeseries bc_upstream = TimeSeries ( name = node_upstream , nodeid = node_upstream , timeinterpolation = TimeInterpolation . linear , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2012-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], datablock = [[ time , dis ] for [ time , dis ] in discharge_excel_df [ 0 ] . values ]) bc_model . forcing . append ( bc_upstream ) # Create the constant water level for node_downstream in nodes_downstream : bc_downstream = Constant ( name = node_downstream , nodeid = node_downstream , quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], datablock = [[ \"0.0\" ]]) bc_model . forcing . append ( bc_downstream ) # Create the boundary locations for the discharge and the water level ext_upstream = Boundary ( quantity = 'dischargebnd' , nodeid = node_upstream , forcingfile = bc_model ) ext_model . boundary . append ( ext_upstream ) for node_downstream in nodes_downstream : ext_downstream = Boundary ( quantity = 'waterlevelbnd' , nodeid = node_downstream , forcingfile = bc_model ) ext_model . boundary . append ( ext_downstream ) ext_model = ExtModel() # External forcing file (.ext) bc_model = ForcingModel() # Boundary conditions file (.bc) model.external_forcing.extforcefilenew = ext_model # Read the upstream boundary time series from excel discharge_file = data_dir / '1D_BoundaryConditions.xlsx' discharge_excel_df = pd.read_excel(discharge_file, sheet_name=[0]) node_ids = model.geometry.netfile.network._mesh1d.network1d_node_id print(node_ids) node_upstream = node_ids[0] # time series discharge node nodes_downstream = node_ids[2:] # constant water level nodes # Create the discharge timeseries bc_upstream = TimeSeries( name = node_upstream, nodeid = node_upstream, timeinterpolation = TimeInterpolation.linear, quantityunitpair = [QuantityUnitPair(quantity = 'time', unit = 'minutes since 2012-01-01 00:00:00'), QuantityUnitPair(quantity = 'dischargebnd', unit = 'm\u00b3/s')], datablock = [[time, dis] for [time,dis] in discharge_excel_df[0].values]) bc_model.forcing.append(bc_upstream) # Create the constant water level for node_downstream in nodes_downstream: bc_downstream = Constant( name = node_downstream, nodeid = node_downstream, quantityunitpair = [QuantityUnitPair(quantity = 'waterlevelbnd', unit = 'm')], datablock = [[\"0.0\"]]) bc_model.forcing.append(bc_downstream) # Create the boundary locations for the discharge and the water level ext_upstream = Boundary( quantity = 'dischargebnd', nodeid = node_upstream, forcingfile = bc_model) ext_model.boundary.append(ext_upstream) for node_downstream in nodes_downstream: ext_downstream = Boundary( quantity = 'waterlevelbnd', nodeid = node_downstream, forcingfile = bc_model ) ext_model.boundary.append(ext_downstream) 9. Adding initial water depths \u00b6 For this model an initial water depth of 1.0 meter is assumed in the 1D model. Below we add an initial water depth to the model with the following steps: Creating global 1D initial conditions field, containing an initial water depth of 1.0. Note that it is also possible to define the initial water depth per branch. Creating an initial field file containing the initial water depth data for our 1D network In [ ]: Copied! # Create 1D initial conditions field file ini_1d = OneDFieldModel () ini_1d . global_ = OneDFieldGlobal ( quantity = 'waterdepth' , unit = 'm' , value = 1.0 ) ini_1d . filepath = 'initialwaterdepth.ini' ini_1d . save ( export_dir / ini_1d . filepath ) # 1D field ini files needs to be saved seperately, because it is not completely supported yet) # Create initial field file ini_field_model = IniFieldModel () ini_field_model . filepath = 'inifield.ini' ini_field_model . initial = InitialField ( quantity = 'waterdepth' , datafile = ini_1d . filepath , datafiletype = DataFileType . onedfield ) # Assign data to the model model . geometry . inifieldfile = ini_field_model # Create 1D initial conditions field file ini_1d = OneDFieldModel() ini_1d.global_ = OneDFieldGlobal(quantity='waterdepth', unit='m', value=1.0) ini_1d.filepath = 'initialwaterdepth.ini' ini_1d.save(export_dir / ini_1d.filepath) # 1D field ini files needs to be saved seperately, because it is not completely supported yet) # Create initial field file ini_field_model = IniFieldModel() ini_field_model.filepath = 'inifield.ini' ini_field_model.initial = InitialField(quantity='waterdepth',datafile=ini_1d.filepath, datafiletype=DataFileType.onedfield) # Assign data to the model model.geometry.inifieldfile = ini_field_model 10. Adding a weir to a branch \u00b6 Many lakes occur close along Canal del Dique. See figure below. This tutorial assumes that these lakes can function as extra storage for the floods from the river. Hence a weir structure, functioning as a small dam, is added downstream of the lakes. This weir structure has the following conditions: It is located at 70 km from the upstream node of the branch (Channel_1D_1). The crest level is 4.0 m AD. The crest width is 105.0 m. The flow over the dam is in both directions.

    Exercise \ud83e\udde9 Create a new weir object with the described properties Create a new structure model and add the new weir to it Assign the data to the D-Flow FM model In [ ]: Copied! # Create weir structure weir = Weir ( id = 'fictive_dam' , name = 'fictive_dam' , branchId = 'Channel_1D_1' , chainage = 70000.0 , allowedFlowDir = FlowDirection . both , crestLevel = 4.0 , crestWidth = 105.0 , corrCoeff = 1.000 , useVelocityHeight = True ) # Create structure model structure_model = StructureModel () structure_model . filepath = 'structure.ini' # Append weir to structure structure_model . structure . append ( weir ) # Assign structure model to D-Flow FM model model . geometry . structurefile = [ structure_model ] # Create weir structure weir = Weir( id='fictive_dam', name = 'fictive_dam', branchId='Channel_1D_1', chainage=70000.0, allowedFlowDir=FlowDirection.both, crestLevel=4.0, crestWidth=105.0, corrCoeff=1.000, useVelocityHeight=True ) # Create structure model structure_model = StructureModel() structure_model.filepath = 'structure.ini' # Append weir to structure structure_model.structure.append(weir) # Assign structure model to D-Flow FM model model.geometry.structurefile = [structure_model] After creating the weir, you want to adjust some values. You found out that the dam should be significantly higher. Exercise \ud83e\udde9 Increase the crest level to 10.0 Change the flow direction to positive (from upstream to downstream) In [ ]: Copied! weir . crestlevel = 10.0 weir . allowedflowdir = FlowDirection . positive weir.crestlevel = 10.0 weir.allowedflowdir = FlowDirection.positive 11. Finishing up and saving the model \u00b6 The 1D model is almost finished now. We first change some time settings and then save the model. Exercise \ud83e\udde9 Export the full model to the export folder API references: FileModel.save() In [ ]: Copied! # Change some time settings model . time . refdate = '20120101' model . time . dtuser = 60. # seconds model . time . tstart = 43200. model . time . tstop = 561600. # Save the model model . save ( recurse = True ) # Change some time settings model.time.refdate = '20120101' model.time.dtuser = 60. # seconds model.time.tstart = 43200. model.time.tstop = 561600. # Save the model model.save(recurse=True) Part 2: Extending the 1D model to a 1D2D model \u00b6 We will now continue with the 1D model and add a 2D mesh to it. We won't add 1D2D coupling, but in practice they should be added to create a true 1D2D model. 12. Creating a 2D flexible mesh \u00b6 Here, we demonstrate how to create a 2D mesh using MeshKernel. \u26a0\ufe0f Network and mesh functionality in HYDROLIB-core is still in development. We use a shape file with the area of interest to define the extent of the new 2D mesh that is to be generated. First, a uniform rectilinear mesh with a grid cell size of 2500x2500m is generated. Second, we clip the generated mesh. API references: Mesh2d Mesh2d.clip() mk.MakeGridParameters In [ ]: Copied! # Read grid outline gdf_grid = gpd . read_file ( data_dir / 'outline_2D_grid.shp' ) # Determine the boundary box xmin , ymin , xmax , ymax = gdf_grid . geometry [ 0 ] . bounds mesh2d = Mesh2d () mesh_kernel = mesh2d . meshkernel # Define the grid generation parameters dx = 2500.0 dy = 2500.0 num_rows = int (( ymax - ymin ) / dy ) num_columns = int (( xmax - xmin ) / dx ) origin_x = xmin origin_y = ymin block_size_x = dx block_size_y = dy make_grid_parameters = MakeGridParameters () make_grid_parameters . num_columns = num_columns make_grid_parameters . num_rows = num_rows make_grid_parameters . origin_x = origin_x make_grid_parameters . origin_y = origin_y make_grid_parameters . block_size_x = dx make_grid_parameters . block_size_y = dy make_grid_parameters . upper_right_x = xmax make_grid_parameters . upper_right_y = ymax # Create uniform rectilinear mesh mesh_kernel . curvilinear_make_uniform ( make_grid_parameters ) mesh_kernel . curvilinear_convert_to_mesh2d () mesh2d . _process ( mesh2d . get_mesh2d ()) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np . array ( gdf_grid . geometry [ 0 ] . exterior . xy ) clip_geometry_list = GeometryList ( clip_polygon [ 0 ], clip_polygon [ 1 ]) mesh2d . clip ( clip_geometry_list ) model . geometry . netfile . network . _mesh2d = mesh2d model . geometry . netfile . filepath = \"FlowFM_1D2D_net.nc\" # Read grid outline gdf_grid = gpd.read_file(data_dir / 'outline_2D_grid.shp') # Determine the boundary box xmin, ymin, xmax, ymax = gdf_grid.geometry[0].bounds mesh2d = Mesh2d() mesh_kernel = mesh2d.meshkernel # Define the grid generation parameters dx=2500.0 dy=2500.0 num_rows = int((ymax - ymin) / dy) num_columns = int((xmax - xmin) / dx) origin_x = xmin origin_y = ymin block_size_x = dx block_size_y = dy make_grid_parameters = MakeGridParameters() make_grid_parameters.num_columns = num_columns make_grid_parameters.num_rows = num_rows make_grid_parameters.origin_x = origin_x make_grid_parameters.origin_y = origin_y make_grid_parameters.block_size_x = dx make_grid_parameters.block_size_y = dy make_grid_parameters.upper_right_x = xmax make_grid_parameters.upper_right_y = ymax # Create uniform rectilinear mesh mesh_kernel.curvilinear_make_uniform(make_grid_parameters) mesh_kernel.curvilinear_convert_to_mesh2d() mesh2d._process(mesh2d.get_mesh2d()) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np.array(gdf_grid.geometry[0].exterior.xy) clip_geometry_list = GeometryList(clip_polygon[0],clip_polygon[1]) mesh2d.clip(clip_geometry_list) model.geometry.netfile.network._mesh2d = mesh2d model.geometry.netfile.filepath = \"FlowFM_1D2D_net.nc\" The cell below produces a basic plot of the 1D2D network. In [ ]: Copied! # Create a plot mesh2d_mk = network . _mesh2d . get_mesh2d () mesh1d_mk = network . _mesh1d . _get_mesh1d () figure , axis = plt . subplots () axis . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) mesh2d_mk . plot_edges ( ax = axis , color = \"orange\" ) mesh1d_mk . plot_edges ( ax = axis , color = 'blue' ) # Create a plot mesh2d_mk = network._mesh2d.get_mesh2d() mesh1d_mk = network._mesh1d._get_mesh1d() figure, axis = plt.subplots() axis.imshow(img, extent=[440000, 531544.97964175534434617, 1057000, 1228644.01383191486820579]) mesh2d_mk.plot_edges(ax=axis, color=\"orange\") mesh1d_mk.plot_edges(ax=axis, color='blue') 13. Refining the 2D grid locally \u00b6 Here, we want to refine the 2D mesh around the river using MeshKernel functionality. We will do one refinement iteration. Exercise \ud83e\udde9 Refine the 2D mesh using MeshKernel with the provided refinment parameters (see code below) API references: mk.MeshRefinementParameters mk.mesh2d_refine_based_on_polygon() (not documented yet): First argument is a GeometryList containing the polygon geometry of the area to refine Second argument is a MeshRefinementParameters containing all the parameters for refining In [ ]: Copied! # Get the refinement polygon to refine around the river gdf_refine = gpd . read_file ( data_dir / 'buffer_around_river_proj.shp' ) refine_polygon = np . array ( gdf_refine . geometry [ 0 ] . exterior . xy ) refine_geom = GeometryList ( refine_polygon [ 0 ], refine_polygon [ 1 ]) # Set parameters refine_intersected = True use_mass_center_when_refining = False min_edge_size = 10.0 refinement_type = 1 connect_hanging_nodes = True account_for_samples_outside_face = False max_refinement_iterations = 1 # Refine the 2D mesh parameters = mk . MeshRefinementParameters ( refine_intersected = refine_intersected , use_mass_center_when_refining = use_mass_center_when_refining , min_edge_size = min_edge_size , refinement_type = refinement_type , connect_hanging_nodes = connect_hanging_nodes , account_for_samples_outside_face = account_for_samples_outside_face , max_refinement_iterations = max_refinement_iterations , ) mesh_kernel . mesh2d_refine_based_on_polygon ( refine_geom , parameters ) # Set 2D mesh on model mesh2d . _process ( mesh2d . get_mesh2d ()) model . geometry . netfile . network . _mesh2d = mesh2d model . geometry . netfile . filepath = \"FlowFM_1D2D_refined_net.nc\" # Get the refinement polygon to refine around the river gdf_refine = gpd.read_file(data_dir / 'buffer_around_river_proj.shp') refine_polygon = np.array(gdf_refine.geometry[0].exterior.xy) refine_geom = GeometryList(refine_polygon[0], refine_polygon[1]) # Set parameters refine_intersected = True use_mass_center_when_refining = False min_edge_size = 10.0 refinement_type = 1 connect_hanging_nodes = True account_for_samples_outside_face = False max_refinement_iterations = 1 # Refine the 2D mesh parameters = mk.MeshRefinementParameters( refine_intersected=refine_intersected, use_mass_center_when_refining=use_mass_center_when_refining, min_edge_size=min_edge_size, refinement_type=refinement_type, connect_hanging_nodes=connect_hanging_nodes, account_for_samples_outside_face=account_for_samples_outside_face, max_refinement_iterations=max_refinement_iterations, ) mesh_kernel.mesh2d_refine_based_on_polygon(refine_geom, parameters) # Set 2D mesh on model mesh2d._process(mesh2d.get_mesh2d()) model.geometry.netfile.network._mesh2d = mesh2d model.geometry.netfile.filepath = \"FlowFM_1D2D_refined_net.nc\" In [ ]: Copied! # Create a plot mesh2d_mk = network . _mesh2d . get_mesh2d () mesh1d_mk = network . _mesh1d . _get_mesh1d () figure , axis = plt . subplots () axis . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) mesh2d_mk . plot_edges ( ax = axis , color = \"orange\" ) mesh1d_mk . plot_edges ( ax = axis , color = 'blue' ) # Create a plot mesh2d_mk = network._mesh2d.get_mesh2d() mesh1d_mk = network._mesh1d._get_mesh1d() figure, axis = plt.subplots() axis.imshow(img, extent=[440000, 531544.97964175534434617, 1057000, 1228644.01383191486820579]) mesh2d_mk.plot_edges(ax=axis, color=\"orange\") mesh1d_mk.plot_edges(ax=axis, color='blue') 14. Saving the 1D2D model \u00b6 The 1D2D model is now finished. Exercise \ud83e\udde9 Save the model wherever you like Import the D-Flow FM model in the Delft3D FM Suite 1D2D In [ ]: Copied! model . save ( recurse = True ) model.save(recurse=True)","title":"Creating a Delft3D FM 1D2D fluvial flood model of Magdalena river"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#creating-a-delft3d-fm-1d2d-fluvial-flood-model-of-magdalena-river","text":"The exercises in this notebook will serve as introduction on how to use HYDROLIB-core functionalities. We will create and adjust a Delft3D FM Suite 1D2D fluvial flood model of the Magdalena river in Columbia. First a 1D river model of the Magdalena river and Canal del Dique will be created, shown in the left figure. This model will be extended with a 2D Flexible Mesh, with a uniform roughness field. Adding a Digital Terrain Model (DTM) on that 2D mesh is currently not part of this tutorial, but in practice this is indispensible to mimic the fluvial flood patterns. Note that the model that will be created is for educational purposes and consists partially of fictive or unvalidated model data.","title":"Creating a Delft3D FM 1D2D fluvial flood model of Magdalena river"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#using-hydrolib-core-to-build-models","text":"HYDROLIB-core is a Python package that offers functionality to process D-HYDRO input files. It offers Python-wrapped classes that represent these files and their content. HYDROLIB-core serves as the basis for various pre- and postprocessing tools for a modelling workflow of hydrodynamic simulations in D-HYDRO. It can easily be used to build models and export the model files that can aftewards be run by dflowfm or other supported D-HYDRO kernels.","title":"Using HYDROLIB-core to build models"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#content-of-the-tutorial","text":"The goal of this tutorial is to familiarize modelers with applying HYDROLIB-core functionalities in their modelling procedures for building new models or adjusting existing models. As mentioned above, you will create an 1D2D fluvial flood model from scratch using the D-Flow FM HYDROLIB-core functionalities and the underlying functions from mesh generation ( MeshKernelPy ). We will walk through the following steps to build the model: Selecting the data location Creating an empty D-Flow FM model Reading the branch data from a shape file Creating and assigning a 1D computational grid to the model Adding cross-sections to the branches Adding cross-section definitions Adding roughness to the model Adding boundary conditions to the model Adding initial water depths Adding a weir to a branch Finishing up and saving the model Creating a 2D flexible mesh Refining the 2D grid locally Saving the 1D2D model","title":"Content of the tutorial"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#tips-for-working-in-the-jupyter-notebook","text":"Tab : Auto-complete on code Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell","title":"\ud83d\udca1 Tips for working in the Jupyter Notebook"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#import-the-needed-modules","text":"Several Python packages are required to run the notebook. These packages are imported below. Please consult the HYDROLIB-core documentation if you want to use additional HYDROLIB-core functionalities later. In [ ]: Copied! # General import geopandas as gpd import matplotlib.pyplot as plt import numpy as np import pandas as pd from pathlib import Path # MeshKernel import meshkernel as mk from meshkernel import GeometryList , MakeGridParameters # HYDROLIB-core from hydrolib.core.dflowfm.mdu import FMModel , AutoStartOption from hydrolib.core.dflowfm.net.models import * from hydrolib.core.dflowfm.crosssection.models import CrossLocModel , CrossDefModel , YZCrsDef from hydrolib.core.dflowfm.friction.models import * from hydrolib.core.dflowfm.bc.models import * from hydrolib.core.dflowfm.ext.models import * from hydrolib.core.dflowfm.inifield.models import * from hydrolib.core.dflowfm.onedfield.models import * from hydrolib.core.dflowfm.structure.models import Weir , FlowDirection , StructureModel print ( \"Imports were successful!\" ) # General import geopandas as gpd import matplotlib.pyplot as plt import numpy as np import pandas as pd from pathlib import Path # MeshKernel import meshkernel as mk from meshkernel import GeometryList, MakeGridParameters # HYDROLIB-core from hydrolib.core.dflowfm.mdu import FMModel, AutoStartOption from hydrolib.core.dflowfm.net.models import * from hydrolib.core.dflowfm.crosssection.models import CrossLocModel, CrossDefModel, YZCrsDef from hydrolib.core.dflowfm.friction.models import * from hydrolib.core.dflowfm.bc.models import * from hydrolib.core.dflowfm.ext.models import * from hydrolib.core.dflowfm.inifield.models import * from hydrolib.core.dflowfm.onedfield.models import * from hydrolib.core.dflowfm.structure.models import Weir, FlowDirection, StructureModel print(\"Imports were successful!\")","title":"Import the needed modules"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#here-starts-the-tutorial","text":"","title":"Here starts the tutorial"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#1-selecting-the-data-location","text":"Exercise \ud83e\udde9: Create a variable that contains the Path to the data folder. In [ ]: Copied! root = Path . cwd () data_dir = root / 'data' print ( f \"Data location: { data_dir } \" ) root = Path.cwd() data_dir = root / 'data' print(f\"Data location: {data_dir}\")","title":"1. Selecting the data location"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#2-creating-an-empty-d-flow-fm-model","text":"To start a model from scratch, you first need to create an empty model without data. In this tutorial we will create a D-Flow FM model. The MDU file (master definition file) is the main input file of the D-Flow FM model. A new D-Flow FM model is constructed with the FMModel initializer. Exercise \ud83e\udde9 Create a variable containing a new FMModel object. Create a variable containing the export directory Export the D-Flow FM model to an MDU file inside the export directory API references: FMModel FileModel.filepath FileModel.save() In [ ]: Copied! model = FMModel () export_dir = root / 'export' model . filepath = export_dir / 'Magdalena_1D.mdu' # Save the MDU file model . save () print ( f \"MDU file saved: { model . filepath } \" ) model = FMModel() export_dir = root / 'export' model.filepath = export_dir / 'Magdalena_1D.mdu' # Save the MDU file model.save() print(f\"MDU file saved: {model.filepath}\")","title":"2. Creating an empty D-Flow FM model"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#part-1-setting-up-a-1d-delft3d-fm-model","text":"In this part we will build up the complete 1D model schematization step by step. At the end you should have a complete set of model input files for a 1D calculation.","title":"Part 1: Setting up a 1D Delft3D FM model"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#3-reading-the-branch-data-from-a-shape-file","text":"The model will include the lower part of the Magadalena from Cordoba Teton to the river mouth Baranquilla and the Canal del Dique. Exercise \ud83e\udde9 Read the branch data from the branches_Branches.shp file Print the branch data, such that we can answer the following questions: How many river branches does the model have? What are their names? Which friction type and friction value is used for each branch? API references: gpd.read_file In [ ]: Copied! # Read the branches branch_shp_file = data_dir / 'branches_Branches.shp' branches_gdf = gpd . read_file ( filename = branch_shp_file ) # Print the data print ( branches_gdf ) # Answers: # * 3 branches # * Channel_1D_1_A, Channel_1D_1_B and Channel_1D_1 # * Channel_1D_1_A: Manning, 0.03 # Channel_1D_1_B: Manning, 0.02 # Channel_1D_1 : Manning, 0.02 # Read the branches branch_shp_file = data_dir / 'branches_Branches.shp' branches_gdf = gpd.read_file(filename = branch_shp_file) # Print the data print(branches_gdf) # Answers: # * 3 branches # * Channel_1D_1_A, Channel_1D_1_B and Channel_1D_1 # * Channel_1D_1_A: Manning, 0.03 # Channel_1D_1_B: Manning, 0.02 # Channel_1D_1 : Manning, 0.02","title":"3. Reading the branch data from a shape file"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#4-creating-and-assigning-a-1d-computational-grid-to-the-model","text":"In the previous step we read the geometry and attributes of the branches from the shape file. This branch data will become the network input for our D-Flow FM model. Since the model does not have a network yet, we need to create a new network object and assign it to the model. A network may contain a 1D network, a 2D mesh and 1D2D links. Exercise \ud83e\udde9 Create a new network Assign the network to the model and assign a (relative) file path for the net file The new network should contain the data that we read from the shape file: Three Branch objects will need to be added to the network. For each branch, the name, geometry and computational grid points should be provided. The computational points are not included in the data, we will need to generate those with a grid point distance as specified: Branch name dx [m] Channel_1D_1_A 1000 Channel_1D_1_B 1000 Channel_1D_1 500 Hint \ud83d\udca1: The MDU file contains a [Geometry] section which has the network file reference, e.g.: [Geometry] netFile = FlowFM_net.nc ... API references: Network NetworkModel Branch Branch.generate_nodes() Network.mesh1d_add_branch() (undocumented): Adds a branch to the 1D network. The function needs two arguments: Branch : the branch to be added str : The name of the branch that is added In [ ]: Copied! # Assign a new network to the D-Flow FM model and specify the file path network = Network () model . geometry . netfile . network = network model . geometry . netfile . filepath = \"FlowFM_net.nc\" # Specify 1D computational grid point distance per branch dx_per_branch = { \"Channel_1D_1_A\" : 1000 , \"Channel_1D_1_B\" : 1000 , \"Channel_1D_1\" : 500 , } # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch_data in branches_gdf . iterrows (): branch_geometry = np . transpose ( branch_data . geometry . xy ) branch = Branch ( geometry = branch_geometry ) branch . generate_nodes ( mesh1d_edge_length = dx_per_branch [ branch_data . Name ]) network . mesh1d_add_branch ( branch , name = branch_data . Name ) network . _mesh1d . _set_mesh1d () # Assign a new network to the D-Flow FM model and specify the file path network = Network() model.geometry.netfile.network = network model.geometry.netfile.filepath = \"FlowFM_net.nc\" # Specify 1D computational grid point distance per branch dx_per_branch = { \"Channel_1D_1_A\" : 1000, \"Channel_1D_1_B\" : 1000, \"Channel_1D_1\" : 500, } # Assign geometry of the branches and generate the computational grid on top of the branches. for index, branch_data in branches_gdf.iterrows(): branch_geometry = np.transpose(branch_data.geometry.xy) branch = Branch(geometry=branch_geometry) branch.generate_nodes(mesh1d_edge_length=dx_per_branch[branch_data.Name]) network.mesh1d_add_branch(branch, name=branch_data.Name) network._mesh1d._set_mesh1d() We can plot the branches onto a background: In [ ]: Copied! # Create a figure with the 1D network figure , axis = plt . subplots ( ncols = 1 ) img = plt . imread ( data_dir / \"osm_background.png\" ) # Add branch names to the plot for branch_name , branch in network . _mesh1d . branches . items (): middle = int (( len ( branch . geometry ) - 1 ) / 2 ) xy = branch . geometry [ middle ] axis . text ( xy [ 0 ], xy [ 1 ], branch_name , ha = 'center' ) axis . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) network . _mesh1d . _get_mesh1d () . plot_edges ( ax = axis , color = 'blue' ) # Create a figure with the 1D network figure, axis = plt.subplots(ncols=1) img = plt.imread(data_dir / \"osm_background.png\") # Add branch names to the plot for branch_name, branch in network._mesh1d.branches.items(): middle = int((len(branch.geometry) - 1)/2) xy = branch.geometry[middle] axis.text(xy[0], xy[1], branch_name, ha='center') axis.imshow(img, extent=[440000, 531544.97964175534434617, 1057000, 1228644.01383191486820579]) network._mesh1d._get_mesh1d().plot_edges(ax=axis, color='blue')","title":"4. Creating and assigning a 1D computational grid to the model"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#5-adding-cross-sections-to-the-branches","text":"In order to determine the flow area of the 1D model during the computation, you need cross-sections. These cross-sections are defined by two components: Cross-section locations Cross-section definitions The cross-section locations and cross-section definitions are exported to their own file. A cross-section location is defined by the following information: The cross-section ID A location, specified by a branch ID and a chainage. A shift, the vertical shift of the cross section profile. This is mainly used to create a good longitudinal slope over the 1D model (in case of shared cross-sections). A reference to the cross-section definition that is used at this location.

    A cross-section definition is defined by the following information: The cross-section definition ID The cross-section type: circle, rectangle, ZW river, ZW, YZ, XYZ Depending on the type of cross-section, a set of properties describing the properties of the profile shape

    In our data folder, there is a CSV file containing the cross-section locations. We want to convert this data to HYDROLIB-core cross-section location objects and add them to the D-Flow FM model. The columns in the CSV correspond exactly with the field names of a CrossSection class, making the conversion easy. Exercise \ud83e\udde9 Read the data from the CSV file Print the cross-section location data, to answer the following questions: How many cross-section does the model contain in total, and how many does each branch have? Do the cross-section have shared cross-section definitions? A shared cross-section definition is a definition used by more than one cross-section. Convert the CSV data (a pd.DataFrame) into HYDROLIB-core CrossSection objects Assign the cross section locations to the model Hint \ud83d\udca1: The MDU file contains a [Geometry] section which has the crossDefFile and crossLocFile reference, e.g.: [Geometry] crossDefFile = crsdef.ini crossLocFile = crsloc.ini ... API references: pd.read_csv() pd.to_dict() CrossLocModel CrossSection In [ ]: Copied! # Read the cross-sections from the CSV cross_section_data_file = data_dir / 'cross_section_locations.csv' cross_section_df = pd . read_csv ( cross_section_data_file , index_col = False ) # Print the data print ( cross_section_df ) # Answers: # * There are 6 cross-sections in the model and each branch has two cross-sections # * There are no shared cross-section definitions; each cross-section has a unique definition ID. # Assign the data to the model cross_loc_model = CrossLocModel () model . geometry . crosslocfile = cross_loc_model cross_loc_model . crosssection = cross_section_df . to_dict ( \"records\" ) # Read the cross-sections from the CSV cross_section_data_file = data_dir / 'cross_section_locations.csv' cross_section_df = pd.read_csv(cross_section_data_file, index_col=False) # Print the data print(cross_section_df) # Answers: # * There are 6 cross-sections in the model and each branch has two cross-sections # * There are no shared cross-section definitions; each cross-section has a unique definition ID. # Assign the data to the model cross_loc_model = CrossLocModel() model.geometry.crosslocfile = cross_loc_model cross_loc_model.crosssection = cross_section_df.to_dict(\"records\")","title":"5. Adding cross-sections to the branches"}]} \ No newline at end of file +{"config":{"indexing":"full","lang":["en"],"min_search_length":3,"prebuild_index":false,"separator":"[\\s\\-]+"},"docs":[{"location":"","text":"Introduction \u00b6 HYDROLIB-core is the core library of Python wrappers around the D-HYDRO model files (input and output) and model engines (kernel libraries). It can serve as the basis for various pre- and postprocessing tools for a modelling workflow of hydrodynamic simulations. More information \u00b6 Some quickstarts: First users: Installation and Tutorials . Developers: List of supported functionalities , API reference , and How to contribute . Releases: hydrolib-core on PyPI , ChangeLog . Known issues and requested features: via GitHub issues .","title":"Home"},{"location":"#introduction","text":"HYDROLIB-core is the core library of Python wrappers around the D-HYDRO model files (input and output) and model engines (kernel libraries). It can serve as the basis for various pre- and postprocessing tools for a modelling workflow of hydrodynamic simulations.","title":"Introduction"},{"location":"#more-information","text":"Some quickstarts: First users: Installation and Tutorials . Developers: List of supported functionalities , API reference , and How to contribute . Releases: hydrolib-core on PyPI , ChangeLog . Known issues and requested features: via GitHub issues .","title":"More information"},{"location":"changelog/","text":"0.6.0 (2023-11-16) \u00b6 Feat \u00b6 Add filetype 10 (polyfile) to class ExtOldFileType (#565) Add missing oldext quantities (#557) Fix \u00b6 Rainfall Runoff .bui file with multiple stations gives parse error 0.5.2 (2023-04-19) \u00b6 Fix \u00b6 failing unittest + SonarCloud security issue (#541) 0.5.1 (2023-04-17) \u00b6 Feat \u00b6 Add the quantity nudge_salinity_temperature to ext old file header. Support the old style external forcings file Add support for several coastal MDU keywords Add support for .tim files and .bc files in the structure file Support meteo blocks in external forcings file (#477) Remove indentation from MDU file Add 4 missing 1D2D settings to FMModel Support *.tim files Add XYN classes to public API (#492) Include old and new observation crossections into MDU FMModel.output class (#470) Support observation crosssection .pli via existing PolyFile class (#464) Add support for 3D Z-sigma settings in MDU Support loading+saving models with configurable OS path style formats (#361) Add support for observation point xyn files (#472) Support filepath as str besides Path for all model classes under FileBasedModel (#469) Add validation for NaN values in datablocks Fix \u00b6 Fixed issues with the new release script Special characters should be parsed correctly from file MDU keywords such as 1d2dLinkFile are written to file without comments (#528) UGRID network files without faces should be accepted correct handling of whitespace and comments in observation point .xyn files (#508) Fix resolving of relative paths containing .. when not using the resolve_casing option. ignore trailing values or text on polyline data lines to better support boundary polyfiles (#482) Reading invalid formatted plifile should raise error instead of warning polyline serializer should print empty trailing comment lines Refactor \u00b6 Make sure of the new Pydantic 1.10 functionality 0.4.1 (2023-01-26) \u00b6 Fix \u00b6 _add_nodes_to_segments fixed ( #440 ) 0.4.0 (2023-01-23) \u00b6 Feat \u00b6 Remove io namespace and add convenient imports/API at several directory levels ( #438 ) Added the option for all supported files to customize the float formatting when saving ( #406 ) Suppress warning in polyfile parser that the white space at the start of the line is ignored ( #409 ) Change data block default spacing from 4 to 2 ( #407 ) Add support for non-recursively loading models ( #401 ) Fix \u00b6 Fixed polylinefile validation for Structure and its subclasses ( #416 ) Rename variable in generate_nodes function ( #437 ) Ensure that QuantityUnitPairs that are not part of a vector are correctly parsed ( #420 ) Enum values are incorrectly written to files ( #403 ) Refactor \u00b6 Small refactoring of the VectorQuantityUnitPairs and VectorForcingBase ( #422 ) Move the base module in XYZ back to IO ( #418 ) Refactored support for vectors in .bc files ( #394 ) 0.3.1 (2022-10-25) \u00b6 Feat \u00b6 option resolve_casing to fix filepath casing between different OS's. Added support for the use of vectors within forcing models with a t3d or timeseries function type. Added possibility to take structure positions into account when discretizing 1d mesh Add support for branches.gui file ( #333 ) Drop extra fields for INIBasedModels if they are not in file format definition Support crs file for observation cross sections ( #289 ) implement mesh generation for pipes ( #294 ) and fix support different reference system ( #298 ) ( #299 ) removed the writeBalanceFile keyword from the mdu support copying generic files/models ( #281 ) Support extra MDU sections ( #284 ) add binder support with a dockerfile ( #264 ) Fix \u00b6 Add backwards compatibility for the old \"percentage from bed\" vertical position type. Fix freeze when printing a ForcingModel with multiple [forcing] blocks by omitting the datablocks. 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See 0.5.1 release notes for the main 0.5 release notes. HYDROLIB-core 0.5.1 Release Notes \u00b6 HYDROLIB-core 0.5.1 mainly adds more support for D-Flow FM 2D3D models in coastal applications. Compatibility Notes \u00b6 Support for MacOS is temporarily dropped, due to an upgrade to MeshKernel 2.0.2, which has no MacOS version at the moment. We aim to re-enable this support in future releases. New Features \u00b6 Support for cross-platform path style ( #361 ), more info in the loading and saving tutorial . Support for more MDU keywords (1D2D: see #489 , 2D/3D: see #474 , #486 ). Support for [Meteo] blocks in external forcings files ( #446 ) Support for various legacy file formats, to facilitate future model conversions: Observation point *.xyn files ( #459 ). Observation crosssection *.pli files ( #364 , #461 ). Old external forcings file *.ext ( #369 ). Support for timeseries in *.tim files ( #348 ), also included in structure files ( #497 ) and external meteo forcings ( #446 ). Improvements \u00b6 All file-based model class constructors now accept file path as a str , in addition to the already existing pathlib.Path ( #365 ). MeshKernel dependency was updated to version 2.0.2, which has more functionality in its API ( #450 ). Bugfixes \u00b6 See the detailed ChangeLog on GitHub . Archive \u00b6 Pre-0.5.0 release notes are available via the ChangeLog on GitHub .","title":"Release notes"},{"location":"releasenotes/#hydrolib-core-052-release-notes","text":"HYDROLIB-core 0.5.2 only contains 'cosmetic' changes, and is otherwise equal to 0.5.1. 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Observation crosssection *.pli files ( #364 , #461 ). Old external forcings file *.ext ( #369 ). Support for timeseries in *.tim files ( #348 ), also included in structure files ( #497 ) and external meteo forcings ( #446 ).","title":"New Features"},{"location":"releasenotes/#improvements","text":"All file-based model class constructors now accept file path as a str , in addition to the already existing pathlib.Path ( #365 ). MeshKernel dependency was updated to version 2.0.2, which has more functionality in its API ( #450 ).","title":"Improvements"},{"location":"releasenotes/#bugfixes","text":"See the detailed ChangeLog on GitHub .","title":"Bugfixes"},{"location":"releasenotes/#archive","text":"Pre-0.5.0 release notes are available via the ChangeLog on GitHub .","title":"Archive"},{"location":"guides/contributing/","text":"Contributing \u00b6 Tooling \u00b6 Poetry \u00b6 We use poetry to manage our package and its dependencies. More information on the separate Poetry page. Pytest \u00b6 We use pytest to test our package. Run it with poetry run pytest to test your code changes locally. Black \u00b6 We use black as an autoformatter. It is also run during CI and will fail if it's not formatted beforehand. Isort \u00b6 We use isort as an autoformatter. Commitizen \u00b6 We use commitizen to automatically bump the version number. If you use conventional commit messages , the changelog.md is generated automatically. More details below under \"Merging\" . Development \u00b6 Branches \u00b6 For each issue or feature, a separate branch should be created from the main. To keep the branches organized each branch should be created with a prefix in the name: * feat/ for new features and feature improvements; * fix/ for bugfixes; * docs/ for documentation; * chore/ for tasks, tool changes, configuration work, everything not relevant for external users. After this prefix, preferrably add the issue number, followed by a brief title using underscores. For example: feat/160_obsfile or, fix/197_validation_pump_stages . Pull requests \u00b6 When starting development on a branch, a pull request should be created for reviews and continous integration. In the description text area on GitHub, use a closing keyword such that this PR will be automatically linked to the issue. For example: Fixes #160 . During continuous integration, the checks will be run with python 3.8 and 3.9 on Windows, Ubuntu and MacOS. The checks consist of running the tests, checking the code formatting and running SonarCloud. We advise to use a draft pull request, to prevent the branch to be merged back before developement is finished. When the branch is ready for review, you can update the status of the pull request to \"ready for review\". Reviews \u00b6 When an issue is ready for review, it should be moved to the \"Ready for review\" column on the GitHub board for visibility. Merging \u00b6 Merging a branch can only happen when a pull request is accepted through review. When a pull request is accepted the changes should be merged back with the \"squash and merge\" option. The merge commit message should adhere to the conventional commit guidelines . * In the first textfield of the GitHub commit form, use for example: feat: Support 3D timeseries in .bc file , without any PR/issue references. * In the text area of the GitHub commit form, optionally add some more description details on the commit. * In the same text area, add footer line Refs: # , and if needed an extra line BREAKING CHANGE: explanation . Don't forget a blank line between footer lines and the preceding description lines (if present). Coding guidelines \u00b6 If there is code that needs to be tested, there should be tests written for it. If there are any additions or changes to the public API, the documentation should be updated. Files should be added to the appropriate folder to keep modules and objects within the correct scope. Releasing \u00b6 Making a release on GitHub and PyPi \u00b6 When we are releasing hydrolib-core, we want to create a release on GitHub and PyPi. This should only be done by one of the hydrolib-core maintainers. To prepare for releasing, please make sure you have a clean checkout of the latest main branch and follow these steps: Go to the root level your hydrolib-core checkout location Open your command line in this location Perform the following commands: If commitizen is not installed yet: pip install commitizen Prepare the Changelog before bumping the release version: cz changelog --unreleased-version=\"0.3.1\" --incremental In the above command, use the version tag instead of the raw version number (so without \"v\" in our case). If you don't know the version tag yet, you can do a dry-run of the next step, for example via: cz bump --dry-run --increment PATCH In the updated docs/changelog.md , manually add links to GitHub PR numbers (or issue numbers) at the end of each line, if appropriate. It is recommended to use the macros [#123](https://github.com/Deltares/HYDROLIB-core/pull/123) , resp. [#345](https://github.com/Deltares/HYDROLIB-core/issues/345) to get automatic hyperlinks (where 123 and 345 are GitHub's PR and issue numbers, respectively). Use MAJOR, MINOR or PATCH to increment the version cz bump --increment {MAJOR,MINOR,PATCH} Or let commitizen detect the increment automatically cz bump Push the tags and changes to git git push --tags git push Build the wheels and publish the package to PyPi poetry build poetry publish You will need a PyPI account and permissions for this publish step. Ask a maintainer for help if you need this. Go to the hydrolib-core GitHub page. Go to Releases and click on Draft a new release . Fill in the Release title field with Release v , with in the full format .. , for example Release v0.3.0 . Choose the appropriate version tag in the Choose a tag dropdown box (typically without \"v\" prefix). Click on Generate release notes . Click on Publish release . Celebrate","title":"Contributing"},{"location":"guides/contributing/#contributing","text":"","title":"Contributing"},{"location":"guides/contributing/#tooling","text":"","title":"Tooling"},{"location":"guides/contributing/#poetry","text":"We use poetry to manage our package and its dependencies. More information on the separate Poetry page.","title":"Poetry"},{"location":"guides/contributing/#pytest","text":"We use pytest to test our package. Run it with poetry run pytest to test your code changes locally.","title":"Pytest"},{"location":"guides/contributing/#black","text":"We use black as an autoformatter. It is also run during CI and will fail if it's not formatted beforehand.","title":"Black"},{"location":"guides/contributing/#isort","text":"We use isort as an autoformatter.","title":"Isort"},{"location":"guides/contributing/#commitizen","text":"We use commitizen to automatically bump the version number. If you use conventional commit messages , the changelog.md is generated automatically. More details below under \"Merging\" .","title":"Commitizen"},{"location":"guides/contributing/#development","text":"","title":"Development"},{"location":"guides/contributing/#branches","text":"For each issue or feature, a separate branch should be created from the main. To keep the branches organized each branch should be created with a prefix in the name: * feat/ for new features and feature improvements; * fix/ for bugfixes; * docs/ for documentation; * chore/ for tasks, tool changes, configuration work, everything not relevant for external users. 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The merge commit message should adhere to the conventional commit guidelines . * In the first textfield of the GitHub commit form, use for example: feat: Support 3D timeseries in .bc file , without any PR/issue references. * In the text area of the GitHub commit form, optionally add some more description details on the commit. * In the same text area, add footer line Refs: # , and if needed an extra line BREAKING CHANGE: explanation . Don't forget a blank line between footer lines and the preceding description lines (if present).","title":"Merging"},{"location":"guides/contributing/#coding-guidelines","text":"If there is code that needs to be tested, there should be tests written for it. If there are any additions or changes to the public API, the documentation should be updated. Files should be added to the appropriate folder to keep modules and objects within the correct scope.","title":"Coding guidelines"},{"location":"guides/contributing/#releasing","text":"","title":"Releasing"},{"location":"guides/contributing/#making-a-release-on-github-and-pypi","text":"When we are releasing hydrolib-core, we want to create a release on GitHub and PyPi. This should only be done by one of the hydrolib-core maintainers. To prepare for releasing, please make sure you have a clean checkout of the latest main branch and follow these steps: Go to the root level your hydrolib-core checkout location Open your command line in this location Perform the following commands: If commitizen is not installed yet: pip install commitizen Prepare the Changelog before bumping the release version: cz changelog --unreleased-version=\"0.3.1\" --incremental In the above command, use the version tag instead of the raw version number (so without \"v\" in our case). If you don't know the version tag yet, you can do a dry-run of the next step, for example via: cz bump --dry-run --increment PATCH In the updated docs/changelog.md , manually add links to GitHub PR numbers (or issue numbers) at the end of each line, if appropriate. It is recommended to use the macros [#123](https://github.com/Deltares/HYDROLIB-core/pull/123) , resp. [#345](https://github.com/Deltares/HYDROLIB-core/issues/345) to get automatic hyperlinks (where 123 and 345 are GitHub's PR and issue numbers, respectively). Use MAJOR, MINOR or PATCH to increment the version cz bump --increment {MAJOR,MINOR,PATCH} Or let commitizen detect the increment automatically cz bump Push the tags and changes to git git push --tags git push Build the wheels and publish the package to PyPi poetry build poetry publish You will need a PyPI account and permissions for this publish step. Ask a maintainer for help if you need this. Go to the hydrolib-core GitHub page. Go to Releases and click on Draft a new release . Fill in the Release title field with Release v , with in the full format .. , for example Release v0.3.0 . Choose the appropriate version tag in the Choose a tag dropdown box (typically without \"v\" prefix). Click on Generate release notes . Click on Publish release . Celebrate","title":"Making a release on GitHub and PyPi"},{"location":"guides/devcontainers/","text":"Devcontainers: Developing HYDROLIB in an isolated environment \u00b6 A common struggle while working on any software project, is to ensure all of your dependencies are available and you can actually build the software, run the tests etc. While any developer is free to choose their own toolchain, environment etc, HYDROLIB-Core includes the necessary files to run the project within a so called devcontainer within Visual Studio Code. With the help of Docker, we can spin up an independent development environment, ensuring that HYDROLIB-Core works out of the box and you are insulated from any specific local configurations on your machines. This should allow you to start working on HYDROLIB-Core quickly. The following sub sections will walk you through the necessary dependencies, and how to use it, and modify it, to fit your own needs. This will be done in the following order: Requirements: Docker and Visual Studio Code Remote - Containers extension Dockerfile configures python, poetry and other dependencies devcontainer.json specifies how visual studio code should be configured External references Requirements: Docker and Visual Studio Code Remote - Containers extension \u00b6 In order to run HYDROLIB in a dev container we need the following dependencies Docker Visual Studio Code Visual Studio Code Remote - Containers extension Docker will ensure we can spin up an isolated container. A full tutorial on how to use Docker is outside the scope of this tutorial, however the Getting Started guide of Docker should provide you with the steps to install Docker on your machine. Visual Studio Code is the editor we will use. The website should provide you with the necessary steps to install it. Lastly, we need to install the Visual Studio Code Remote - Containers extension . The install button on the marketplace should walk you through the steps to install it. Run HYDROLIB in a devcontainer by executing \"Reopen in container\" command \u00b6 With all of the dependencies set up, we should be able to run HYDROLIB within our devcontainer. When opening the HYDROLIB-Core repository in Visual Studio Code, we should either get a pop-up asking us to reopen the project within a remote container, or we can select the \"Open a Remote Window\" button, the green button in the bottom left corner of your visual studio code window, after which we can select \"Reopen in container\". Both will then spin up a new container in which we can work. Note that if it is the first time starting our repository, or if we have made changes to the Docker Images we might need to build the container, which could take a few moments. Once opened in a separate container, we can start a terminal to verify everything is working correctly. First, we need to ensure the correct python interpreter is used. We want to use the virtual environment created by poetry, which default resides in ./.venv/ . Visual Studio Code might prompt you to select an interpreter. If it does press the 'Select Python Interpreter', and select the virtual environment residing in ./.venv/ . If it does not explicitly prompt you (or if you want to change it later on), press ctrl + shift + p , and select 'Python: Select Interpreter'. If it currently is not set to the virtual environment, change it to the correct interpreter. It should now be possible to run the HYDROLIB-Core tests within our container by opening the 'Testing' tab. If the 'Testing' is not already configured in the ./.vscode/settings.json , we will need to configure the Python tests: click the 'Configure Python Tests' button in the 'Testing' tab Select 'pytest' in the pop-up window Select 'tests', this will ensure tests are located in our 'tests' directory Once this is done all tests should pass as they would normally. Dockerfile configures python, poetry and other dependencies \u00b6 The Dockerfile which specifies our specific devcontainer can be found here in the repository . Currently, it extends the python 3.9 buster image provided by the Python foundation. It then does the following: Installs Poetry 1.1.11 and configure the necessary paths Copies the poetry.lock and pyproject.toml and installs the project Installs git within the container This should provide us with a ready to go environment to run HYDROLIB-Core with. devcontainer.json specifies how visual studio code should be configured \u00b6 We can further customise our environment by editing the devcontainer.json located here in the repository . In particular, you can add any Visual Studio Code extensions you require for your work to the extensions field. Currently it is populated with several common Python extensions which we use to develop HYDROLIB. For a full overview how to customise this file, you can find the documentation here External references: \u00b6 Developing inside a Container - VS Code docs Develop with containers - VS Code docs (guide specific for python) Document docker poetry best practices - Poetry issue","title":"Developer container"},{"location":"guides/devcontainers/#devcontainers-developing-hydrolib-in-an-isolated-environment","text":"A common struggle while working on any software project, is to ensure all of your dependencies are available and you can actually build the software, run the tests etc. While any developer is free to choose their own toolchain, environment etc, HYDROLIB-Core includes the necessary files to run the project within a so called devcontainer within Visual Studio Code. With the help of Docker, we can spin up an independent development environment, ensuring that HYDROLIB-Core works out of the box and you are insulated from any specific local configurations on your machines. This should allow you to start working on HYDROLIB-Core quickly. The following sub sections will walk you through the necessary dependencies, and how to use it, and modify it, to fit your own needs. This will be done in the following order: Requirements: Docker and Visual Studio Code Remote - Containers extension Dockerfile configures python, poetry and other dependencies devcontainer.json specifies how visual studio code should be configured External references","title":"Devcontainers: Developing HYDROLIB in an isolated environment"},{"location":"guides/devcontainers/#requirements-docker-and-visual-studio-code-remote-containers-extension","text":"In order to run HYDROLIB in a dev container we need the following dependencies Docker Visual Studio Code Visual Studio Code Remote - Containers extension Docker will ensure we can spin up an isolated container. A full tutorial on how to use Docker is outside the scope of this tutorial, however the Getting Started guide of Docker should provide you with the steps to install Docker on your machine. Visual Studio Code is the editor we will use. The website should provide you with the necessary steps to install it. Lastly, we need to install the Visual Studio Code Remote - Containers extension . The install button on the marketplace should walk you through the steps to install it.","title":"Requirements: Docker and Visual Studio Code Remote - Containers extension"},{"location":"guides/devcontainers/#run-hydrolib-in-a-devcontainer-by-executing-reopen-in-container-command","text":"With all of the dependencies set up, we should be able to run HYDROLIB within our devcontainer. When opening the HYDROLIB-Core repository in Visual Studio Code, we should either get a pop-up asking us to reopen the project within a remote container, or we can select the \"Open a Remote Window\" button, the green button in the bottom left corner of your visual studio code window, after which we can select \"Reopen in container\". Both will then spin up a new container in which we can work. Note that if it is the first time starting our repository, or if we have made changes to the Docker Images we might need to build the container, which could take a few moments. Once opened in a separate container, we can start a terminal to verify everything is working correctly. First, we need to ensure the correct python interpreter is used. We want to use the virtual environment created by poetry, which default resides in ./.venv/ . Visual Studio Code might prompt you to select an interpreter. If it does press the 'Select Python Interpreter', and select the virtual environment residing in ./.venv/ . If it does not explicitly prompt you (or if you want to change it later on), press ctrl + shift + p , and select 'Python: Select Interpreter'. If it currently is not set to the virtual environment, change it to the correct interpreter. It should now be possible to run the HYDROLIB-Core tests within our container by opening the 'Testing' tab. If the 'Testing' is not already configured in the ./.vscode/settings.json , we will need to configure the Python tests: click the 'Configure Python Tests' button in the 'Testing' tab Select 'pytest' in the pop-up window Select 'tests', this will ensure tests are located in our 'tests' directory Once this is done all tests should pass as they would normally.","title":"Run HYDROLIB in a devcontainer by executing \"Reopen in container\" command"},{"location":"guides/devcontainers/#dockerfile-configures-python-poetry-and-other-dependencies","text":"The Dockerfile which specifies our specific devcontainer can be found here in the repository . Currently, it extends the python 3.9 buster image provided by the Python foundation. It then does the following: Installs Poetry 1.1.11 and configure the necessary paths Copies the poetry.lock and pyproject.toml and installs the project Installs git within the container This should provide us with a ready to go environment to run HYDROLIB-Core with.","title":"Dockerfile configures python, poetry and other dependencies"},{"location":"guides/devcontainers/#devcontainerjson-specifies-how-visual-studio-code-should-be-configured","text":"We can further customise our environment by editing the devcontainer.json located here in the repository . In particular, you can add any Visual Studio Code extensions you require for your work to the extensions field. Currently it is populated with several common Python extensions which we use to develop HYDROLIB. For a full overview how to customise this file, you can find the documentation here","title":"devcontainer.json specifies how visual studio code should be configured"},{"location":"guides/devcontainers/#external-references","text":"Developing inside a Container - VS Code docs Develop with containers - VS Code docs (guide specific for python) Document docker poetry best practices - Poetry issue","title":"External references:"},{"location":"guides/developers/","text":"Developer guide \u00b6 This guide contains some more in-depth guidelines, tasks and examples that developers should adhere to when working on hydrolib-core. In addition to being a useful resource for developing, this documentation can also be helpful for code reviews. Explicitly exposing the public API \u00b6 Whenever you add new functionality that should (or could) be used by the users, make sure you explicitly expose them in the correct __init__.py files. For example, you have developed a new TimModel class that represents a .tim file. The TimModel makes use of the TimParser class and TimSerializer class. While the TimModel class should be publicly exposed to the users, because it is part of the public API, the parser and serializer classes are implementation details that users should not be concerned with. The parser and serializer should therefore not be publicly exposed to the users. To expose the TimModel explicitly to our users, you have to update both the hydrolib/core/dflowfm/tim/__init__.py (assuming you created a new tim folder for this new functionality) and the hydrolib/core/dflowfm/__init__.py : # hydrolib/core/dflowfm/tim/__init__.py from .models import TimModel __all__ = [ \"TimModel\" , ] # hydrolib/core/dflowfm/__init__.py ... ... from .tim import * Updating the documentation \u00b6 In the hydrolib-core repository there are several reference files that are used to automatically generate the API reference . If you add or make changes to the existing API, always make sure the API reference is still up to date. Let's use the example mentioned before, where the TimModel was introduced in hydrolib-core. Since this is new functionality that affects the API, we have to update the reference files. The API reference files are located at docs\\reference . Since the TimModel was newly introduced, we should create a new file named tim.md . The contents of this file include a short description about what the '.tim' file is and what it is used for, followed by the actual API. You do not have to manually write the API, that is done for us by mkdocs. Since the newly introduced TimParser and TimSerializer are not part of the public API, they should not be added to the reference file. An example of such an .md can be found below: # Timeseries .tim files Timeseries .tim files are timeseries input files for a [ D-Flow FM ]( glossary.md#d-flow-fm ) model. The support of .tim files is discontinued and are replaced by the [ .bc file ]( #bc-file ). They are represented by the class below. ## Model ::: hydrolib.core.dflowfm.tim.models Updating the functionalities sheet \u00b6 To generate a list of D-HYDRO functionalities, grouped by kernel, and the current status of support inside hydrolib-core, we use an Excel sheet. This Excel sheet can be found at docs\\topics\\dhydro_support_hydrolib-core.xlsx . Each time you add support for new D-HYDRO functionalities, this Excel file has to be updated. Detailed information on how to update the Excel file correctly can be found inside the Excel file itself.","title":"Developer guide"},{"location":"guides/developers/#developer-guide","text":"This guide contains some more in-depth guidelines, tasks and examples that developers should adhere to when working on hydrolib-core. In addition to being a useful resource for developing, this documentation can also be helpful for code reviews.","title":"Developer guide"},{"location":"guides/developers/#explicitly-exposing-the-public-api","text":"Whenever you add new functionality that should (or could) be used by the users, make sure you explicitly expose them in the correct __init__.py files. For example, you have developed a new TimModel class that represents a .tim file. The TimModel makes use of the TimParser class and TimSerializer class. While the TimModel class should be publicly exposed to the users, because it is part of the public API, the parser and serializer classes are implementation details that users should not be concerned with. The parser and serializer should therefore not be publicly exposed to the users. To expose the TimModel explicitly to our users, you have to update both the hydrolib/core/dflowfm/tim/__init__.py (assuming you created a new tim folder for this new functionality) and the hydrolib/core/dflowfm/__init__.py : # hydrolib/core/dflowfm/tim/__init__.py from .models import TimModel __all__ = [ \"TimModel\" , ] # hydrolib/core/dflowfm/__init__.py ... ... from .tim import *","title":"Explicitly exposing the public API"},{"location":"guides/developers/#updating-the-documentation","text":"In the hydrolib-core repository there are several reference files that are used to automatically generate the API reference . If you add or make changes to the existing API, always make sure the API reference is still up to date. Let's use the example mentioned before, where the TimModel was introduced in hydrolib-core. Since this is new functionality that affects the API, we have to update the reference files. The API reference files are located at docs\\reference . Since the TimModel was newly introduced, we should create a new file named tim.md . The contents of this file include a short description about what the '.tim' file is and what it is used for, followed by the actual API. You do not have to manually write the API, that is done for us by mkdocs. Since the newly introduced TimParser and TimSerializer are not part of the public API, they should not be added to the reference file. An example of such an .md can be found below: # Timeseries .tim files Timeseries .tim files are timeseries input files for a [ D-Flow FM ]( glossary.md#d-flow-fm ) model. The support of .tim files is discontinued and are replaced by the [ .bc file ]( #bc-file ). They are represented by the class below. ## Model ::: hydrolib.core.dflowfm.tim.models","title":"Updating the documentation"},{"location":"guides/developers/#updating-the-functionalities-sheet","text":"To generate a list of D-HYDRO functionalities, grouped by kernel, and the current status of support inside hydrolib-core, we use an Excel sheet. This Excel sheet can be found at docs\\topics\\dhydro_support_hydrolib-core.xlsx . Each time you add support for new D-HYDRO functionalities, this Excel file has to be updated. Detailed information on how to update the Excel file correctly can be found inside the Excel file itself.","title":"Updating the functionalities sheet"},{"location":"guides/documentation/","text":"Documentation \u00b6 We use MKdocs for documentation. For full documentation visit mkdocs.org . The documentation itself is written with https://documentation.divio.com/ structure in mind, creating different categories: - Guides - Tutorials - Reference - Topics Commands \u00b6 mkdocs new [dir-name] - Create a new project. mkdocs serve - Start the live-reloading docs server. mkdocs build - Build the documentation site. mkdocs -h - Print help message and exit. Project layout \u00b6 mkdocs.yml # The configuration file. docs/ index.md # The documentation homepage. ... # Other markdown pages, images and other files.","title":"Documentation"},{"location":"guides/documentation/#documentation","text":"We use MKdocs for documentation. For full documentation visit mkdocs.org . The documentation itself is written with https://documentation.divio.com/ structure in mind, creating different categories: - Guides - Tutorials - Reference - Topics","title":"Documentation"},{"location":"guides/documentation/#commands","text":"mkdocs new [dir-name] - Create a new project. mkdocs serve - Start the live-reloading docs server. mkdocs build - Build the documentation site. mkdocs -h - Print help message and exit.","title":"Commands"},{"location":"guides/documentation/#project-layout","text":"mkdocs.yml # The configuration file. docs/ index.md # The documentation homepage. ... # Other markdown pages, images and other files.","title":"Project layout"},{"location":"guides/gettinghelp/","text":"Getting help \u00b6 See the How-to's and Tutorials to get started using hydrolib-core. For building you own tools upon hydrolib-core, see the API reference for more complete documentation of all current features. If you are missing functionality, please check the list of supported functionalities first. If you think you've encountered a bug, please check the open GitHub issues . Feel free to open a new issue if your issue is not yet known. You can contact the package maintainers about any remaining questions you have.","title":"Getting help"},{"location":"guides/gettinghelp/#getting-help","text":"See the How-to's and Tutorials to get started using hydrolib-core. For building you own tools upon hydrolib-core, see the API reference for more complete documentation of all current features. If you are missing functionality, please check the list of supported functionalities first. If you think you've encountered a bug, please check the open GitHub issues . Feel free to open a new issue if your issue is not yet known. You can contact the package maintainers about any remaining questions you have.","title":"Getting help"},{"location":"guides/poetry/","text":"Installation using Poetry \u00b6 You can use a Poetry-based installation if you are using hydrolib-core from a local clone of the Github repository, for example if you intend to contribute to the code. Clone the GitHub repo \u00b6 Use your own preferred way of cloning the GitHub repository of hydrolib-core. In the examples below it is placed in C:\\checkouts\\HYDROLIB-core_git . Use Poetry to install hydrolib-core \u00b6 We use poetry to manage our package and its dependencies. Note If you use conda , do not combine conda virtual environments with the poetry virtual environment. In other words, run the poetry install command from the base conda environment. Download + installation instructions for Poetry are here . After installation of Poetry itself, now use it to install your local clone of the hydrolib-core package, as follows. Make sure Poetry is available on your PATH and run poetry install in the hydrolib-core directory in your shell of choice. This will create a virtual environment in which hydrolib-core is installed and made available for use in your own scripts. For example in an Anaconda PowerShell: (base) PS C:\\checkouts\\HYDROLIB-core_git> poetry install Creating virtualenv hydrolib-core-kHkQBdtS-py3.8 in C:\\Users\\dam_ar\\AppData\\Local\\pypoetry\\Cache\\virtualenvs Installing dependencies from lock file Package operations: 67 installs, 0 updates, 0 removals * Installing six (1.16.0) [..] Installing the current project: hydrolib-core (0.1.5) (base) PS C:\\checkouts\\HYDROLIB-core_git> If you need to use an already existing Python installation, you can activate it and run poetry env use system before poetry install . Test your installation, by running the hydrolib-core pytest suite via poetry: (base) PS C:\\checkouts\\HYDROLIB-core_git> poetry run pytest ===================================== test session starts ====================================== platform win32 -- Python 3.8.8, pytest-6.2.5, py-1.10.0, pluggy-1.0.0 rootdir: C:\\checkouts\\HYDROLIB-core_git, configfile: pyproject.toml plugins: cov-2.12.1 collected 473 items / 2 deselected / 471 selected tests\\io\\dflowfm\\ini\\test_ini.py ........................................................ [ 3%] tests\\io\\dflowfm\\test_bc.py .... [ 4%] tests\\io\\dflowfm\\test_ext.py ........................................................ [ 5%] tests\\io\\dflowfm\\test_fnm.py .................. [ 11%] tests\\io\\dflowfm\\test_net.py ............ [ 11%] tests\\io\\dflowfm\\test_parser.py . [ 12%] tests\\io\\dflowfm\\test_polyfile.py ........................................................[ 23%] .................................... [ 27%] tests\\io\\dflowfm\\test_structure.py .......................................................[ 42%] ......................................................... [ 54%] tests\\io\\dimr\\test_dimr.py ... [ 56%] tests\\io\\rr\\meteo\\test_bui.py ........................... [ 57%] tests\\io\\test_docker.py . [ 70%] tests\\test_model.py ............... [ 78%] tests\\test_utils.py ....... [ 91%] ......................................... [100%] ============================== 471 passed, 2 deselected in 3.50s =============================== (base) PS C:\\checkouts\\HYDROLIB-core_git> Start using hydrolib-core. You can launch your favourite editor (for example VS Code) by first starting a poetry shell with the virtual hydrolib-core environment: (base) PS C:\\checkouts\\HYDROLIB-core_git> poetry shell (base) PS C:\\checkouts\\HYDROLIB-core_git> code Frequently asked questions \u00b6 How to fix \"File ... does not exist\" errors during poetry install as in the example below? * Installing six (1.16.0) ValueError File \\C:\\Users\\dam_ar\\AppData\\Local\\pypoetry\\Cache\\artifacts\\48\\e6\\04\\8118155ae3ec3a16dd2a213bbf7a7d8a62c596b2e90f73a22c896269f1\\six-1.16.0-py2.py3-none-any.whl does not exist This may occur when a conda environment was activated. Delete the AppData\\Local\\pypoetry\\Cache directory. Then run conda deactivate to return to the base environment. Finally, rerun poetry install .","title":"Local clone + Poetry"},{"location":"guides/poetry/#installation-using-poetry","text":"You can use a Poetry-based installation if you are using hydrolib-core from a local clone of the Github repository, for example if you intend to contribute to the code.","title":"Installation using Poetry"},{"location":"guides/poetry/#clone-the-github-repo","text":"Use your own preferred way of cloning the GitHub repository of hydrolib-core. In the examples below it is placed in C:\\checkouts\\HYDROLIB-core_git .","title":"Clone the GitHub repo"},{"location":"guides/poetry/#use-poetry-to-install-hydrolib-core","text":"We use poetry to manage our package and its dependencies. Note If you use conda , do not combine conda virtual environments with the poetry virtual environment. In other words, run the poetry install command from the base conda environment. Download + installation instructions for Poetry are here . After installation of Poetry itself, now use it to install your local clone of the hydrolib-core package, as follows. Make sure Poetry is available on your PATH and run poetry install in the hydrolib-core directory in your shell of choice. This will create a virtual environment in which hydrolib-core is installed and made available for use in your own scripts. For example in an Anaconda PowerShell: (base) PS C:\\checkouts\\HYDROLIB-core_git> poetry install Creating virtualenv hydrolib-core-kHkQBdtS-py3.8 in C:\\Users\\dam_ar\\AppData\\Local\\pypoetry\\Cache\\virtualenvs Installing dependencies from lock file Package operations: 67 installs, 0 updates, 0 removals * Installing six (1.16.0) [..] Installing the current project: hydrolib-core (0.1.5) (base) PS C:\\checkouts\\HYDROLIB-core_git> If you need to use an already existing Python installation, you can activate it and run poetry env use system before poetry install . Test your installation, by running the hydrolib-core pytest suite via poetry: (base) PS C:\\checkouts\\HYDROLIB-core_git> poetry run pytest ===================================== test session starts ====================================== platform win32 -- Python 3.8.8, pytest-6.2.5, py-1.10.0, pluggy-1.0.0 rootdir: C:\\checkouts\\HYDROLIB-core_git, configfile: pyproject.toml plugins: cov-2.12.1 collected 473 items / 2 deselected / 471 selected tests\\io\\dflowfm\\ini\\test_ini.py ........................................................ [ 3%] tests\\io\\dflowfm\\test_bc.py .... [ 4%] tests\\io\\dflowfm\\test_ext.py ........................................................ [ 5%] tests\\io\\dflowfm\\test_fnm.py .................. [ 11%] tests\\io\\dflowfm\\test_net.py ............ [ 11%] tests\\io\\dflowfm\\test_parser.py . [ 12%] tests\\io\\dflowfm\\test_polyfile.py ........................................................[ 23%] .................................... [ 27%] tests\\io\\dflowfm\\test_structure.py .......................................................[ 42%] ......................................................... [ 54%] tests\\io\\dimr\\test_dimr.py ... [ 56%] tests\\io\\rr\\meteo\\test_bui.py ........................... [ 57%] tests\\io\\test_docker.py . [ 70%] tests\\test_model.py ............... [ 78%] tests\\test_utils.py ....... [ 91%] ......................................... [100%] ============================== 471 passed, 2 deselected in 3.50s =============================== (base) PS C:\\checkouts\\HYDROLIB-core_git> Start using hydrolib-core. You can launch your favourite editor (for example VS Code) by first starting a poetry shell with the virtual hydrolib-core environment: (base) PS C:\\checkouts\\HYDROLIB-core_git> poetry shell (base) PS C:\\checkouts\\HYDROLIB-core_git> code","title":"Use Poetry to install hydrolib-core"},{"location":"guides/poetry/#frequently-asked-questions","text":"How to fix \"File ... does not exist\" errors during poetry install as in the example below? * Installing six (1.16.0) ValueError File \\C:\\Users\\dam_ar\\AppData\\Local\\pypoetry\\Cache\\artifacts\\48\\e6\\04\\8118155ae3ec3a16dd2a213bbf7a7d8a62c596b2e90f73a22c896269f1\\six-1.16.0-py2.py3-none-any.whl does not exist This may occur when a conda environment was activated. Delete the AppData\\Local\\pypoetry\\Cache directory. Then run conda deactivate to return to the base environment. Finally, rerun poetry install .","title":"Frequently asked questions"},{"location":"guides/setup/","text":"Installation using pip \u00b6 You can use a pip-based installation if you simply want to use hydrolib-core, without making contributions to the package yourself. You should be able to install hydrolib-core with: pip install hydrolib-core Conda specifics \u00b6 Note If you use conda , it is advisable to install hydrolib-core within a new environment with only conda-forge as channel. If you want to create a fresh test environment for hydrolib-core, you could use the following command (only once): conda create -n hydrolib python = 3 .8 -c conda-forge Prior to the pip install , first activate the desired environment: conda activate hydrolib After successful installation, you should be able to do the \"Basic Model\" tutorial .","title":"pip install"},{"location":"guides/setup/#installation-using-pip","text":"You can use a pip-based installation if you simply want to use hydrolib-core, without making contributions to the package yourself. You should be able to install hydrolib-core with: pip install hydrolib-core","title":"Installation using pip"},{"location":"guides/setup/#conda-specifics","text":"Note If you use conda , it is advisable to install hydrolib-core within a new environment with only conda-forge as channel. If you want to create a fresh test environment for hydrolib-core, you could use the following command (only once): conda create -n hydrolib python = 3 .8 -c conda-forge Prior to the pip install , first activate the desired environment: conda activate hydrolib After successful installation, you should be able to do the \"Basic Model\" tutorial .","title":"Conda specifics"},{"location":"include/mkdocs-macros/main/","text":"(function (global, factory) { typeof exports === 'object' && typeof module !== 'undefined' ? module.exports = factory() : typeof define === 'function' && define.amd ? define(factory) : (global = global || self, global.ClipboardCopyElement = factory()); }(this, function () { 'use strict'; function createNode(text) { const node = document.createElement('pre'); node.style.width = '1px'; node.style.height = '1px'; node.style.position = 'fixed'; node.style.top = '5px'; node.textContent = text; return node; } function copyNode(node) { if ('clipboard' in navigator) { // eslint-disable-next-line flowtype/no-flow-fix-me-comments // $FlowFixMe Clipboard is not defined in Flow yet. return navigator.clipboard.writeText(node.textContent); 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if (!(root instanceof Document || 'ShadowRoot' in window && root instanceof ShadowRoot)) return; const node = root.getElementById(id); if (node) copyTarget(node).then(trigger); } } function copyTarget(content) { if (content instanceof HTMLInputElement || content instanceof HTMLTextAreaElement) { return copyText(content.value); } else if (content instanceof HTMLAnchorElement && content.hasAttribute('href')) { return copyText(content.href); } else { return copyNode(content); } } function clicked(event) { const button = event.currentTarget; if (button instanceof HTMLElement) { copy(button); } } function keydown(event) { if (event.key === ' ' || event.key === 'Enter') { const button = event.currentTarget; if (button instanceof HTMLElement) { event.preventDefault(); copy(button); } } } function focused(event) { event.currentTarget.addEventListener('keydown', keydown); } function blurred(event) { event.currentTarget.removeEventListener('keydown', keydown); } class ClipboardCopyElement extends HTMLElement { constructor() { super(); this.addEventListener('click', clicked); this.addEventListener('focus', focused); this.addEventListener('blur', blurred); } connectedCallback() { if (!this.hasAttribute('tabindex')) { this.setAttribute('tabindex', '0'); } if (!this.hasAttribute('role')) { this.setAttribute('role', 'button'); } } get value() { return this.getAttribute('value') || ''; } set value(text) { this.setAttribute('value', text); } } if (!window.customElements.get('clipboard-copy')) { window.ClipboardCopyElement = ClipboardCopyElement; window.customElements.define('clipboard-copy', ClipboardCopyElement); } return ClipboardCopyElement; })); document.addEventListener('clipboard-copy', function(event) { const notice = event.target.querySelector('.notice') notice.hidden = false setTimeout(function() { notice.hidden = true }, 1000) }) pre { line-height: 125%; } td.linenos .normal { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; } span.linenos { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; } td.linenos .special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; } span.linenos.special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; } .highlight-ipynb .hll { background-color: var(--jp-cell-editor-active-background) } .highlight-ipynb { background: var(--jp-cell-editor-background); color: var(--jp-mirror-editor-variable-color) } .highlight-ipynb .c { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment */ .highlight-ipynb .err { color: var(--jp-mirror-editor-error-color) } /* Error */ .highlight-ipynb .k { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword */ .highlight-ipynb .o { color: var(--jp-mirror-editor-operator-color); font-weight: bold } /* Operator */ .highlight-ipynb .p { color: var(--jp-mirror-editor-punctuation-color) } /* Punctuation */ .highlight-ipynb .ch { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Hashbang */ .highlight-ipynb .cm { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Multiline */ .highlight-ipynb .cp { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Preproc */ .highlight-ipynb .cpf { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.PreprocFile */ .highlight-ipynb .c1 { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Single */ .highlight-ipynb .cs { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Special */ .highlight-ipynb .kc { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Constant */ .highlight-ipynb .kd { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Declaration */ .highlight-ipynb .kn { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Namespace */ .highlight-ipynb .kp { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Pseudo */ .highlight-ipynb .kr { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Reserved */ .highlight-ipynb .kt { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Type */ .highlight-ipynb .m { color: var(--jp-mirror-editor-number-color) } /* Literal.Number */ .highlight-ipynb .s { color: var(--jp-mirror-editor-string-color) } /* Literal.String */ .highlight-ipynb .ow { color: var(--jp-mirror-editor-operator-color); font-weight: bold } /* Operator.Word */ .highlight-ipynb .pm { color: var(--jp-mirror-editor-punctuation-color) } /* Punctuation.Marker */ .highlight-ipynb .w { color: var(--jp-mirror-editor-variable-color) } /* Text.Whitespace */ .highlight-ipynb .mb { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Bin */ .highlight-ipynb .mf { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Float */ .highlight-ipynb .mh { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Hex */ .highlight-ipynb .mi { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Integer */ .highlight-ipynb .mo { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Oct */ .highlight-ipynb .sa { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Affix */ .highlight-ipynb .sb { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Backtick */ .highlight-ipynb .sc { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Char */ .highlight-ipynb .dl { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Delimiter */ .highlight-ipynb .sd { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Doc */ .highlight-ipynb .s2 { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Double */ .highlight-ipynb .se { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Escape */ .highlight-ipynb .sh { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Heredoc */ .highlight-ipynb .si { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Interpol */ .highlight-ipynb .sx { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Other */ .highlight-ipynb .sr { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Regex */ .highlight-ipynb .s1 { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Single */ .highlight-ipynb .ss { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Symbol */ .highlight-ipynb .il { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Integer.Long */ /* This file is taken from the built JupyterLab theme.css Found on share/nbconvert/templates/lab/static Some changes have been made and marked with CHANGE */ .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. 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When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(0, 0, 0, 1); --jp-ui-font-color1: rgba(0, 0, 0, 0.87); --jp-ui-font-color2: rgba(0, 0, 0, 0.54); --jp-ui-font-color3: rgba(0, 0, 0, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color1: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color2: rgba(255, 255, 255, 0.7); --jp-ui-inverse-font-color3: rgba(255, 255, 255, 0.5); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(0, 0, 0, 1); --jp-content-font-color1: rgba(0, 0, 0, 0.87); --jp-content-font-color2: rgba(0, 0, 0, 0.54); --jp-content-font-color3: rgba(0, 0, 0, 0.38); --jp-content-link-color: var(--md-blue-700); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: white; --jp-layout-color1: white; --jp-layout-color2: var(--md-grey-200); --jp-layout-color3: var(--md-grey-400); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: #111111; --jp-inverse-layout-color1: var(--md-grey-900); --jp-inverse-layout-color2: var(--md-grey-800); --jp-inverse-layout-color3: var(--md-grey-700); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-900); --jp-brand-color1: var(--md-blue-700); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-900); --jp-accent-color1: var(--md-green-700); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-900); --jp-warn-color1: var(--md-orange-700); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-900); --jp-error-color1: var(--md-red-700); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-900); --jp-success-color1: var(--md-green-700); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-900); --jp-info-color1: var(--md-cyan-700); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--md-grey-100); --jp-cell-editor-border-color: var(--md-grey-300); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 0.5; --jp-cell-prompt-not-active-font-color: var(--md-grey-700); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: var(--md-blue-50); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: #fdd; --jp-rendermime-table-row-background: var(--md-grey-100); --jp-rendermime-table-row-hover-background: var(--md-light-blue-50); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.25); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color1); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.24); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--md-grey-300); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color1); --jp-input-hover-background: var(--jp-layout-color1); --jp-input-background: var(--md-grey-100); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: #d9d9d9; --jp-editor-selected-focused-background: #d7d4f0; --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: #008000; --jp-mirror-editor-atom-color: #88f; --jp-mirror-editor-number-color: #080; --jp-mirror-editor-def-color: #00f; --jp-mirror-editor-variable-color: var(--md-grey-900); --jp-mirror-editor-variable-2-color: #05a; --jp-mirror-editor-variable-3-color: #085; --jp-mirror-editor-punctuation-color: #05a; --jp-mirror-editor-property-color: #05a; --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ba2121; --jp-mirror-editor-string-2-color: #708; --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: #008000; --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: #170; --jp-mirror-editor-attribute-color: #00c; --jp-mirror-editor-header-color: blue; --jp-mirror-editor-quote-color: #090; --jp-mirror-editor-link-color: #00c; --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: white; /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.5; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(245, 200, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } [data-md-color-scheme=\"slate\"] .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ /* The dark theme shadows need a bit of work, but this will probably also require work on the core layout * colors used in the theme as well. */ --jp-shadow-base-lightness: 32; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-700); --jp-border-color1: var(--md-grey-700); --jp-border-color2: var(--md-grey-800); --jp-border-color3: var(--md-grey-900); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(255, 255, 255, 1); --jp-ui-font-color1: rgba(255, 255, 255, 0.87); --jp-ui-font-color2: rgba(255, 255, 255, 0.54); --jp-ui-font-color3: rgba(255, 255, 255, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(0, 0, 0, 1); --jp-ui-inverse-font-color1: rgba(0, 0, 0, 0.8); --jp-ui-inverse-font-color2: rgba(0, 0, 0, 0.5); --jp-ui-inverse-font-color3: rgba(0, 0, 0, 0.3); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(255, 255, 255, 1); --jp-content-font-color1: rgba(255, 255, 255, 1); --jp-content-font-color2: rgba(255, 255, 255, 0.7); --jp-content-font-color3: rgba(255, 255, 255, 0.5); --jp-content-link-color: var(--md-blue-300); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: #111111; --jp-layout-color1: var(--md-grey-900); --jp-layout-color2: var(--md-grey-800); --jp-layout-color3: var(--md-grey-700); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: white; --jp-inverse-layout-color1: white; --jp-inverse-layout-color2: var(--md-grey-200); --jp-inverse-layout-color3: var(--md-grey-400); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-700); --jp-brand-color1: var(--md-blue-500); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-700); --jp-accent-color1: var(--md-green-500); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-700); --jp-warn-color1: var(--md-orange-500); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-700); --jp-error-color1: var(--md-red-500); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-700); --jp-success-color1: var(--md-green-500); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-700); --jp-info-color1: var(--md-cyan-500); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--jp-layout-color1); --jp-cell-editor-border-color: var(--md-grey-700); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 1; --jp-cell-prompt-not-active-font-color: var(--md-grey-300); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: rgba(33, 150, 243, 0.24); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: rgba(244, 67, 54, 0.28); --jp-rendermime-table-row-background: var(--md-grey-900); --jp-rendermime-table-row-hover-background: rgba(3, 169, 244, 0.2); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.6); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color2); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.8); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--jp-layout-color0); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color0); --jp-input-hover-background: var(--jp-layout-color2); --jp-input-background: var(--md-grey-800); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: var(--jp-layout-color2); --jp-editor-selected-focused-background: rgba(33, 150, 243, 0.24); --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: var(--md-green-500); --jp-mirror-editor-atom-color: var(--md-blue-300); --jp-mirror-editor-number-color: var(--md-green-400); --jp-mirror-editor-def-color: var(--md-blue-600); --jp-mirror-editor-variable-color: var(--md-grey-300); --jp-mirror-editor-variable-2-color: var(--md-blue-400); --jp-mirror-editor-variable-3-color: var(--md-green-600); --jp-mirror-editor-punctuation-color: var(--md-blue-400); --jp-mirror-editor-property-color: var(--md-blue-400); --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ff7070; --jp-mirror-editor-string-2-color: var(--md-purple-300); --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: var(--md-green-600); --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: var(--md-green-700); --jp-mirror-editor-attribute-color: var(--md-blue-700); --jp-mirror-editor-header-color: var(--md-blue-500); --jp-mirror-editor-quote-color: var(--md-green-300); --jp-mirror-editor-link-color: var(--md-blue-700); --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: var(--md-grey-400); /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.6; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(255, 225, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* scrollbar related styles. Supports every browser except Edge. */ /* colors based on JetBrain's Darcula theme */ --jp-scrollbar-background-color: #3f4244; --jp-scrollbar-thumb-color: 88, 96, 97; /* need to specify thumb color as an RGB triplet */ --jp-scrollbar-endpad: 3px; /* the minimum gap between the thumb and the ends of a scrollbar */ /* hacks for setting the thumb shape. These do nothing in Firefox */ --jp-scrollbar-thumb-margin: 3.5px; /* the space in between the sides of the thumb and the track */ --jp-scrollbar-thumb-radius: 9px; /* set to a large-ish value for rounded endcaps on the thumb */ /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } :root{--md-red-50: #ffebee;--md-red-100: #ffcdd2;--md-red-200: #ef9a9a;--md-red-300: #e57373;--md-red-400: #ef5350;--md-red-500: #f44336;--md-red-600: #e53935;--md-red-700: #d32f2f;--md-red-800: #c62828;--md-red-900: #b71c1c;--md-red-A100: #ff8a80;--md-red-A200: #ff5252;--md-red-A400: #ff1744;--md-red-A700: #d50000;--md-pink-50: #fce4ec;--md-pink-100: #f8bbd0;--md-pink-200: #f48fb1;--md-pink-300: #f06292;--md-pink-400: #ec407a;--md-pink-500: #e91e63;--md-pink-600: #d81b60;--md-pink-700: #c2185b;--md-pink-800: #ad1457;--md-pink-900: #880e4f;--md-pink-A100: #ff80ab;--md-pink-A200: #ff4081;--md-pink-A400: #f50057;--md-pink-A700: #c51162;--md-purple-50: #f3e5f5;--md-purple-100: #e1bee7;--md-purple-200: #ce93d8;--md-purple-300: #ba68c8;--md-purple-400: #ab47bc;--md-purple-500: #9c27b0;--md-purple-600: #8e24aa;--md-purple-700: #7b1fa2;--md-purple-800: #6a1b9a;--md-purple-900: #4a148c;--md-purple-A100: #ea80fc;--md-purple-A200: #e040fb;--md-purple-A400: #d500f9;--md-purple-A700: #aa00ff;--md-deep-purple-50: #ede7f6;--md-deep-purple-100: #d1c4e9;--md-deep-purple-200: #b39ddb;--md-deep-purple-300: #9575cd;--md-deep-purple-400: #7e57c2;--md-deep-purple-500: #673ab7;--md-deep-purple-600: #5e35b1;--md-deep-purple-700: #512da8;--md-deep-purple-800: #4527a0;--md-deep-purple-900: #311b92;--md-deep-purple-A100: #b388ff;--md-deep-purple-A200: #7c4dff;--md-deep-purple-A400: #651fff;--md-deep-purple-A700: #6200ea;--md-indigo-50: #e8eaf6;--md-indigo-100: #c5cae9;--md-indigo-200: #9fa8da;--md-indigo-300: #7986cb;--md-indigo-400: #5c6bc0;--md-indigo-500: #3f51b5;--md-indigo-600: #3949ab;--md-indigo-700: #303f9f;--md-indigo-800: #283593;--md-indigo-900: #1a237e;--md-indigo-A100: #8c9eff;--md-indigo-A200: #536dfe;--md-indigo-A400: #3d5afe;--md-indigo-A700: #304ffe;--md-blue-50: #e3f2fd;--md-blue-100: #bbdefb;--md-blue-200: #90caf9;--md-blue-300: #64b5f6;--md-blue-400: #42a5f5;--md-blue-500: #2196f3;--md-blue-600: #1e88e5;--md-blue-700: #1976d2;--md-blue-800: #1565c0;--md-blue-900: #0d47a1;--md-blue-A100: #82b1ff;--md-blue-A200: #448aff;--md-blue-A400: #2979ff;--md-blue-A700: #2962ff;--md-light-blue-50: #e1f5fe;--md-light-blue-100: #b3e5fc;--md-light-blue-200: #81d4fa;--md-light-blue-300: #4fc3f7;--md-light-blue-400: #29b6f6;--md-light-blue-500: #03a9f4;--md-light-blue-600: #039be5;--md-light-blue-700: #0288d1;--md-light-blue-800: #0277bd;--md-light-blue-900: #01579b;--md-light-blue-A100: #80d8ff;--md-light-blue-A200: #40c4ff;--md-light-blue-A400: #00b0ff;--md-light-blue-A700: #0091ea;--md-cyan-50: #e0f7fa;--md-cyan-100: #b2ebf2;--md-cyan-200: #80deea;--md-cyan-300: #4dd0e1;--md-cyan-400: #26c6da;--md-cyan-500: #00bcd4;--md-cyan-600: #00acc1;--md-cyan-700: #0097a7;--md-cyan-800: #00838f;--md-cyan-900: #006064;--md-cyan-A100: #84ffff;--md-cyan-A200: #18ffff;--md-cyan-A400: #00e5ff;--md-cyan-A700: #00b8d4;--md-teal-50: #e0f2f1;--md-teal-100: #b2dfdb;--md-teal-200: #80cbc4;--md-teal-300: #4db6ac;--md-teal-400: #26a69a;--md-teal-500: #009688;--md-teal-600: #00897b;--md-teal-700: #00796b;--md-teal-800: #00695c;--md-teal-900: #004d40;--md-teal-A100: #a7ffeb;--md-teal-A200: #64ffda;--md-teal-A400: #1de9b6;--md-teal-A700: #00bfa5;--md-green-50: #e8f5e9;--md-green-100: #c8e6c9;--md-green-200: #a5d6a7;--md-green-300: #81c784;--md-green-400: #66bb6a;--md-green-500: #4caf50;--md-green-600: #43a047;--md-green-700: #388e3c;--md-green-800: #2e7d32;--md-green-900: #1b5e20;--md-green-A100: #b9f6ca;--md-green-A200: #69f0ae;--md-green-A400: #00e676;--md-green-A700: 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sourceMappingURL=mkdocs-jupyter.css.map*/ init_mathjax = function() { if (window.MathJax) { // MathJax loaded MathJax.Hub.Config({ TeX: { equationNumbers: { autoNumber: \"AMS\", useLabelIds: true } }, tex2jax: { inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ], displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ], processEscapes: true, processEnvironments: true }, displayAlign: 'center', CommonHTML: { linebreaks: { automatic: true } } }); MathJax.Hub.Queue([\"Typeset\", MathJax.Hub]); } } init_mathjax(); In [ ]: Copied! def define_env ( env ): \"\"\" Set up specific environment for documentation site, with some convenience macro's. Available custom mkdocs-macros that produce Markdown content: { sobek_um(anchor, linktext) }: (deep)link to SOBEK User Manual PDF. { dflowfm_um(anchor, linktext) }: (deep)link to D-Flow FM User Manual PDF. { gh_issue(number, linktext) }: link to GitHub issue page. { gh_pr(number, linktext) }: link to GitHub pull request page. { gh_repo(path, linktext) }: link to a file's page in the GitHub repo. \"\"\" dflowfm_um_url = ( \"https://content.oss.deltares.nl/delft3dfm1d2d/D-Flow_FM_User_Manual_1D2D.pdf\" ) sobek_um_url = \"https://content.oss.deltares.nl/sobek2/SOBEK_User_Manual.pdf\" hydrolib_core_url = \"https://github.com/Deltares/HYDROLIB-core\" def _get_url ( url : str , anchor : str = None ): return url + ( \"#\" + anchor if anchor else \"\" ) @env . macro def dflowfm_um ( anchor : str = \"\" , linktext : str = \"D-Flow FM UM\" ): \"\"\"Create Markdown link for D-Flow FM User Manual, with optional anchor/bookmark.\"\"\" return \"[\" + linktext + \"](\" + _get_url ( dflowfm_um_url , anchor ) + \")\" @env . macro def sobek_um ( anchor : str = \"\" , linktext : str = \"SOBEK UM\" ): \"\"\"Create Markdown link for SOBEK User Manual, with optional anchor/bookmark.\"\"\" return \"[\" + linktext + \"](\" + _get_url ( sobek_um_url , anchor ) + \")\" @env . macro def gh_issue ( number : int , linktext : str = None ): \"\"\"Create Markdown link to GitHub issue page.\"\"\" return ( \"[\" + ( linktext or \"#\" + str ( number )) + \"](\" + hydrolib_core_url + \"/issues/\" + str ( number ) + \")\" ) @env . macro def gh_pr ( number : int , linktext : str = None ): \"\"\"Create Markdown link to GitHub pull request page.\"\"\" return ( \"[\" + ( linktext or \"#\" + str ( number )) + \"](\" + hydrolib_core_url + \"/pull/\" + str ( number ) + \")\" ) @env . macro def gh_repo ( path : str , linktext : str = None ): \"\"\"Create Markdown link to a file's page in the GitHub repo.\"\"\" return ( \"[\" + ( linktext or \"#\" + path ) + \"](\" + hydrolib_core_url + \"/blob/main/\" + path + \")\" ) def define_env(env): \"\"\" Set up specific environment for documentation site, with some convenience macro's. Available custom mkdocs-macros that produce Markdown content: { sobek_um(anchor, linktext) }: (deep)link to SOBEK User Manual PDF. { dflowfm_um(anchor, linktext) }: (deep)link to D-Flow FM User Manual PDF. { gh_issue(number, linktext) }: link to GitHub issue page. { gh_pr(number, linktext) }: link to GitHub pull request page. { gh_repo(path, linktext) }: link to a file's page in the GitHub repo. \"\"\" dflowfm_um_url = ( \"https://content.oss.deltares.nl/delft3dfm1d2d/D-Flow_FM_User_Manual_1D2D.pdf\" ) sobek_um_url = \"https://content.oss.deltares.nl/sobek2/SOBEK_User_Manual.pdf\" hydrolib_core_url = \"https://github.com/Deltares/HYDROLIB-core\" def _get_url(url: str, anchor: str = None): return url + (\"#\" + anchor if anchor else \"\") @env.macro def dflowfm_um(anchor: str = \"\", linktext: str = \"D-Flow FM UM\"): \"\"\"Create Markdown link for D-Flow FM User Manual, with optional anchor/bookmark.\"\"\" return \"[\" + linktext + \"](\" + _get_url(dflowfm_um_url, anchor) + \")\" @env.macro def sobek_um(anchor: str = \"\", linktext: str = \"SOBEK UM\"): \"\"\"Create Markdown link for SOBEK User Manual, with optional anchor/bookmark.\"\"\" return \"[\" + linktext + \"](\" + _get_url(sobek_um_url, anchor) + \")\" @env.macro def gh_issue(number: int, linktext: str = None): \"\"\"Create Markdown link to GitHub issue page.\"\"\" return ( \"[\" + (linktext or \"#\" + str(number)) + \"](\" + hydrolib_core_url + \"/issues/\" + str(number) + \")\" ) @env.macro def gh_pr(number: int, linktext: str = None): \"\"\"Create Markdown link to GitHub pull request page.\"\"\" return ( \"[\" + (linktext or \"#\" + str(number)) + \"](\" + hydrolib_core_url + \"/pull/\" + str(number) + \")\" ) @env.macro def gh_repo(path: str, linktext: str = None): \"\"\"Create Markdown link to a file's page in the GitHub repo.\"\"\" return ( \"[\" + (linktext or \"#\" + path) + \"](\" + hydrolib_core_url + \"/blob/main/\" + path + \")\" )","title":"Main"},{"location":"reference/api/","text":"API \u00b6 Much of HYDROLIB-core's classes that represent input data are based on BaseModel and FileModel . These build upon the pydantic package for data validation. BaseModel and FileModel \u00b6 Here we define our Pydantic BaseModel with custom settings, as well as a FileModel that inherits from a BaseModel but also represents a file on disk. BaseModel ( BaseModel ) pydantic-model \u00b6 Config \u00b6 alias_generator ( string : str ) -> str \u00b6 Construct a key name from a given field name. The given field name may be a Pydantic Field alias, and the key name is intended to be used as a BaseModel class member variable name. Parameters: Name Type Description Default string str input field name required Source code in hydrolib/core/basemodel.py def to_key ( string : str ) -> str : \"\"\" Construct a key name from a given field name. The given field name may be a Pydantic Field alias, and the key name is intended to be used as a BaseModel class member variable name. Args: string (str): input field name \"\"\" # First replace any leading digits, because those are undesirable # in variable names. digitdict = { \"0\" : \"zero\" , \"1\" : \"one\" , \"2\" : \"two\" , \"3\" : \"three\" , \"4\" : \"four\" , \"5\" : \"five\" , \"6\" : \"six\" , \"7\" : \"seven\" , \"8\" : \"eight\" , \"9\" : \"nine\" , } m = re . search ( r \"^\\d+\" , string ) if m : digitstring = string [ 0 : m . end ()] for key , val in digitdict . items (): digitstring = digitstring . replace ( key , val ) string = digitstring + string [ m . end () :] # Next, replace spaces and hyphens in the potential variable name. return string . lower () . replace ( \" \" , \"_\" ) . replace ( \"-\" , \"\" ) __init__ ( self , ** data : Any ) -> None special \u00b6 Initialize a BaseModel with the provided data. Exceptions: Type Description ValidationError A validation error when the data is invalid. Source code in hydrolib/core/basemodel.py def __init__ ( self , ** data : Any ) -> None : \"\"\"Initialize a BaseModel with the provided data. Raises: ValidationError: A validation error when the data is invalid. \"\"\" try : super () . __init__ ( ** data ) except ValidationError as e : # Give a special message for faulty list input for re in e . raw_errors : if ( hasattr ( re , \"_loc\" ) and hasattr ( re . exc , \"msg_template\" ) and isinstance ( data . get ( to_key ( re . _loc )), list ) ): re . exc . msg_template += ( f \". The key { re . _loc } might be duplicated in the input file.\" ) # Update error with specific model location name identifier = self . _get_identifier ( data ) if identifier is None : raise e else : # If there is an identifier, include this in the ValidationError messages. raise ValidationError ([ ErrorWrapper ( e , loc = identifier )], self . __class__ ) is_file_link ( self ) -> bool \u00b6 Generic attribute for models backed by a file. Source code in hydrolib/core/basemodel.py def is_file_link ( self ) -> bool : \"\"\"Generic attribute for models backed by a file.\"\"\" return False is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/basemodel.py def is_intermediate_link ( self ) -> bool : \"\"\"Generic attribute for models that have children fields that could contain files.\"\"\" return self . is_file_link () show_tree ( self , indent = 0 ) \u00b6 Recursive print function for showing a tree of a model. Source code in hydrolib/core/basemodel.py def show_tree ( self , indent = 0 ): \"\"\"Recursive print function for showing a tree of a model.\"\"\" angle = \"\u221f\" if indent > 0 else \"\" # Only print if we're backed by a file if self . is_file_link (): print ( \" \" * indent * 2 , angle , self ) # Otherwise we recurse through the fields of a model for _ , value in self : # Handle lists of items if not isinstance ( value , list ): value = [ value ] for v in value : if hasattr ( v , \"is_intermediate_link\" ) and v . is_intermediate_link (): # If the field is only an intermediate, print the name only if not v . is_file_link (): print ( \" \" * ( indent * 2 + 2 ), angle , v . __class__ . __name__ ) v . show_tree ( indent + 1 ) DiskOnlyFileModel ( FileModel ) pydantic-model \u00b6 DiskOnlyFileModel provides a stub implementation for file based models which are not explicitly implemented within hydrolib.core. It implements the FileModel with a void parser and serializer, and a save method which copies the file associated with the FileModel to a new location if it exists. We further explicitly assume that when the filepath is None, no file will be written. Actual file model implementations should not inherit from the DiskOnlyFileModel and instead inherit directly from FileModel. is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/basemodel.py def is_intermediate_link ( self ) -> bool : # If the filepath is not None, there is an underlying file, and as such we need # to traverse it. return self . filepath is not None FileCasingResolver \u00b6 Class for resolving file path in a case-insensitive manner. resolve ( self , path : Path ) -> Path \u00b6 Resolve the casing of a file path when the file does exist but not with the exact casing. Parameters: Name Type Description Default path Path The path of the file or directory for which the casing needs to be resolved. required Returns: Type Description Path The file path with the matched casing if a match exists; otherwise, the original file path. Exceptions: Type Description NotImplementedError When this function is called with an operating system other than Windows, Linux or MacOS. Source code in hydrolib/core/basemodel.py def resolve ( self , path : Path ) -> Path : \"\"\"Resolve the casing of a file path when the file does exist but not with the exact casing. Args: path (Path): The path of the file or directory for which the casing needs to be resolved. Returns: Path: The file path with the matched casing if a match exists; otherwise, the original file path. Raises: NotImplementedError: When this function is called with an operating system other than Windows, Linux or MacOS. \"\"\" operating_system = get_operating_system () if operating_system == OperatingSystem . WINDOWS : return self . _resolve_casing_windows ( path ) if operating_system == OperatingSystem . LINUX : return self . _resolve_casing_linux ( path ) if operating_system == OperatingSystem . MACOS : return self . _resolve_casing_macos ( path ) else : raise NotImplementedError ( f \"Path case resolving for operating system { operating_system } is not supported yet.\" ) FileLoadContext \u00b6 FileLoadContext provides the context necessary to resolve paths during the init of a FileModel, as well as ensure the relevant models are only read once. __init__ ( self ) -> None special \u00b6 Create a new empty FileLoadContext. Source code in hydrolib/core/basemodel.py def __init__ ( self ) -> None : \"\"\"Create a new empty FileLoadContext.\"\"\" self . _path_resolver = FilePathResolver () self . _cache = FileModelCache () self . _file_casing_resolver = FileCasingResolver () self . _file_path_style_converter = FilePathStyleConverter () self . _load_settings : Optional [ ModelLoadSettings ] = None cache_is_empty ( self ) -> bool \u00b6 Whether or not the file model cache is empty. Returns: Type Description bool Whether or not the file model cache is empty. Source code in hydrolib/core/basemodel.py def cache_is_empty ( self ) -> bool : \"\"\"Whether or not the file model cache is empty. Returns: bool: Whether or not the file model cache is empty. \"\"\" return self . _cache . is_empty () convert_path_style ( self , file_path : Path ) -> Path \u00b6 Resolve the file path by converting it from its own file path style to the path style for the current operating system. Parameters: Name Type Description Default file_path Path The file path to convert to the OS path style. required Returns: Type Description Path The resolved file path. Source code in hydrolib/core/basemodel.py def convert_path_style ( self , file_path : Path ) -> Path : \"\"\"Resolve the file path by converting it from its own file path style to the path style for the current operating system. Args: file_path (Path): The file path to convert to the OS path style. Returns: Path: The resolved file path. \"\"\" if file_path . is_absolute (): return file_path converted_file_path = self . _file_path_style_converter . convert_to_os_style ( file_path , self . load_settings . path_style ) return Path ( converted_file_path ) get_current_parent ( self ) -> Path \u00b6 Get the current absolute path with which files are resolved. If the current mode is relative to the parent, the latest added parent is added. If the current mode is relative to an anchor path, the latest added anchor path is returned. Returns: Type Description Path The absolute path to the current parent. Source code in hydrolib/core/basemodel.py def get_current_parent ( self ) -> Path : \"\"\"Get the current absolute path with which files are resolved. If the current mode is relative to the parent, the latest added parent is added. If the current mode is relative to an anchor path, the latest added anchor path is returned. Returns: Path: The absolute path to the current parent. \"\"\" return self . _path_resolver . get_current_parent () initialize_load_settings ( self , recurse : bool , resolve_casing : bool , path_style : PathStyle ) \u00b6 Initialize the global model load setting. Can only be set once. Parameters: Name Type Description Default recurse bool Whether or not to recursively load the whole model. required resolve_casing bool Whether or not to resolve the file casing. required path_style PathStyle Which path style is used in the loaded files. required Source code in hydrolib/core/basemodel.py def initialize_load_settings ( self , recurse : bool , resolve_casing : bool , path_style : PathStyle ): \"\"\"Initialize the global model load setting. Can only be set once. Args: recurse (bool): Whether or not to recursively load the whole model. resolve_casing (bool): Whether or not to resolve the file casing. path_style (PathStyle): Which path style is used in the loaded files. \"\"\" if self . _load_settings is None : self . _load_settings = ModelLoadSettings ( recurse , resolve_casing , path_style ) load_settings : ModelLoadSettings property readonly \u00b6 Gets the model load settings. Exceptions: Type Description ValueError When the model load settings have not been initialized yet. Returns: Type Description ModelLoadSettings The model load settings. pop_last_parent ( self ) -> None \u00b6 Pop the last added parent off this FileLoadContext. Source code in hydrolib/core/basemodel.py def pop_last_parent ( self ) -> None : \"\"\"Pop the last added parent off this FileLoadContext.\"\"\" self . _path_resolver . pop_last_parent () push_new_parent ( self , parent_path : Path , relative_mode : ResolveRelativeMode ) -> None \u00b6 Push a new parent_path with the given relative_mode on this FileLoadContext. Parameters: Name Type Description Default parent_path Path The parent path to be added to this FileLoadContext. required relative_mode ResolveRelativeMode The relative mode. required Source code in hydrolib/core/basemodel.py def push_new_parent ( self , parent_path : Path , relative_mode : ResolveRelativeMode ) -> None : \"\"\"Push a new parent_path with the given relative_mode on this FileLoadContext. Args: parent_path (Path): The parent path to be added to this FileLoadContext. relative_mode (ResolveRelativeMode): The relative mode. \"\"\" self . _path_resolver . push_new_parent ( parent_path , relative_mode ) register_model ( self , path : Path , model : FileModel ) -> None \u00b6 Associate the provided model with the provided path. Relative paths will be resolved based on the current state of the FileLoadContext. Parameters: Name Type Description Default path Path The relative path from which the model was loaded. required model FileModel The loaded model. required Source code in hydrolib/core/basemodel.py def register_model ( self , path : Path , model : \"FileModel\" ) -> None : \"\"\"Associate the provided model with the provided path. Relative paths will be resolved based on the current state of the FileLoadContext. Args: path (Path): The relative path from which the model was loaded. model (FileModel): The loaded model. \"\"\" absolute_path = self . _path_resolver . resolve ( path ) self . _cache . register_model ( absolute_path , model ) resolve ( self , path : Path ) -> Path \u00b6 Resolve the provided path. If path is already absolute, it will be returned as is. Otherwise it will be resolved based on the current state of this FileLoadContext. Parameters: Name Type Description Default path Path The path to be resolved. required Returns: Type Description Path An absolute path resolved based on the current state. Source code in hydrolib/core/basemodel.py def resolve ( self , path : Path ) -> Path : \"\"\"Resolve the provided path. If path is already absolute, it will be returned as is. Otherwise it will be resolved based on the current state of this FileLoadContext. Args: path (Path): The path to be resolved. Returns: Path: An absolute path resolved based on the current state. \"\"\" return self . _path_resolver . resolve ( path ) resolve_casing ( self , file_path : Path ) -> Path \u00b6 Resolve the file casing for the provided file path. Parameters: Name Type Description Default file_path Path The file path to resolve the casing for. required Returns: Type Description Path The resolved file path. Source code in hydrolib/core/basemodel.py def resolve_casing ( self , file_path : Path ) -> Path : \"\"\"Resolve the file casing for the provided file path. Args: file_path (Path): The file path to resolve the casing for. Returns: Path: The resolved file path. \"\"\" if self . load_settings . resolve_casing : return self . _file_casing_resolver . resolve ( file_path ) return file_path retrieve_model ( self , path : Optional [ pathlib . Path ]) -> Optional [ FileModel ] \u00b6 Retrieve the model associated with the path. If no model has been associated with the provided path, or the path is None, then None will be returned. Relative paths will be resolved based on the current state of the FileLoadContext. Returns: Type Description [Optional[FileModel]] The file model associated with the provided path if it has been registered, else None. Source code in hydrolib/core/basemodel.py def retrieve_model ( self , path : Optional [ Path ]) -> Optional [ \"FileModel\" ]: \"\"\"Retrieve the model associated with the path. If no model has been associated with the provided path, or the path is None, then None will be returned. Relative paths will be resolved based on the current state of the FileLoadContext. Returns: [Optional[FileModel]]: The file model associated with the provided path if it has been registered, else None. \"\"\" if path is None : return None absolute_path = self . _path_resolver . resolve ( path ) return self . _cache . retrieve_model ( absolute_path ) FileModel ( BaseModel , ABC ) pydantic-model \u00b6 Base class to represent models with a file representation. It therefore always has a filepath and if it is given on initilization, it will parse that file. The filepath can be relative, in which case the paths are expected to be resolved relative to some root model. If a path is absolute, this path will always be used, regardless of a root parent. When saving a model, if the current filepath is relative, the last resolved absolute path will be used. If the model has just been read, the This class extends the validate option of Pydantic, so when when a Path is given to a field with type FileModel , it doesn't error, but actually initializes the FileModel . Attributes: Name Type Description filepath Optional[Path] The path of this FileModel. This path can be either absolute or relative. If it is a relative path, it is assumed to be resolved from some root model. save_location Path A readonly property corresponding with the (current) save location of this FileModel. If read from a file or after saving recursively or after calling synchronize_filepath, this value will be updated to its new state. If made from memory and filepath is not set, it will correspond with cwd / filename.extension __init__ ( self , filepath : Union [ pathlib . Path , str ] = None , resolve_casing : bool = False , recurse : bool = True , path_style : Optional [ str ] = None , * args , ** kwargs ) special \u00b6 Create a new FileModel from the given filepath. If no filepath is provided, the model is initialized as an empty model with default values. If the filepath is provided, it is read from disk. Parameters: Name Type Description Default filepath Optional[PathOrStr] The file path. Defaults to None. None resolve_casing bool Whether or not to resolve the file name references so that they match the case with what is on disk. Defaults to False. False recurse bool Whether or not to recursively load the model. Defaults to True. True path_style Optional[str] Which path style is used in the loaded files. Defaults to the path style that matches the current operating system. Options: 'unix', 'windows'. None Exceptions: Type Description ValueError When an unsupported path style is passed. Source code in hydrolib/core/basemodel.py def __init__ ( self , filepath : Optional [ PathOrStr ] = None , resolve_casing : bool = False , recurse : bool = True , path_style : Optional [ str ] = None , * args , ** kwargs , ): \"\"\"Create a new FileModel from the given filepath. If no filepath is provided, the model is initialized as an empty model with default values. If the filepath is provided, it is read from disk. Args: filepath (Optional[PathOrStr], optional): The file path. Defaults to None. resolve_casing (bool, optional): Whether or not to resolve the file name references so that they match the case with what is on disk. Defaults to False. recurse (bool, optional): Whether or not to recursively load the model. Defaults to True. path_style (Optional[str], optional): Which path style is used in the loaded files. Defaults to the path style that matches the current operating system. Options: 'unix', 'windows'. Raises: ValueError: When an unsupported path style is passed. \"\"\" if not filepath : super () . __init__ ( * args , ** kwargs ) return filepath = FileModel . _change_to_path ( filepath ) path_style = path_style_validator . validate ( path_style ) with file_load_context () as context : context . initialize_load_settings ( recurse , resolve_casing , path_style ) filepath = context . convert_path_style ( filepath ) if not FileModel . _should_load_model ( context ): super () . __init__ ( * args , ** kwargs ) self . filepath = filepath return self . _absolute_anchor_path = context . get_current_parent () loading_path = context . resolve ( filepath ) loading_path = context . resolve_casing ( loading_path ) if context . load_settings . resolve_casing : filepath = self . _get_updated_file_path ( filepath , loading_path ) logger . info ( f \"Loading data from { filepath } \" ) data = self . _load ( loading_path ) context . register_model ( filepath , self ) data [ \"filepath\" ] = filepath kwargs . update ( data ) context . register_model ( filepath , self ) # Note: the relative mode needs to be obtained from the data directly # because self._relative_mode has not been resolved yet (this is done as # part of the __init__), however during the __init__ we need to already # have pushed the new parent. As such we cannot move this call later. relative_mode = self . _get_relative_mode_from_data ( data ) context . push_new_parent ( filepath . parent , relative_mode ) super () . __init__ ( * args , ** kwargs ) self . _post_init_load () context . pop_last_parent () __new__ ( cls , filepath : Union [ pathlib . Path , str ] = None , * args , ** kwargs ) special staticmethod \u00b6 Create a new model. If the file at the provided file path was already parsed, this instance is returned. Parameters: Name Type Description Default filepath Optional[PathOrStr] The file path to the file. Defaults to None. None Returns: Type Description FileModel A file model. Source code in hydrolib/core/basemodel.py def __new__ ( cls , filepath : Optional [ PathOrStr ] = None , * args , ** kwargs ): \"\"\"Create a new model. If the file at the provided file path was already parsed, this instance is returned. Args: filepath (Optional[PathOrStr], optional): The file path to the file. Defaults to None. Returns: FileModel: A file model. \"\"\" filepath = FileModel . _change_to_path ( filepath ) with file_load_context () as context : if ( file_model := context . retrieve_model ( filepath )) is not None : return file_model else : return super () . __new__ ( cls ) is_file_link ( self ) -> bool \u00b6 Generic attribute for models backed by a file. Source code in hydrolib/core/basemodel.py def is_file_link ( self ) -> bool : return True save ( self , filepath : Optional [ pathlib . Path ] = None , recurse : bool = False , path_style : Optional [ str ] = None ) -> None \u00b6 Save the model to disk. If recurse is set to True, all of the child FileModels will be saved as well. Relative child models are stored relative to this Model, according to the model file hierarchy specified with the respective filepaths. Absolute paths will be written to their respective locations. Note that this will overwrite any existing files that are stored in this location. Note that if recurse is set to True, the save_location properties of the children are updated to their respective new locations. If filepath it is specified, the filepath of this FileModel is set to the specified path before the save operation is executed. If none is specified it will use the current filepath. If the used filepath is relative, it will be stored at the current save_location. If you only want to save a child model of some root model, it is recommended to first call synchronize_filepaths on the root model, to ensure the child model's save_location is correctly determined. Parameters: Name Type Description Default filepath Optional[Path] The file path at which this model is saved. If None is specified it defaults to the filepath currently stored in the filemodel. Defaults to None. None recurse bool Whether to save all children of this FileModel (when set to True), or only save this model (when set to False). Defaults to False. False path_style Optional[str] With which file path style to save the model. File references will be written with the specified path style. Defaults to the path style used by the current operating system. Options: 'unix', 'windows'. None Exceptions: Type Description ValueError When an unsupported path style is passed. Source code in hydrolib/core/basemodel.py def save ( self , filepath : Optional [ Path ] = None , recurse : bool = False , path_style : Optional [ str ] = None , ) -> None : \"\"\"Save the model to disk. If recurse is set to True, all of the child FileModels will be saved as well. Relative child models are stored relative to this Model, according to the model file hierarchy specified with the respective filepaths. Absolute paths will be written to their respective locations. Note that this will overwrite any existing files that are stored in this location. Note that if recurse is set to True, the save_location properties of the children are updated to their respective new locations. If filepath it is specified, the filepath of this FileModel is set to the specified path before the save operation is executed. If none is specified it will use the current filepath. If the used filepath is relative, it will be stored at the current save_location. If you only want to save a child model of some root model, it is recommended to first call synchronize_filepaths on the root model, to ensure the child model's save_location is correctly determined. Args: filepath (Optional[Path], optional): The file path at which this model is saved. If None is specified it defaults to the filepath currently stored in the filemodel. Defaults to None. recurse (bool, optional): Whether to save all children of this FileModel (when set to True), or only save this model (when set to False). Defaults to False. path_style (Optional[str], optional): With which file path style to save the model. File references will be written with the specified path style. Defaults to the path style used by the current operating system. Options: 'unix', 'windows'. Raises: ValueError: When an unsupported path style is passed. \"\"\" if filepath is not None : self . filepath = filepath path_style = path_style_validator . validate ( path_style ) save_settings = ModelSaveSettings ( path_style = path_style ) # Handle save with file_load_context () as context : context . push_new_parent ( self . _absolute_anchor_path , self . _relative_mode ) if recurse : self . _save_tree ( context , save_settings ) else : self . _save_instance ( save_settings ) save_location : Optional [ pathlib . Path ] property readonly \u00b6 Get the current save location which will be used when calling save() This value can be None if the filepath is None and no name can be generated. Returns: Type Description Path The location at which this model will be saved. synchronize_filepaths ( self ) -> None \u00b6 Synchronize the save_location properties of all child models respective to this FileModel's save_location. Source code in hydrolib/core/basemodel.py def synchronize_filepaths ( self ) -> None : \"\"\"Synchronize the save_location properties of all child models respective to this FileModel's save_location. \"\"\" def sync_pre ( model : BaseModel , acc : FileLoadContext ) -> FileLoadContext : if isinstance ( model , FileModel ): acc . push_new_parent ( model . filepath . parent , model . _relative_mode ) # type: ignore[arg-type] return acc def sync_post ( model : BaseModel , acc : FileLoadContext ) -> FileLoadContext : if isinstance ( model , FileModel ): acc . pop_last_parent () model . _absolute_anchor_path = acc . get_current_parent () return acc traverser = ModelTreeTraverser [ FileLoadContext ]( should_traverse = _should_traverse , should_execute = _should_execute , pre_traverse_func = sync_pre , post_traverse_func = sync_post , ) with file_load_context () as context : context . push_new_parent ( self . _absolute_anchor_path , self . _relative_mode ) traverser . traverse ( self , context ) FileModelCache \u00b6 FileModelCache provides a simple structure to register and retrieve FileModel objects. __init__ ( self ) special \u00b6 Create a new empty FileModelCache. Source code in hydrolib/core/basemodel.py def __init__ ( self ): \"\"\"Create a new empty FileModelCache.\"\"\" self . _cache_dict : Dict [ Path , \"FileModel\" ] = {} is_empty ( self ) -> bool \u00b6 Whether or not this file model cache is empty. Returns: Type Description bool Whether or not the cache is empty. Source code in hydrolib/core/basemodel.py def is_empty ( self ) -> bool : \"\"\"Whether or not this file model cache is empty. Returns: bool: Whether or not the cache is empty. \"\"\" return not any ( self . _cache_dict ) register_model ( self , path : Path , model : FileModel ) -> None \u00b6 Register the model with the specified path in this FileModelCache. Parameters: Name Type Description Default path Path The path to associate the model with. required model FileModel The model to be associated with the path. required Source code in hydrolib/core/basemodel.py def register_model ( self , path : Path , model : \"FileModel\" ) -> None : \"\"\"Register the model with the specified path in this FileModelCache. Args: path (Path): The path to associate the model with. model (FileModel): The model to be associated with the path. \"\"\" self . _cache_dict [ path ] = model retrieve_model ( self , path : Path ) -> Optional [ FileModel ] \u00b6 Retrieve the model associated with the (absolute) path if it has been registered before, otherwise return None. Returns: Type Description [Optional[FileModel]] The FileModel associated with the Path if it has been registered before, otherwise None. Source code in hydrolib/core/basemodel.py def retrieve_model ( self , path : Path ) -> Optional [ \"FileModel\" ]: \"\"\"Retrieve the model associated with the (absolute) path if it has been registered before, otherwise return None. Returns: [Optional[FileModel]]: The FileModel associated with the Path if it has been registered before, otherwise None. \"\"\" return self . _cache_dict . get ( path , None ) FilePathResolver \u00b6 FilePathResolver is responsible for resolving relative paths. The current state to which paths are resolved can be altered by pushing a new parent path to the FilePathResolver, or removing the latest added parent path from the FilePathResolver __init__ ( self ) -> None special \u00b6 Create a new empty FilePathResolver. Source code in hydrolib/core/basemodel.py def __init__ ( self ) -> None : \"\"\"Create a new empty FilePathResolver.\"\"\" self . _anchors : List [ Path ] = [] self . _parents : List [ Tuple [ Path , ResolveRelativeMode ]] = [] get_current_parent ( self ) -> Path \u00b6 Get the current absolute path with which files are resolved. If the current mode is relative to the parent, the latest added parent is added. If the current mode is relative to an anchor path, the latest added anchor path is returned. Returns: Type Description Path The absolute path to the current parent. Source code in hydrolib/core/basemodel.py def get_current_parent ( self ) -> Path : \"\"\"Get the current absolute path with which files are resolved. If the current mode is relative to the parent, the latest added parent is added. If the current mode is relative to an anchor path, the latest added anchor path is returned. Returns: Path: The absolute path to the current parent. \"\"\" if self . _anchor : return self . _anchor return self . _direct_parent pop_last_parent ( self ) -> None \u00b6 Pop the last added parent from this FilePathResolver If there are currently no parents defined, nothing will happen. Source code in hydrolib/core/basemodel.py def pop_last_parent ( self ) -> None : \"\"\"Pop the last added parent from this FilePathResolver If there are currently no parents defined, nothing will happen. \"\"\" if not self . _parents : return _ , relative_mode = self . _parents . pop () if relative_mode == ResolveRelativeMode . ToAnchor : self . _anchors . pop () push_new_parent ( self , parent_path : Path , relative_mode : ResolveRelativeMode ) -> None \u00b6 Push a new parent_path with the given relative_mode to this FilePathResolver. Relative paths added to this FilePathResolver will be resolved with respect to the current state, i.e. similar to FilePathResolver.resolve. Parameters: Name Type Description Default parent_path Path The parent path required relative_mode ResolveRelativeMode The relative mode used to resolve. required Source code in hydrolib/core/basemodel.py def push_new_parent ( self , parent_path : Path , relative_mode : ResolveRelativeMode ) -> None : \"\"\"Push a new parent_path with the given relative_mode to this FilePathResolver. Relative paths added to this FilePathResolver will be resolved with respect to the current state, i.e. similar to FilePathResolver.resolve. Args: parent_path (Path): The parent path relative_mode (ResolveRelativeMode): The relative mode used to resolve. \"\"\" absolute_parent_path = self . resolve ( parent_path ) if relative_mode == ResolveRelativeMode . ToAnchor : self . _anchors . append ( absolute_parent_path ) self . _parents . append (( absolute_parent_path , relative_mode )) resolve ( self , path : Path ) -> Path \u00b6 Resolve the provided path to an absolute path given the current state. If the provided path is already absolute, it will be returned as is. Parameters: Name Type Description Default path Path The path to resolve required Returns: Type Description Path An absolute path resolved given the current state. Source code in hydrolib/core/basemodel.py def resolve ( self , path : Path ) -> Path : \"\"\"Resolve the provided path to an absolute path given the current state. If the provided path is already absolute, it will be returned as is. Args: path (Path): The path to resolve Returns: Path: An absolute path resolved given the current state. \"\"\" if path . is_absolute (): return path parent = self . get_current_parent () return ( parent / path ) . resolve () ModelLoadSettings \u00b6 A class that holds the global settings for model loading. __init__ ( self , recurse : bool , resolve_casing : bool , path_style : PathStyle ) -> None special \u00b6 Initializes a new instance of the ModelLoadSettings class. Parameters: Name Type Description Default recurse bool Whether or not to recursively load the whole model. required resolve_casing bool Whether or not to resolve the file casing. required path_style PathStyle Which path style is used in the loaded files. required Source code in hydrolib/core/basemodel.py def __init__ ( self , recurse : bool , resolve_casing : bool , path_style : PathStyle ) -> None : \"\"\"Initializes a new instance of the ModelLoadSettings class. Args: recurse (bool): Whether or not to recursively load the whole model. resolve_casing (bool): Whether or not to resolve the file casing. path_style (PathStyle): Which path style is used in the loaded files. \"\"\" self . _recurse = recurse self . _resolve_casing = resolve_casing self . _path_style = path_style path_style : PathStyle property readonly \u00b6 Gets the path style setting. Returns: Type Description PathStyle Which path style is used in the loaded files. recurse : bool property readonly \u00b6 Gets the recurse setting. Returns: Type Description bool Whether or not to recursively load the whole model. resolve_casing : bool property readonly \u00b6 Gets the resolve casing setting. Returns: Type Description bool Whether or not to resolve the file casing. ModelSaveSettings \u00b6 A class that holds the global settings for model saving. __init__ ( self , path_style : Optional [ hydrolib . core . utils . PathStyle ] = None ) -> None special \u00b6 Initializes a new instance of the ModelSaveSettings class. Parameters: Name Type Description Default path_style Optional[PathStyle] Which file path style to use when saving the model. Defaults to the path style that matches the current operating system. None Source code in hydrolib/core/basemodel.py def __init__ ( self , path_style : Optional [ PathStyle ] = None ) -> None : \"\"\"Initializes a new instance of the ModelSaveSettings class. Args: path_style (Optional[PathStyle], optional): Which file path style to use when saving the model. Defaults to the path style that matches the current operating system. \"\"\" if path_style is None : path_style = self . _os_path_style self . _path_style = path_style path_style : PathStyle property readonly \u00b6 Gets the path style setting. Returns: Type Description PathStyle Which path style is used to save the files. ModelTreeTraverser ( Generic ) \u00b6 ModelTreeTraverser is responsible for traversing a ModelTree using the provided functions. The ModelTreeTraverser will only traverse BaseModel and derived objects. Type parameter TAcc defines the type of Accumulator to be used. __init__ ( self , should_traverse : Optional [ Callable [[ hydrolib . core . basemodel . BaseModel , ~ TAcc ], bool ]] = None , should_execute : Optional [ Callable [[ hydrolib . core . basemodel . BaseModel , ~ TAcc ], bool ]] = None , pre_traverse_func : Optional [ Callable [[ hydrolib . core . basemodel . BaseModel , ~ TAcc ], ~ TAcc ]] = None , post_traverse_func : Optional [ Callable [[ hydrolib . core . basemodel . BaseModel , ~ TAcc ], ~ TAcc ]] = None ) special \u00b6 Create a new ModelTreeTraverser with the given functions. If a predicate it is not defined, it is assumed to always be true, i.e. we will always traverse to the next node, or always execute the traverse functions. If a traverse function is not defined, it will be skipped. The traverse functions share an accumulator, i.e. the accumulator argument is passed through all evaluated traverse functions. It is expected that the traverse function return the (potentially) changed accumulator. Parameters: Name Type Description Default should_traverse Optional[Callable[[BaseModel, TAcc], bool]] Function to evaluate whether to traverse to the provided BaseModel. Defaults to None. None should_execute Optional[Callable[[BaseModel, TAcc], bool]] Function to evaluate whether to execute the traverse functions for the provided BaseModel. Defaults to None. None pre_traverse_func Callable[[BaseModel, TAcc], TAcc] Traverse function executed before we traverse into the next BaseModel, i.e. top-down traversal. Defaults to None. None post_traverse_func Callable[[BaseModel, TAcc], TAcc] Traverse function executed after we traverse into the next BaseModel, i.e. bottom-up traversal. Defaults to None. None Source code in hydrolib/core/basemodel.py def __init__ ( self , should_traverse : Optional [ Callable [[ BaseModel , TAcc ], bool ]] = None , should_execute : Optional [ Callable [[ BaseModel , TAcc ], bool ]] = None , pre_traverse_func : Optional [ Callable [[ BaseModel , TAcc ], TAcc ]] = None , post_traverse_func : Optional [ Callable [[ BaseModel , TAcc ], TAcc ]] = None , ): \"\"\"Create a new ModelTreeTraverser with the given functions. If a predicate it is not defined, it is assumed to always be true, i.e. we will always traverse to the next node, or always execute the traverse functions. If a traverse function is not defined, it will be skipped. The traverse functions share an accumulator, i.e. the accumulator argument is passed through all evaluated traverse functions. It is expected that the traverse function return the (potentially) changed accumulator. Args: should_traverse (Optional[Callable[[BaseModel, TAcc], bool]], optional): Function to evaluate whether to traverse to the provided BaseModel. Defaults to None. should_execute (Optional[Callable[[BaseModel, TAcc], bool]], optional): Function to evaluate whether to execute the traverse functions for the provided BaseModel. Defaults to None. pre_traverse_func (Callable[[BaseModel, TAcc], TAcc], optional): Traverse function executed before we traverse into the next BaseModel, i.e. top-down traversal. Defaults to None. post_traverse_func (Callable[[BaseModel, TAcc], TAcc], optional): Traverse function executed after we traverse into the next BaseModel, i.e. bottom-up traversal. Defaults to None. \"\"\" self . _should_traverse_func = should_traverse self . _should_execute_func = should_execute self . _pre_traverse_func = pre_traverse_func self . _post_traverse_func = post_traverse_func traverse ( self , model : BaseModel , acc : ~ TAcc ) -> ~ TAcc \u00b6 Traverse the model tree of BaseModels including the model as the root, with the provided state of the acc and return the final accumulator. The actual executed functions as well as the predicates defining whether these functions should be executed for this model as well as whether child BaseModel objects should be traversed are provided in the constructor of the ModelTreeTraverser. The final accumulator is returned. Parameters: Name Type Description Default model BaseModel The root model in which the traversal of the model tree starts. required acc TAcc The current accumulator. required Returns: Type Description TAcc The accumulator after the traversal of the model tree. Source code in hydrolib/core/basemodel.py def traverse ( self , model : BaseModel , acc : TAcc ) -> TAcc : \"\"\"Traverse the model tree of BaseModels including the model as the root, with the provided state of the acc and return the final accumulator. The actual executed functions as well as the predicates defining whether these functions should be executed for this model as well as whether child BaseModel objects should be traversed are provided in the constructor of the ModelTreeTraverser. The final accumulator is returned. Args: model (BaseModel): The root model in which the traversal of the model tree starts. acc (TAcc): The current accumulator. Returns: TAcc: The accumulator after the traversal of the model tree. \"\"\" if self . _should_execute_pre ( model , acc ): acc = self . _pre_traverse_func ( model , acc ) # type: ignore[arg-type] for _ , value in model : if not isinstance ( value , list ): value = [ value ] for v in value : if self . _should_traverse ( v , acc ): acc = self . traverse ( v , acc ) if self . _should_execute_post ( model , acc ): acc = self . _post_traverse_func ( model , acc ) # type: ignore[arg-type] return acc ParsableFileModel ( FileModel ) pydantic-model \u00b6 ParsableFileModel defines a FileModel which can be parsed and serialized with a serializer . Each ParsableFileModel has a default _filename and _ext, which are used to generate the file name of any instance where the filepath is not (yet) set. Children of the ParsableFileModel are expected to implement a serializer function which takes a Path and Dict and writes the ParsableFileModel to disk, and a parser function which takes a Path and outputs a Dict. If more complicated solutions are required, a ParsableFileModel child can also opt to overwrite the _serialize and _parse methods, to skip the _get_serializer and _get_parser methods respectively. dict ( self , * args , ** kwargs ) \u00b6 Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/basemodel.py def dict ( self , * args , ** kwargs ): kwargs [ \"exclude\" ] = self . _exclude_fields () return super () . dict ( * args , ** kwargs ) PathStyleValidator \u00b6 Class to take care of path style validation. validate ( self , path_style : Optional [ str ]) -> PathStyle \u00b6 Validates the path style as string on whether it is a supported path style. If it is a valid path style the path style enum value will be return as a result. Parameters: Name Type Description Default path_style Optional[str] The path style as string value. required Returns: Type Description PathStyle The converted PathStyle object. Exceptions: Type Description ValueError When an unsupported path style is passed. Source code in hydrolib/core/basemodel.py def validate ( self , path_style : Optional [ str ]) -> PathStyle : \"\"\"Validates the path style as string on whether it is a supported path style. If it is a valid path style the path style enum value will be return as a result. Args: path_style (Optional[str]): The path style as string value. Returns: PathStyle: The converted PathStyle object. Raises: ValueError: When an unsupported path style is passed. \"\"\" if path_style is None : return self . _os_path_style supported_path_styles = list ( PathStyle ) if path_style in supported_path_styles : return PathStyle ( path_style ) supported_path_style_str = \", \" . join (([ x . value for x in supported_path_styles ])) raise ValueError ( f \"Path style ' { path_style } ' not supported. Supported path styles: { supported_path_style_str } \" ) ResolveRelativeMode ( IntEnum ) \u00b6 ResolveRelativeMode defines the possible resolve modes used within the FilePathResolver. It determines how the relative paths to child models within some FileModel should be interpreted. By default it should be relative to the parent model, i.e. the model in which the mode is defined. However there exist some exceptions, where the relative paths should be evaluated relative to some other folder, regardless of the current parent location. Options Toparent Relative paths should be resolved relative to their direct parent model. Toanchor All relative paths should be resolved relative to the specified regardless of subsequent parent model locations. SerializerConfig ( BaseModel , ABC ) pydantic-model \u00b6 Class that holds the configuration settings for serialization. file_load_context () \u00b6 Provide a FileLoadingContext. If none has been created in the context of this call stack yet, a new one will be created, which will be maintained until it goes out of scope. Yields [FileLoadContext]: The file load context. Source code in hydrolib/core/basemodel.py @contextmanager def file_load_context (): \"\"\"Provide a FileLoadingContext. If none has been created in the context of this call stack yet, a new one will be created, which will be maintained until it goes out of scope. Yields: [FileLoadContext]: The file load context. \"\"\" file_loading_context = context_file_loading . get ( None ) context_reset_token = None if not file_loading_context : file_loading_context = FileLoadContext () context_reset_token = context_file_loading . set ( file_loading_context ) try : yield file_loading_context finally : if context_reset_token is not None : context_file_loading . reset ( context_reset_token ) validator_set_default_disk_only_file_model_when_none () -> classmethod \u00b6 Validator to ensure a default empty DiskOnlyFileModel is created when the corresponding field is initialized with None. Returns: Type Description classmethod Validator to adjust None values to empty DiskOnlyFileModel objects Source code in hydrolib/core/basemodel.py def validator_set_default_disk_only_file_model_when_none () -> classmethod : \"\"\"Validator to ensure a default empty DiskOnlyFileModel is created when the corresponding field is initialized with None. Returns: classmethod: Validator to adjust None values to empty DiskOnlyFileModel objects \"\"\" def adjust_none ( v : Any , field : ModelField ) -> Any : if field . type_ is DiskOnlyFileModel and v is None : return { \"filepath\" : None } return v return validator ( \"*\" , allow_reuse = True , pre = True )( adjust_none )","title":"API"},{"location":"reference/api/#api","text":"Much of HYDROLIB-core's classes that represent input data are based on BaseModel and FileModel . These build upon the pydantic package for data validation.","title":"API"},{"location":"reference/api/#basemodel-and-filemodel","text":"Here we define our Pydantic BaseModel with custom settings, as well as a FileModel that inherits from a BaseModel but also represents a file on disk.","title":"BaseModel and FileModel"},{"location":"reference/api/#hydrolib.core.basemodel.BaseModel","text":"","title":"BaseModel"},{"location":"reference/api/#hydrolib.core.basemodel.BaseModel.Config","text":"","title":"Config"},{"location":"reference/api/#hydrolib.core.basemodel.BaseModel.Config.alias_generator","text":"Construct a key name from a given field name. The given field name may be a Pydantic Field alias, and the key name is intended to be used as a BaseModel class member variable name. Parameters: Name Type Description Default string str input field name required Source code in hydrolib/core/basemodel.py def to_key ( string : str ) -> str : \"\"\" Construct a key name from a given field name. The given field name may be a Pydantic Field alias, and the key name is intended to be used as a BaseModel class member variable name. Args: string (str): input field name \"\"\" # First replace any leading digits, because those are undesirable # in variable names. digitdict = { \"0\" : \"zero\" , \"1\" : \"one\" , \"2\" : \"two\" , \"3\" : \"three\" , \"4\" : \"four\" , \"5\" : \"five\" , \"6\" : \"six\" , \"7\" : \"seven\" , \"8\" : \"eight\" , \"9\" : \"nine\" , } m = re . search ( r \"^\\d+\" , string ) if m : digitstring = string [ 0 : m . end ()] for key , val in digitdict . items (): digitstring = digitstring . replace ( key , val ) string = digitstring + string [ m . end () :] # Next, replace spaces and hyphens in the potential variable name. return string . lower () . replace ( \" \" , \"_\" ) . replace ( \"-\" , \"\" )","title":"alias_generator()"},{"location":"reference/api/#hydrolib.core.basemodel.BaseModel.__init__","text":"Initialize a BaseModel with the provided data. Exceptions: Type Description ValidationError A validation error when the data is invalid. Source code in hydrolib/core/basemodel.py def __init__ ( self , ** data : Any ) -> None : \"\"\"Initialize a BaseModel with the provided data. Raises: ValidationError: A validation error when the data is invalid. \"\"\" try : super () . __init__ ( ** data ) except ValidationError as e : # Give a special message for faulty list input for re in e . raw_errors : if ( hasattr ( re , \"_loc\" ) and hasattr ( re . exc , \"msg_template\" ) and isinstance ( data . get ( to_key ( re . _loc )), list ) ): re . exc . msg_template += ( f \". The key { re . _loc } might be duplicated in the input file.\" ) # Update error with specific model location name identifier = self . _get_identifier ( data ) if identifier is None : raise e else : # If there is an identifier, include this in the ValidationError messages. raise ValidationError ([ ErrorWrapper ( e , loc = identifier )], self . __class__ )","title":"__init__()"},{"location":"reference/api/#hydrolib.core.basemodel.BaseModel.is_file_link","text":"Generic attribute for models backed by a file. Source code in hydrolib/core/basemodel.py def is_file_link ( self ) -> bool : \"\"\"Generic attribute for models backed by a file.\"\"\" return False","title":"is_file_link()"},{"location":"reference/api/#hydrolib.core.basemodel.BaseModel.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/basemodel.py def is_intermediate_link ( self ) -> bool : \"\"\"Generic attribute for models that have children fields that could contain files.\"\"\" return self . is_file_link ()","title":"is_intermediate_link()"},{"location":"reference/api/#hydrolib.core.basemodel.BaseModel.show_tree","text":"Recursive print function for showing a tree of a model. Source code in hydrolib/core/basemodel.py def show_tree ( self , indent = 0 ): \"\"\"Recursive print function for showing a tree of a model.\"\"\" angle = \"\u221f\" if indent > 0 else \"\" # Only print if we're backed by a file if self . is_file_link (): print ( \" \" * indent * 2 , angle , self ) # Otherwise we recurse through the fields of a model for _ , value in self : # Handle lists of items if not isinstance ( value , list ): value = [ value ] for v in value : if hasattr ( v , \"is_intermediate_link\" ) and v . is_intermediate_link (): # If the field is only an intermediate, print the name only if not v . is_file_link (): print ( \" \" * ( indent * 2 + 2 ), angle , v . __class__ . __name__ ) v . show_tree ( indent + 1 )","title":"show_tree()"},{"location":"reference/api/#hydrolib.core.basemodel.DiskOnlyFileModel","text":"DiskOnlyFileModel provides a stub implementation for file based models which are not explicitly implemented within hydrolib.core. It implements the FileModel with a void parser and serializer, and a save method which copies the file associated with the FileModel to a new location if it exists. We further explicitly assume that when the filepath is None, no file will be written. Actual file model implementations should not inherit from the DiskOnlyFileModel and instead inherit directly from FileModel.","title":"DiskOnlyFileModel"},{"location":"reference/api/#hydrolib.core.basemodel.DiskOnlyFileModel.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/basemodel.py def is_intermediate_link ( self ) -> bool : # If the filepath is not None, there is an underlying file, and as such we need # to traverse it. return self . filepath is not None","title":"is_intermediate_link()"},{"location":"reference/api/#hydrolib.core.basemodel.FileCasingResolver","text":"Class for resolving file path in a case-insensitive manner.","title":"FileCasingResolver"},{"location":"reference/api/#hydrolib.core.basemodel.FileCasingResolver.resolve","text":"Resolve the casing of a file path when the file does exist but not with the exact casing. Parameters: Name Type Description Default path Path The path of the file or directory for which the casing needs to be resolved. required Returns: Type Description Path The file path with the matched casing if a match exists; otherwise, the original file path. Exceptions: Type Description NotImplementedError When this function is called with an operating system other than Windows, Linux or MacOS. Source code in hydrolib/core/basemodel.py def resolve ( self , path : Path ) -> Path : \"\"\"Resolve the casing of a file path when the file does exist but not with the exact casing. Args: path (Path): The path of the file or directory for which the casing needs to be resolved. Returns: Path: The file path with the matched casing if a match exists; otherwise, the original file path. Raises: NotImplementedError: When this function is called with an operating system other than Windows, Linux or MacOS. \"\"\" operating_system = get_operating_system () if operating_system == OperatingSystem . WINDOWS : return self . _resolve_casing_windows ( path ) if operating_system == OperatingSystem . LINUX : return self . _resolve_casing_linux ( path ) if operating_system == OperatingSystem . MACOS : return self . _resolve_casing_macos ( path ) else : raise NotImplementedError ( f \"Path case resolving for operating system { operating_system } is not supported yet.\" )","title":"resolve()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext","text":"FileLoadContext provides the context necessary to resolve paths during the init of a FileModel, as well as ensure the relevant models are only read once.","title":"FileLoadContext"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.__init__","text":"Create a new empty FileLoadContext. Source code in hydrolib/core/basemodel.py def __init__ ( self ) -> None : \"\"\"Create a new empty FileLoadContext.\"\"\" self . _path_resolver = FilePathResolver () self . _cache = FileModelCache () self . _file_casing_resolver = FileCasingResolver () self . _file_path_style_converter = FilePathStyleConverter () self . _load_settings : Optional [ ModelLoadSettings ] = None","title":"__init__()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.cache_is_empty","text":"Whether or not the file model cache is empty. Returns: Type Description bool Whether or not the file model cache is empty. Source code in hydrolib/core/basemodel.py def cache_is_empty ( self ) -> bool : \"\"\"Whether or not the file model cache is empty. Returns: bool: Whether or not the file model cache is empty. \"\"\" return self . _cache . is_empty ()","title":"cache_is_empty()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.convert_path_style","text":"Resolve the file path by converting it from its own file path style to the path style for the current operating system. Parameters: Name Type Description Default file_path Path The file path to convert to the OS path style. required Returns: Type Description Path The resolved file path. Source code in hydrolib/core/basemodel.py def convert_path_style ( self , file_path : Path ) -> Path : \"\"\"Resolve the file path by converting it from its own file path style to the path style for the current operating system. Args: file_path (Path): The file path to convert to the OS path style. Returns: Path: The resolved file path. \"\"\" if file_path . is_absolute (): return file_path converted_file_path = self . _file_path_style_converter . convert_to_os_style ( file_path , self . load_settings . path_style ) return Path ( converted_file_path )","title":"convert_path_style()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.get_current_parent","text":"Get the current absolute path with which files are resolved. If the current mode is relative to the parent, the latest added parent is added. If the current mode is relative to an anchor path, the latest added anchor path is returned. Returns: Type Description Path The absolute path to the current parent. Source code in hydrolib/core/basemodel.py def get_current_parent ( self ) -> Path : \"\"\"Get the current absolute path with which files are resolved. If the current mode is relative to the parent, the latest added parent is added. If the current mode is relative to an anchor path, the latest added anchor path is returned. Returns: Path: The absolute path to the current parent. \"\"\" return self . _path_resolver . get_current_parent ()","title":"get_current_parent()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.initialize_load_settings","text":"Initialize the global model load setting. Can only be set once. Parameters: Name Type Description Default recurse bool Whether or not to recursively load the whole model. required resolve_casing bool Whether or not to resolve the file casing. required path_style PathStyle Which path style is used in the loaded files. required Source code in hydrolib/core/basemodel.py def initialize_load_settings ( self , recurse : bool , resolve_casing : bool , path_style : PathStyle ): \"\"\"Initialize the global model load setting. Can only be set once. Args: recurse (bool): Whether or not to recursively load the whole model. resolve_casing (bool): Whether or not to resolve the file casing. path_style (PathStyle): Which path style is used in the loaded files. \"\"\" if self . _load_settings is None : self . _load_settings = ModelLoadSettings ( recurse , resolve_casing , path_style )","title":"initialize_load_settings()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.load_settings","text":"Gets the model load settings. Exceptions: Type Description ValueError When the model load settings have not been initialized yet. Returns: Type Description ModelLoadSettings The model load settings.","title":"load_settings"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.pop_last_parent","text":"Pop the last added parent off this FileLoadContext. Source code in hydrolib/core/basemodel.py def pop_last_parent ( self ) -> None : \"\"\"Pop the last added parent off this FileLoadContext.\"\"\" self . _path_resolver . pop_last_parent ()","title":"pop_last_parent()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.push_new_parent","text":"Push a new parent_path with the given relative_mode on this FileLoadContext. Parameters: Name Type Description Default parent_path Path The parent path to be added to this FileLoadContext. required relative_mode ResolveRelativeMode The relative mode. required Source code in hydrolib/core/basemodel.py def push_new_parent ( self , parent_path : Path , relative_mode : ResolveRelativeMode ) -> None : \"\"\"Push a new parent_path with the given relative_mode on this FileLoadContext. Args: parent_path (Path): The parent path to be added to this FileLoadContext. relative_mode (ResolveRelativeMode): The relative mode. \"\"\" self . _path_resolver . push_new_parent ( parent_path , relative_mode )","title":"push_new_parent()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.register_model","text":"Associate the provided model with the provided path. Relative paths will be resolved based on the current state of the FileLoadContext. Parameters: Name Type Description Default path Path The relative path from which the model was loaded. required model FileModel The loaded model. required Source code in hydrolib/core/basemodel.py def register_model ( self , path : Path , model : \"FileModel\" ) -> None : \"\"\"Associate the provided model with the provided path. Relative paths will be resolved based on the current state of the FileLoadContext. Args: path (Path): The relative path from which the model was loaded. model (FileModel): The loaded model. \"\"\" absolute_path = self . _path_resolver . resolve ( path ) self . _cache . register_model ( absolute_path , model )","title":"register_model()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.resolve","text":"Resolve the provided path. If path is already absolute, it will be returned as is. Otherwise it will be resolved based on the current state of this FileLoadContext. Parameters: Name Type Description Default path Path The path to be resolved. required Returns: Type Description Path An absolute path resolved based on the current state. Source code in hydrolib/core/basemodel.py def resolve ( self , path : Path ) -> Path : \"\"\"Resolve the provided path. If path is already absolute, it will be returned as is. Otherwise it will be resolved based on the current state of this FileLoadContext. Args: path (Path): The path to be resolved. Returns: Path: An absolute path resolved based on the current state. \"\"\" return self . _path_resolver . resolve ( path )","title":"resolve()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.resolve_casing","text":"Resolve the file casing for the provided file path. Parameters: Name Type Description Default file_path Path The file path to resolve the casing for. required Returns: Type Description Path The resolved file path. Source code in hydrolib/core/basemodel.py def resolve_casing ( self , file_path : Path ) -> Path : \"\"\"Resolve the file casing for the provided file path. Args: file_path (Path): The file path to resolve the casing for. Returns: Path: The resolved file path. \"\"\" if self . load_settings . resolve_casing : return self . _file_casing_resolver . resolve ( file_path ) return file_path","title":"resolve_casing()"},{"location":"reference/api/#hydrolib.core.basemodel.FileLoadContext.retrieve_model","text":"Retrieve the model associated with the path. If no model has been associated with the provided path, or the path is None, then None will be returned. Relative paths will be resolved based on the current state of the FileLoadContext. Returns: Type Description [Optional[FileModel]] The file model associated with the provided path if it has been registered, else None. Source code in hydrolib/core/basemodel.py def retrieve_model ( self , path : Optional [ Path ]) -> Optional [ \"FileModel\" ]: \"\"\"Retrieve the model associated with the path. If no model has been associated with the provided path, or the path is None, then None will be returned. Relative paths will be resolved based on the current state of the FileLoadContext. Returns: [Optional[FileModel]]: The file model associated with the provided path if it has been registered, else None. \"\"\" if path is None : return None absolute_path = self . _path_resolver . resolve ( path ) return self . _cache . retrieve_model ( absolute_path )","title":"retrieve_model()"},{"location":"reference/api/#hydrolib.core.basemodel.FileModel","text":"Base class to represent models with a file representation. It therefore always has a filepath and if it is given on initilization, it will parse that file. The filepath can be relative, in which case the paths are expected to be resolved relative to some root model. If a path is absolute, this path will always be used, regardless of a root parent. When saving a model, if the current filepath is relative, the last resolved absolute path will be used. If the model has just been read, the This class extends the validate option of Pydantic, so when when a Path is given to a field with type FileModel , it doesn't error, but actually initializes the FileModel . Attributes: Name Type Description filepath Optional[Path] The path of this FileModel. This path can be either absolute or relative. If it is a relative path, it is assumed to be resolved from some root model. save_location Path A readonly property corresponding with the (current) save location of this FileModel. If read from a file or after saving recursively or after calling synchronize_filepath, this value will be updated to its new state. If made from memory and filepath is not set, it will correspond with cwd / filename.extension","title":"FileModel"},{"location":"reference/api/#hydrolib.core.basemodel.FileModel.__init__","text":"Create a new FileModel from the given filepath. If no filepath is provided, the model is initialized as an empty model with default values. If the filepath is provided, it is read from disk. Parameters: Name Type Description Default filepath Optional[PathOrStr] The file path. Defaults to None. None resolve_casing bool Whether or not to resolve the file name references so that they match the case with what is on disk. Defaults to False. False recurse bool Whether or not to recursively load the model. Defaults to True. True path_style Optional[str] Which path style is used in the loaded files. Defaults to the path style that matches the current operating system. Options: 'unix', 'windows'. None Exceptions: Type Description ValueError When an unsupported path style is passed. Source code in hydrolib/core/basemodel.py def __init__ ( self , filepath : Optional [ PathOrStr ] = None , resolve_casing : bool = False , recurse : bool = True , path_style : Optional [ str ] = None , * args , ** kwargs , ): \"\"\"Create a new FileModel from the given filepath. If no filepath is provided, the model is initialized as an empty model with default values. If the filepath is provided, it is read from disk. Args: filepath (Optional[PathOrStr], optional): The file path. Defaults to None. resolve_casing (bool, optional): Whether or not to resolve the file name references so that they match the case with what is on disk. Defaults to False. recurse (bool, optional): Whether or not to recursively load the model. Defaults to True. path_style (Optional[str], optional): Which path style is used in the loaded files. Defaults to the path style that matches the current operating system. Options: 'unix', 'windows'. Raises: ValueError: When an unsupported path style is passed. \"\"\" if not filepath : super () . __init__ ( * args , ** kwargs ) return filepath = FileModel . _change_to_path ( filepath ) path_style = path_style_validator . validate ( path_style ) with file_load_context () as context : context . initialize_load_settings ( recurse , resolve_casing , path_style ) filepath = context . convert_path_style ( filepath ) if not FileModel . _should_load_model ( context ): super () . __init__ ( * args , ** kwargs ) self . filepath = filepath return self . _absolute_anchor_path = context . get_current_parent () loading_path = context . resolve ( filepath ) loading_path = context . resolve_casing ( loading_path ) if context . load_settings . resolve_casing : filepath = self . _get_updated_file_path ( filepath , loading_path ) logger . info ( f \"Loading data from { filepath } \" ) data = self . _load ( loading_path ) context . register_model ( filepath , self ) data [ \"filepath\" ] = filepath kwargs . update ( data ) context . register_model ( filepath , self ) # Note: the relative mode needs to be obtained from the data directly # because self._relative_mode has not been resolved yet (this is done as # part of the __init__), however during the __init__ we need to already # have pushed the new parent. As such we cannot move this call later. relative_mode = self . _get_relative_mode_from_data ( data ) context . push_new_parent ( filepath . parent , relative_mode ) super () . __init__ ( * args , ** kwargs ) self . _post_init_load () context . pop_last_parent ()","title":"__init__()"},{"location":"reference/api/#hydrolib.core.basemodel.FileModel.__new__","text":"Create a new model. If the file at the provided file path was already parsed, this instance is returned. Parameters: Name Type Description Default filepath Optional[PathOrStr] The file path to the file. Defaults to None. None Returns: Type Description FileModel A file model. Source code in hydrolib/core/basemodel.py def __new__ ( cls , filepath : Optional [ PathOrStr ] = None , * args , ** kwargs ): \"\"\"Create a new model. If the file at the provided file path was already parsed, this instance is returned. Args: filepath (Optional[PathOrStr], optional): The file path to the file. Defaults to None. Returns: FileModel: A file model. \"\"\" filepath = FileModel . _change_to_path ( filepath ) with file_load_context () as context : if ( file_model := context . retrieve_model ( filepath )) is not None : return file_model else : return super () . __new__ ( cls )","title":"__new__()"},{"location":"reference/api/#hydrolib.core.basemodel.FileModel.is_file_link","text":"Generic attribute for models backed by a file. Source code in hydrolib/core/basemodel.py def is_file_link ( self ) -> bool : return True","title":"is_file_link()"},{"location":"reference/api/#hydrolib.core.basemodel.FileModel.save","text":"Save the model to disk. If recurse is set to True, all of the child FileModels will be saved as well. Relative child models are stored relative to this Model, according to the model file hierarchy specified with the respective filepaths. Absolute paths will be written to their respective locations. Note that this will overwrite any existing files that are stored in this location. Note that if recurse is set to True, the save_location properties of the children are updated to their respective new locations. If filepath it is specified, the filepath of this FileModel is set to the specified path before the save operation is executed. If none is specified it will use the current filepath. If the used filepath is relative, it will be stored at the current save_location. If you only want to save a child model of some root model, it is recommended to first call synchronize_filepaths on the root model, to ensure the child model's save_location is correctly determined. Parameters: Name Type Description Default filepath Optional[Path] The file path at which this model is saved. If None is specified it defaults to the filepath currently stored in the filemodel. Defaults to None. None recurse bool Whether to save all children of this FileModel (when set to True), or only save this model (when set to False). Defaults to False. False path_style Optional[str] With which file path style to save the model. File references will be written with the specified path style. Defaults to the path style used by the current operating system. Options: 'unix', 'windows'. None Exceptions: Type Description ValueError When an unsupported path style is passed. Source code in hydrolib/core/basemodel.py def save ( self , filepath : Optional [ Path ] = None , recurse : bool = False , path_style : Optional [ str ] = None , ) -> None : \"\"\"Save the model to disk. If recurse is set to True, all of the child FileModels will be saved as well. Relative child models are stored relative to this Model, according to the model file hierarchy specified with the respective filepaths. Absolute paths will be written to their respective locations. Note that this will overwrite any existing files that are stored in this location. Note that if recurse is set to True, the save_location properties of the children are updated to their respective new locations. If filepath it is specified, the filepath of this FileModel is set to the specified path before the save operation is executed. If none is specified it will use the current filepath. If the used filepath is relative, it will be stored at the current save_location. If you only want to save a child model of some root model, it is recommended to first call synchronize_filepaths on the root model, to ensure the child model's save_location is correctly determined. Args: filepath (Optional[Path], optional): The file path at which this model is saved. If None is specified it defaults to the filepath currently stored in the filemodel. Defaults to None. recurse (bool, optional): Whether to save all children of this FileModel (when set to True), or only save this model (when set to False). Defaults to False. path_style (Optional[str], optional): With which file path style to save the model. File references will be written with the specified path style. Defaults to the path style used by the current operating system. Options: 'unix', 'windows'. Raises: ValueError: When an unsupported path style is passed. \"\"\" if filepath is not None : self . filepath = filepath path_style = path_style_validator . validate ( path_style ) save_settings = ModelSaveSettings ( path_style = path_style ) # Handle save with file_load_context () as context : context . push_new_parent ( self . _absolute_anchor_path , self . _relative_mode ) if recurse : self . _save_tree ( context , save_settings ) else : self . _save_instance ( save_settings )","title":"save()"},{"location":"reference/api/#hydrolib.core.basemodel.FileModel.save_location","text":"Get the current save location which will be used when calling save() This value can be None if the filepath is None and no name can be generated. Returns: Type Description Path The location at which this model will be saved.","title":"save_location"},{"location":"reference/api/#hydrolib.core.basemodel.FileModel.synchronize_filepaths","text":"Synchronize the save_location properties of all child models respective to this FileModel's save_location. Source code in hydrolib/core/basemodel.py def synchronize_filepaths ( self ) -> None : \"\"\"Synchronize the save_location properties of all child models respective to this FileModel's save_location. \"\"\" def sync_pre ( model : BaseModel , acc : FileLoadContext ) -> FileLoadContext : if isinstance ( model , FileModel ): acc . push_new_parent ( model . filepath . parent , model . _relative_mode ) # type: ignore[arg-type] return acc def sync_post ( model : BaseModel , acc : FileLoadContext ) -> FileLoadContext : if isinstance ( model , FileModel ): acc . pop_last_parent () model . _absolute_anchor_path = acc . get_current_parent () return acc traverser = ModelTreeTraverser [ FileLoadContext ]( should_traverse = _should_traverse , should_execute = _should_execute , pre_traverse_func = sync_pre , post_traverse_func = sync_post , ) with file_load_context () as context : context . push_new_parent ( self . _absolute_anchor_path , self . _relative_mode ) traverser . traverse ( self , context )","title":"synchronize_filepaths()"},{"location":"reference/api/#hydrolib.core.basemodel.FileModelCache","text":"FileModelCache provides a simple structure to register and retrieve FileModel objects.","title":"FileModelCache"},{"location":"reference/api/#hydrolib.core.basemodel.FileModelCache.__init__","text":"Create a new empty FileModelCache. Source code in hydrolib/core/basemodel.py def __init__ ( self ): \"\"\"Create a new empty FileModelCache.\"\"\" self . _cache_dict : Dict [ Path , \"FileModel\" ] = {}","title":"__init__()"},{"location":"reference/api/#hydrolib.core.basemodel.FileModelCache.is_empty","text":"Whether or not this file model cache is empty. Returns: Type Description bool Whether or not the cache is empty. Source code in hydrolib/core/basemodel.py def is_empty ( self ) -> bool : \"\"\"Whether or not this file model cache is empty. Returns: bool: Whether or not the cache is empty. \"\"\" return not any ( self . _cache_dict )","title":"is_empty()"},{"location":"reference/api/#hydrolib.core.basemodel.FileModelCache.register_model","text":"Register the model with the specified path in this FileModelCache. Parameters: Name Type Description Default path Path The path to associate the model with. required model FileModel The model to be associated with the path. required Source code in hydrolib/core/basemodel.py def register_model ( self , path : Path , model : \"FileModel\" ) -> None : \"\"\"Register the model with the specified path in this FileModelCache. Args: path (Path): The path to associate the model with. model (FileModel): The model to be associated with the path. \"\"\" self . _cache_dict [ path ] = model","title":"register_model()"},{"location":"reference/api/#hydrolib.core.basemodel.FileModelCache.retrieve_model","text":"Retrieve the model associated with the (absolute) path if it has been registered before, otherwise return None. Returns: Type Description [Optional[FileModel]] The FileModel associated with the Path if it has been registered before, otherwise None. Source code in hydrolib/core/basemodel.py def retrieve_model ( self , path : Path ) -> Optional [ \"FileModel\" ]: \"\"\"Retrieve the model associated with the (absolute) path if it has been registered before, otherwise return None. Returns: [Optional[FileModel]]: The FileModel associated with the Path if it has been registered before, otherwise None. \"\"\" return self . _cache_dict . get ( path , None )","title":"retrieve_model()"},{"location":"reference/api/#hydrolib.core.basemodel.FilePathResolver","text":"FilePathResolver is responsible for resolving relative paths. The current state to which paths are resolved can be altered by pushing a new parent path to the FilePathResolver, or removing the latest added parent path from the FilePathResolver","title":"FilePathResolver"},{"location":"reference/api/#hydrolib.core.basemodel.FilePathResolver.__init__","text":"Create a new empty FilePathResolver. Source code in hydrolib/core/basemodel.py def __init__ ( self ) -> None : \"\"\"Create a new empty FilePathResolver.\"\"\" self . _anchors : List [ Path ] = [] self . _parents : List [ Tuple [ Path , ResolveRelativeMode ]] = []","title":"__init__()"},{"location":"reference/api/#hydrolib.core.basemodel.FilePathResolver.get_current_parent","text":"Get the current absolute path with which files are resolved. If the current mode is relative to the parent, the latest added parent is added. If the current mode is relative to an anchor path, the latest added anchor path is returned. Returns: Type Description Path The absolute path to the current parent. Source code in hydrolib/core/basemodel.py def get_current_parent ( self ) -> Path : \"\"\"Get the current absolute path with which files are resolved. If the current mode is relative to the parent, the latest added parent is added. If the current mode is relative to an anchor path, the latest added anchor path is returned. Returns: Path: The absolute path to the current parent. \"\"\" if self . _anchor : return self . _anchor return self . _direct_parent","title":"get_current_parent()"},{"location":"reference/api/#hydrolib.core.basemodel.FilePathResolver.pop_last_parent","text":"Pop the last added parent from this FilePathResolver If there are currently no parents defined, nothing will happen. Source code in hydrolib/core/basemodel.py def pop_last_parent ( self ) -> None : \"\"\"Pop the last added parent from this FilePathResolver If there are currently no parents defined, nothing will happen. \"\"\" if not self . _parents : return _ , relative_mode = self . _parents . pop () if relative_mode == ResolveRelativeMode . ToAnchor : self . _anchors . pop ()","title":"pop_last_parent()"},{"location":"reference/api/#hydrolib.core.basemodel.FilePathResolver.push_new_parent","text":"Push a new parent_path with the given relative_mode to this FilePathResolver. Relative paths added to this FilePathResolver will be resolved with respect to the current state, i.e. similar to FilePathResolver.resolve. Parameters: Name Type Description Default parent_path Path The parent path required relative_mode ResolveRelativeMode The relative mode used to resolve. required Source code in hydrolib/core/basemodel.py def push_new_parent ( self , parent_path : Path , relative_mode : ResolveRelativeMode ) -> None : \"\"\"Push a new parent_path with the given relative_mode to this FilePathResolver. Relative paths added to this FilePathResolver will be resolved with respect to the current state, i.e. similar to FilePathResolver.resolve. Args: parent_path (Path): The parent path relative_mode (ResolveRelativeMode): The relative mode used to resolve. \"\"\" absolute_parent_path = self . resolve ( parent_path ) if relative_mode == ResolveRelativeMode . ToAnchor : self . _anchors . append ( absolute_parent_path ) self . _parents . append (( absolute_parent_path , relative_mode ))","title":"push_new_parent()"},{"location":"reference/api/#hydrolib.core.basemodel.FilePathResolver.resolve","text":"Resolve the provided path to an absolute path given the current state. If the provided path is already absolute, it will be returned as is. Parameters: Name Type Description Default path Path The path to resolve required Returns: Type Description Path An absolute path resolved given the current state. Source code in hydrolib/core/basemodel.py def resolve ( self , path : Path ) -> Path : \"\"\"Resolve the provided path to an absolute path given the current state. If the provided path is already absolute, it will be returned as is. Args: path (Path): The path to resolve Returns: Path: An absolute path resolved given the current state. \"\"\" if path . is_absolute (): return path parent = self . get_current_parent () return ( parent / path ) . resolve ()","title":"resolve()"},{"location":"reference/api/#hydrolib.core.basemodel.ModelLoadSettings","text":"A class that holds the global settings for model loading.","title":"ModelLoadSettings"},{"location":"reference/api/#hydrolib.core.basemodel.ModelLoadSettings.__init__","text":"Initializes a new instance of the ModelLoadSettings class. Parameters: Name Type Description Default recurse bool Whether or not to recursively load the whole model. required resolve_casing bool Whether or not to resolve the file casing. required path_style PathStyle Which path style is used in the loaded files. required Source code in hydrolib/core/basemodel.py def __init__ ( self , recurse : bool , resolve_casing : bool , path_style : PathStyle ) -> None : \"\"\"Initializes a new instance of the ModelLoadSettings class. Args: recurse (bool): Whether or not to recursively load the whole model. resolve_casing (bool): Whether or not to resolve the file casing. path_style (PathStyle): Which path style is used in the loaded files. \"\"\" self . _recurse = recurse self . _resolve_casing = resolve_casing self . _path_style = path_style","title":"__init__()"},{"location":"reference/api/#hydrolib.core.basemodel.ModelLoadSettings.path_style","text":"Gets the path style setting. Returns: Type Description PathStyle Which path style is used in the loaded files.","title":"path_style"},{"location":"reference/api/#hydrolib.core.basemodel.ModelLoadSettings.recurse","text":"Gets the recurse setting. Returns: Type Description bool Whether or not to recursively load the whole model.","title":"recurse"},{"location":"reference/api/#hydrolib.core.basemodel.ModelLoadSettings.resolve_casing","text":"Gets the resolve casing setting. Returns: Type Description bool Whether or not to resolve the file casing.","title":"resolve_casing"},{"location":"reference/api/#hydrolib.core.basemodel.ModelSaveSettings","text":"A class that holds the global settings for model saving.","title":"ModelSaveSettings"},{"location":"reference/api/#hydrolib.core.basemodel.ModelSaveSettings.__init__","text":"Initializes a new instance of the ModelSaveSettings class. Parameters: Name Type Description Default path_style Optional[PathStyle] Which file path style to use when saving the model. Defaults to the path style that matches the current operating system. None Source code in hydrolib/core/basemodel.py def __init__ ( self , path_style : Optional [ PathStyle ] = None ) -> None : \"\"\"Initializes a new instance of the ModelSaveSettings class. Args: path_style (Optional[PathStyle], optional): Which file path style to use when saving the model. Defaults to the path style that matches the current operating system. \"\"\" if path_style is None : path_style = self . _os_path_style self . _path_style = path_style","title":"__init__()"},{"location":"reference/api/#hydrolib.core.basemodel.ModelSaveSettings.path_style","text":"Gets the path style setting. Returns: Type Description PathStyle Which path style is used to save the files.","title":"path_style"},{"location":"reference/api/#hydrolib.core.basemodel.ModelTreeTraverser","text":"ModelTreeTraverser is responsible for traversing a ModelTree using the provided functions. The ModelTreeTraverser will only traverse BaseModel and derived objects. Type parameter TAcc defines the type of Accumulator to be used.","title":"ModelTreeTraverser"},{"location":"reference/api/#hydrolib.core.basemodel.ModelTreeTraverser.__init__","text":"Create a new ModelTreeTraverser with the given functions. If a predicate it is not defined, it is assumed to always be true, i.e. we will always traverse to the next node, or always execute the traverse functions. If a traverse function is not defined, it will be skipped. The traverse functions share an accumulator, i.e. the accumulator argument is passed through all evaluated traverse functions. It is expected that the traverse function return the (potentially) changed accumulator. Parameters: Name Type Description Default should_traverse Optional[Callable[[BaseModel, TAcc], bool]] Function to evaluate whether to traverse to the provided BaseModel. Defaults to None. None should_execute Optional[Callable[[BaseModel, TAcc], bool]] Function to evaluate whether to execute the traverse functions for the provided BaseModel. Defaults to None. None pre_traverse_func Callable[[BaseModel, TAcc], TAcc] Traverse function executed before we traverse into the next BaseModel, i.e. top-down traversal. Defaults to None. None post_traverse_func Callable[[BaseModel, TAcc], TAcc] Traverse function executed after we traverse into the next BaseModel, i.e. bottom-up traversal. Defaults to None. None Source code in hydrolib/core/basemodel.py def __init__ ( self , should_traverse : Optional [ Callable [[ BaseModel , TAcc ], bool ]] = None , should_execute : Optional [ Callable [[ BaseModel , TAcc ], bool ]] = None , pre_traverse_func : Optional [ Callable [[ BaseModel , TAcc ], TAcc ]] = None , post_traverse_func : Optional [ Callable [[ BaseModel , TAcc ], TAcc ]] = None , ): \"\"\"Create a new ModelTreeTraverser with the given functions. If a predicate it is not defined, it is assumed to always be true, i.e. we will always traverse to the next node, or always execute the traverse functions. If a traverse function is not defined, it will be skipped. The traverse functions share an accumulator, i.e. the accumulator argument is passed through all evaluated traverse functions. It is expected that the traverse function return the (potentially) changed accumulator. Args: should_traverse (Optional[Callable[[BaseModel, TAcc], bool]], optional): Function to evaluate whether to traverse to the provided BaseModel. Defaults to None. should_execute (Optional[Callable[[BaseModel, TAcc], bool]], optional): Function to evaluate whether to execute the traverse functions for the provided BaseModel. Defaults to None. pre_traverse_func (Callable[[BaseModel, TAcc], TAcc], optional): Traverse function executed before we traverse into the next BaseModel, i.e. top-down traversal. Defaults to None. post_traverse_func (Callable[[BaseModel, TAcc], TAcc], optional): Traverse function executed after we traverse into the next BaseModel, i.e. bottom-up traversal. Defaults to None. \"\"\" self . _should_traverse_func = should_traverse self . _should_execute_func = should_execute self . _pre_traverse_func = pre_traverse_func self . _post_traverse_func = post_traverse_func","title":"__init__()"},{"location":"reference/api/#hydrolib.core.basemodel.ModelTreeTraverser.traverse","text":"Traverse the model tree of BaseModels including the model as the root, with the provided state of the acc and return the final accumulator. The actual executed functions as well as the predicates defining whether these functions should be executed for this model as well as whether child BaseModel objects should be traversed are provided in the constructor of the ModelTreeTraverser. The final accumulator is returned. Parameters: Name Type Description Default model BaseModel The root model in which the traversal of the model tree starts. required acc TAcc The current accumulator. required Returns: Type Description TAcc The accumulator after the traversal of the model tree. Source code in hydrolib/core/basemodel.py def traverse ( self , model : BaseModel , acc : TAcc ) -> TAcc : \"\"\"Traverse the model tree of BaseModels including the model as the root, with the provided state of the acc and return the final accumulator. The actual executed functions as well as the predicates defining whether these functions should be executed for this model as well as whether child BaseModel objects should be traversed are provided in the constructor of the ModelTreeTraverser. The final accumulator is returned. Args: model (BaseModel): The root model in which the traversal of the model tree starts. acc (TAcc): The current accumulator. Returns: TAcc: The accumulator after the traversal of the model tree. \"\"\" if self . _should_execute_pre ( model , acc ): acc = self . _pre_traverse_func ( model , acc ) # type: ignore[arg-type] for _ , value in model : if not isinstance ( value , list ): value = [ value ] for v in value : if self . _should_traverse ( v , acc ): acc = self . traverse ( v , acc ) if self . _should_execute_post ( model , acc ): acc = self . _post_traverse_func ( model , acc ) # type: ignore[arg-type] return acc","title":"traverse()"},{"location":"reference/api/#hydrolib.core.basemodel.ParsableFileModel","text":"ParsableFileModel defines a FileModel which can be parsed and serialized with a serializer . Each ParsableFileModel has a default _filename and _ext, which are used to generate the file name of any instance where the filepath is not (yet) set. Children of the ParsableFileModel are expected to implement a serializer function which takes a Path and Dict and writes the ParsableFileModel to disk, and a parser function which takes a Path and outputs a Dict. If more complicated solutions are required, a ParsableFileModel child can also opt to overwrite the _serialize and _parse methods, to skip the _get_serializer and _get_parser methods respectively.","title":"ParsableFileModel"},{"location":"reference/api/#hydrolib.core.basemodel.ParsableFileModel.dict","text":"Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/basemodel.py def dict ( self , * args , ** kwargs ): kwargs [ \"exclude\" ] = self . _exclude_fields () return super () . dict ( * args , ** kwargs )","title":"dict()"},{"location":"reference/api/#hydrolib.core.basemodel.PathStyleValidator","text":"Class to take care of path style validation.","title":"PathStyleValidator"},{"location":"reference/api/#hydrolib.core.basemodel.PathStyleValidator.validate","text":"Validates the path style as string on whether it is a supported path style. If it is a valid path style the path style enum value will be return as a result. Parameters: Name Type Description Default path_style Optional[str] The path style as string value. required Returns: Type Description PathStyle The converted PathStyle object. Exceptions: Type Description ValueError When an unsupported path style is passed. Source code in hydrolib/core/basemodel.py def validate ( self , path_style : Optional [ str ]) -> PathStyle : \"\"\"Validates the path style as string on whether it is a supported path style. If it is a valid path style the path style enum value will be return as a result. Args: path_style (Optional[str]): The path style as string value. Returns: PathStyle: The converted PathStyle object. Raises: ValueError: When an unsupported path style is passed. \"\"\" if path_style is None : return self . _os_path_style supported_path_styles = list ( PathStyle ) if path_style in supported_path_styles : return PathStyle ( path_style ) supported_path_style_str = \", \" . join (([ x . value for x in supported_path_styles ])) raise ValueError ( f \"Path style ' { path_style } ' not supported. Supported path styles: { supported_path_style_str } \" )","title":"validate()"},{"location":"reference/api/#hydrolib.core.basemodel.ResolveRelativeMode","text":"ResolveRelativeMode defines the possible resolve modes used within the FilePathResolver. It determines how the relative paths to child models within some FileModel should be interpreted. By default it should be relative to the parent model, i.e. the model in which the mode is defined. However there exist some exceptions, where the relative paths should be evaluated relative to some other folder, regardless of the current parent location. Options Toparent Relative paths should be resolved relative to their direct parent model. Toanchor All relative paths should be resolved relative to the specified regardless of subsequent parent model locations.","title":"ResolveRelativeMode"},{"location":"reference/api/#hydrolib.core.basemodel.SerializerConfig","text":"Class that holds the configuration settings for serialization.","title":"SerializerConfig"},{"location":"reference/api/#hydrolib.core.basemodel.file_load_context","text":"Provide a FileLoadingContext. If none has been created in the context of this call stack yet, a new one will be created, which will be maintained until it goes out of scope. Yields [FileLoadContext]: The file load context. Source code in hydrolib/core/basemodel.py @contextmanager def file_load_context (): \"\"\"Provide a FileLoadingContext. If none has been created in the context of this call stack yet, a new one will be created, which will be maintained until it goes out of scope. Yields: [FileLoadContext]: The file load context. \"\"\" file_loading_context = context_file_loading . get ( None ) context_reset_token = None if not file_loading_context : file_loading_context = FileLoadContext () context_reset_token = context_file_loading . set ( file_loading_context ) try : yield file_loading_context finally : if context_reset_token is not None : context_file_loading . reset ( context_reset_token )","title":"file_load_context()"},{"location":"reference/api/#hydrolib.core.basemodel.validator_set_default_disk_only_file_model_when_none","text":"Validator to ensure a default empty DiskOnlyFileModel is created when the corresponding field is initialized with None. Returns: Type Description classmethod Validator to adjust None values to empty DiskOnlyFileModel objects Source code in hydrolib/core/basemodel.py def validator_set_default_disk_only_file_model_when_none () -> classmethod : \"\"\"Validator to ensure a default empty DiskOnlyFileModel is created when the corresponding field is initialized with None. Returns: classmethod: Validator to adjust None values to empty DiskOnlyFileModel objects \"\"\" def adjust_none ( v : Any , field : ModelField ) -> Any : if field . type_ is DiskOnlyFileModel and v is None : return { \"filepath\" : None } return v return validator ( \"*\" , allow_reuse = True , pre = True )( adjust_none )","title":"validator_set_default_disk_only_file_model_when_none()"},{"location":"reference/crosssection/","text":"Cross section files \u00b6 The crosssection module provides the specific logic for accessing cross section files (location and definition) for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. The cross section files are represented by the classes below. Model \u00b6 CircleCrsDef ( CrossSectionDefinition ) pydantic-model \u00b6 Crosssection definition with type=circle , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the circle input as described in UM Sec.C.16.1.1 . CrossDefGeneral ( INIGeneral ) pydantic-model \u00b6 The crosssection definition file's [General] section with file meta data. CrossDefModel ( INIModel ) pydantic-model \u00b6 The overall crosssection definition model that contains the contents of one crossdef file. This model is typically referenced under a FMModel .geometry.crossdeffile . Attributes: Name Type Description general CrossdefGeneral [General] block with file metadata. definition List[CrossSectionDefinition] List of [Definition] blocks for all cross sections. CrossLocGeneral ( INIGeneral ) pydantic-model \u00b6 The crosssection location file's [General] section with file meta data. CrossLocModel ( INIModel ) pydantic-model \u00b6 The overall crosssection location model that contains the contents of one crossloc file. This model is typically referenced under a FMModel .geometry.crosslocfile . Attributes: Name Type Description general CrossLocGeneral [General] block with file metadata. crosssection List[CrossSection] List of [CrossSection] blocks for all cross section locations. CrossSection ( INIBasedModel ) pydantic-model \u00b6 A [CrossSection] block for use inside a crosssection location file, i.e., a CrossLocModel . Attributes: Name Type Description id str Unique cross-section location id. branchid str Branch on which the cross section is located. chainage str Chainage on the branch (m). x str x-coordinate of the location of the cross section. y str y-coordinate of the location of the cross section. shift float Vertical shift of the cross section definition [m]. Defined positive upwards. definitionid str Id of cross section definition. validate_that_location_specification_is_correct ( values : Dict ) -> Dict classmethod \u00b6 Validates that the correct location specification is given. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def validate_that_location_specification_is_correct ( cls , values : Dict ) -> Dict : \"\"\"Validates that the correct location specification is given.\"\"\" return validate_location_specification ( values , config = LocationValidationConfiguration ( validate_node = False , validate_num_coordinates = False ), fields = LocationValidationFieldNames ( x_coordinates = \"x\" , y_coordinates = \"y\" ), ) CrossSectionDefinition ( INIBasedModel ) pydantic-model \u00b6 A [Definition] block for use inside a crosssection definition file, i.e., a CrossDefModel . This class is intended as an abstract class: various subclasses should define they actual types of crosssection definitions. validate ( v ) classmethod \u00b6 Try to initialize subclass based on the type field. This field is compared to each type field of the derived models of CrossSectionDefinition . The derived model with an equal crosssection definition type will be initialized. Exceptions: Type Description ValueError When the given type is not a known crosssection definition type. Source code in hydrolib/core/dflowfm/crosssection/models.py @classmethod def validate ( cls , v ): \"\"\"Try to initialize subclass based on the `type` field. This field is compared to each `type` field of the derived models of `CrossSectionDefinition`. The derived model with an equal crosssection definition type will be initialized. Raises: ValueError: When the given type is not a known crosssection definition type. \"\"\" # should be replaced by discriminated unions once merged # https://github.com/samuelcolvin/pydantic/pull/2336 if isinstance ( v , dict ): for c in cls . __subclasses__ (): if ( c . __fields__ . get ( \"type\" ) . default . lower () == v . get ( \"type\" , \"\" ) . lower () ): v = c ( ** v ) break else : raise ValueError ( f \"Type of { cls . __name__ } with id= { v . get ( 'id' , '' ) } and type= { v . get ( 'type' , '' ) } is not recognized.\" ) return super () . validate ( v ) RectangleCrsDef ( CrossSectionDefinition ) pydantic-model \u00b6 Crosssection definition with type=rectangle , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the rectangle input as described in UM Sec.C.16.1.2 . XYZCrsDef ( YZCrsDef , CrossSectionDefinition ) pydantic-model \u00b6 Crosssection definition with type=xyz , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the xyz input as described in UM Sec.C.16.1.5 . This class extends the YZCrsDef class with x-coordinates and an optional branchId field. Most other attributes are inherited, but the coordcount is overridden under the Pydantic alias \"xyzCount\". Attributes: Name Type Description yzcount Optional[int] dummy attribute that should not be set nor used. Only present to mask the inherited attribute from parent class YZCrsDef. xyzcount int Number of XYZ-coordinates. Always use this instead of yzcount. check_list_lengths_coordinates ( values ) classmethod \u00b6 Validates that the length of the xcoordinates, ycoordinates and zcoordinates field are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths_coordinates ( cls , values ): \"\"\"Validates that the length of the xcoordinates, ycoordinates and zcoordinates field are as expected.\"\"\" return validate_correct_length ( values , \"xcoordinates\" , \"ycoordinates\" , \"zcoordinates\" , length_name = \"xyzcount\" , ) validate_xyzcount_without_yzcount ( field_value : int , values : dict ) -> int classmethod \u00b6 Validates whether this XYZCrsDef does have attribute xyzcount, but not the parent class's yzcount. Parameters: Name Type Description Default field_value Optional[Path] Value given for xyzcount. required values dict Dictionary of values already validated. required Exceptions: Type Description ValueError When yzcount is present. Returns: Type Description int The value given for xyzcount. Source code in hydrolib/core/dflowfm/crosssection/models.py @validator ( \"xyzcount\" ) @classmethod def validate_xyzcount_without_yzcount ( cls , field_value : int , values : dict ) -> int : \"\"\" Validates whether this XYZCrsDef does have attribute xyzcount, but not the parent class's yzcount. Args: field_value (Optional[Path]): Value given for xyzcount. values (dict): Dictionary of values already validated. Raises: ValueError: When yzcount is present. Returns: int: The value given for xyzcount. \"\"\" # Retrieve the algorithm value (if not found use 0). yzcount_value = values . get ( \"yzcount\" ) if field_value is not None and yzcount_value is not None : # yzcount should not be set, when xyzcount is set. raise ValueError ( f \"xyz cross section definition should not contain field yzCount (rather: xyzCount), current value: { yzcount_value } .\" ) return field_value YZCrsDef ( CrossSectionDefinition ) pydantic-model \u00b6 Crosssection definition with type=yz , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the yz input as described in UM Sec.C.16.1.6 . check_list_length_frictionpositions ( values ) classmethod \u00b6 Validates that the length of the frictionpositions field is as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_length_frictionpositions ( cls , values ): \"\"\"Validates that the length of the frictionpositions field is as expected.\"\"\" return validate_correct_length ( values , \"frictionpositions\" , length_name = \"sectioncount\" , length_incr = 1 , # 1 extra for frictionpositions ) check_list_lengths_coordinates ( values ) classmethod \u00b6 Validates that the length of the ycoordinates and zcoordinates fields are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths_coordinates ( cls , values ): \"\"\"Validates that the length of the ycoordinates and zcoordinates fields are as expected.\"\"\" return validate_correct_length ( values , \"ycoordinates\" , \"zcoordinates\" , length_name = \"yzcount\" , ) check_list_lengths_friction ( values ) classmethod \u00b6 Validates that the length of the frictionids, frictiontypes and frictionvalues field are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths_friction ( cls , values ): \"\"\"Validates that the length of the frictionids, frictiontypes and frictionvalues field are as expected.\"\"\" return validate_correct_length ( values , \"frictionids\" , \"frictiontypes\" , \"frictionvalues\" , length_name = \"sectioncount\" , ) ZWCrsDef ( CrossSectionDefinition ) pydantic-model \u00b6 Crosssection definition with type=zw , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the zw input as described in UM Sec.C.16.1.4 . check_list_lengths ( values ) classmethod \u00b6 Validates that the length of the levels, flowwidths and totalwidths fields are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths ( cls , values ): \"\"\"Validates that the length of the levels, flowwidths and totalwidths fields are as expected.\"\"\" return validate_correct_length ( values , \"levels\" , \"flowwidths\" , \"totalwidths\" , length_name = \"numlevels\" , ) ZWRiverCrsDef ( CrossSectionDefinition ) pydantic-model \u00b6 Crosssection definition with type=zwRiver , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the zwRiver input as described in UM Sec.C.16.1.3 . check_list_lengths ( values ) classmethod \u00b6 Validates that the length of the levels, flowwidths and totalwidths fields are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths ( cls , values ): \"\"\"Validates that the length of the levels, flowwidths and totalwidths fields are as expected.\"\"\" return validate_correct_length ( values , \"levels\" , \"flowwidths\" , \"totalwidths\" , length_name = \"numlevels\" , )","title":"Cross section files"},{"location":"reference/crosssection/#cross-section-files","text":"The crosssection module provides the specific logic for accessing cross section files (location and definition) for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. The cross section files are represented by the classes below.","title":"Cross section files"},{"location":"reference/crosssection/#model","text":"","title":"Model"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.CircleCrsDef","text":"Crosssection definition with type=circle , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the circle input as described in UM Sec.C.16.1.1 .","title":"CircleCrsDef"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.CrossDefGeneral","text":"The crosssection definition file's [General] section with file meta data.","title":"CrossDefGeneral"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.CrossDefModel","text":"The overall crosssection definition model that contains the contents of one crossdef file. This model is typically referenced under a FMModel .geometry.crossdeffile . Attributes: Name Type Description general CrossdefGeneral [General] block with file metadata. definition List[CrossSectionDefinition] List of [Definition] blocks for all cross sections.","title":"CrossDefModel"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.CrossLocGeneral","text":"The crosssection location file's [General] section with file meta data.","title":"CrossLocGeneral"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.CrossLocModel","text":"The overall crosssection location model that contains the contents of one crossloc file. This model is typically referenced under a FMModel .geometry.crosslocfile . Attributes: Name Type Description general CrossLocGeneral [General] block with file metadata. crosssection List[CrossSection] List of [CrossSection] blocks for all cross section locations.","title":"CrossLocModel"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.CrossSection","text":"A [CrossSection] block for use inside a crosssection location file, i.e., a CrossLocModel . Attributes: Name Type Description id str Unique cross-section location id. branchid str Branch on which the cross section is located. chainage str Chainage on the branch (m). x str x-coordinate of the location of the cross section. y str y-coordinate of the location of the cross section. shift float Vertical shift of the cross section definition [m]. Defined positive upwards. definitionid str Id of cross section definition.","title":"CrossSection"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.CrossSection.validate_that_location_specification_is_correct","text":"Validates that the correct location specification is given. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def validate_that_location_specification_is_correct ( cls , values : Dict ) -> Dict : \"\"\"Validates that the correct location specification is given.\"\"\" return validate_location_specification ( values , config = LocationValidationConfiguration ( validate_node = False , validate_num_coordinates = False ), fields = LocationValidationFieldNames ( x_coordinates = \"x\" , y_coordinates = \"y\" ), )","title":"validate_that_location_specification_is_correct()"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.CrossSectionDefinition","text":"A [Definition] block for use inside a crosssection definition file, i.e., a CrossDefModel . This class is intended as an abstract class: various subclasses should define they actual types of crosssection definitions.","title":"CrossSectionDefinition"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.CrossSectionDefinition.validate","text":"Try to initialize subclass based on the type field. This field is compared to each type field of the derived models of CrossSectionDefinition . The derived model with an equal crosssection definition type will be initialized. Exceptions: Type Description ValueError When the given type is not a known crosssection definition type. Source code in hydrolib/core/dflowfm/crosssection/models.py @classmethod def validate ( cls , v ): \"\"\"Try to initialize subclass based on the `type` field. This field is compared to each `type` field of the derived models of `CrossSectionDefinition`. The derived model with an equal crosssection definition type will be initialized. Raises: ValueError: When the given type is not a known crosssection definition type. \"\"\" # should be replaced by discriminated unions once merged # https://github.com/samuelcolvin/pydantic/pull/2336 if isinstance ( v , dict ): for c in cls . __subclasses__ (): if ( c . __fields__ . get ( \"type\" ) . default . lower () == v . get ( \"type\" , \"\" ) . lower () ): v = c ( ** v ) break else : raise ValueError ( f \"Type of { cls . __name__ } with id= { v . get ( 'id' , '' ) } and type= { v . get ( 'type' , '' ) } is not recognized.\" ) return super () . validate ( v )","title":"validate()"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.RectangleCrsDef","text":"Crosssection definition with type=rectangle , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the rectangle input as described in UM Sec.C.16.1.2 .","title":"RectangleCrsDef"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.XYZCrsDef","text":"Crosssection definition with type=xyz , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the xyz input as described in UM Sec.C.16.1.5 . This class extends the YZCrsDef class with x-coordinates and an optional branchId field. Most other attributes are inherited, but the coordcount is overridden under the Pydantic alias \"xyzCount\". Attributes: Name Type Description yzcount Optional[int] dummy attribute that should not be set nor used. Only present to mask the inherited attribute from parent class YZCrsDef. xyzcount int Number of XYZ-coordinates. Always use this instead of yzcount.","title":"XYZCrsDef"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.XYZCrsDef.check_list_lengths_coordinates","text":"Validates that the length of the xcoordinates, ycoordinates and zcoordinates field are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths_coordinates ( cls , values ): \"\"\"Validates that the length of the xcoordinates, ycoordinates and zcoordinates field are as expected.\"\"\" return validate_correct_length ( values , \"xcoordinates\" , \"ycoordinates\" , \"zcoordinates\" , length_name = \"xyzcount\" , )","title":"check_list_lengths_coordinates()"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.XYZCrsDef.validate_xyzcount_without_yzcount","text":"Validates whether this XYZCrsDef does have attribute xyzcount, but not the parent class's yzcount. Parameters: Name Type Description Default field_value Optional[Path] Value given for xyzcount. required values dict Dictionary of values already validated. required Exceptions: Type Description ValueError When yzcount is present. Returns: Type Description int The value given for xyzcount. Source code in hydrolib/core/dflowfm/crosssection/models.py @validator ( \"xyzcount\" ) @classmethod def validate_xyzcount_without_yzcount ( cls , field_value : int , values : dict ) -> int : \"\"\" Validates whether this XYZCrsDef does have attribute xyzcount, but not the parent class's yzcount. Args: field_value (Optional[Path]): Value given for xyzcount. values (dict): Dictionary of values already validated. Raises: ValueError: When yzcount is present. Returns: int: The value given for xyzcount. \"\"\" # Retrieve the algorithm value (if not found use 0). yzcount_value = values . get ( \"yzcount\" ) if field_value is not None and yzcount_value is not None : # yzcount should not be set, when xyzcount is set. raise ValueError ( f \"xyz cross section definition should not contain field yzCount (rather: xyzCount), current value: { yzcount_value } .\" ) return field_value","title":"validate_xyzcount_without_yzcount()"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.YZCrsDef","text":"Crosssection definition with type=yz , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the yz input as described in UM Sec.C.16.1.6 .","title":"YZCrsDef"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.YZCrsDef.check_list_length_frictionpositions","text":"Validates that the length of the frictionpositions field is as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_length_frictionpositions ( cls , values ): \"\"\"Validates that the length of the frictionpositions field is as expected.\"\"\" return validate_correct_length ( values , \"frictionpositions\" , length_name = \"sectioncount\" , length_incr = 1 , # 1 extra for frictionpositions )","title":"check_list_length_frictionpositions()"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.YZCrsDef.check_list_lengths_coordinates","text":"Validates that the length of the ycoordinates and zcoordinates fields are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths_coordinates ( cls , values ): \"\"\"Validates that the length of the ycoordinates and zcoordinates fields are as expected.\"\"\" return validate_correct_length ( values , \"ycoordinates\" , \"zcoordinates\" , length_name = \"yzcount\" , )","title":"check_list_lengths_coordinates()"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.YZCrsDef.check_list_lengths_friction","text":"Validates that the length of the frictionids, frictiontypes and frictionvalues field are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths_friction ( cls , values ): \"\"\"Validates that the length of the frictionids, frictiontypes and frictionvalues field are as expected.\"\"\" return validate_correct_length ( values , \"frictionids\" , \"frictiontypes\" , \"frictionvalues\" , length_name = \"sectioncount\" , )","title":"check_list_lengths_friction()"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.ZWCrsDef","text":"Crosssection definition with type=zw , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the zw input as described in UM Sec.C.16.1.4 .","title":"ZWCrsDef"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.ZWCrsDef.check_list_lengths","text":"Validates that the length of the levels, flowwidths and totalwidths fields are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths ( cls , values ): \"\"\"Validates that the length of the levels, flowwidths and totalwidths fields are as expected.\"\"\" return validate_correct_length ( values , \"levels\" , \"flowwidths\" , \"totalwidths\" , length_name = \"numlevels\" , )","title":"check_list_lengths()"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.ZWRiverCrsDef","text":"Crosssection definition with type=zwRiver , to be included in a crossdef file. Typically inside the definition list of a FMModel .geometry.crossdeffile.definition[..] All lowercased attributes match with the zwRiver input as described in UM Sec.C.16.1.3 .","title":"ZWRiverCrsDef"},{"location":"reference/crosssection/#hydrolib.core.dflowfm.crosssection.models.ZWRiverCrsDef.check_list_lengths","text":"Validates that the length of the levels, flowwidths and totalwidths fields are as expected. Source code in hydrolib/core/dflowfm/crosssection/models.py @root_validator ( allow_reuse = True ) def check_list_lengths ( cls , values ): \"\"\"Validates that the length of the levels, flowwidths and totalwidths fields are as expected.\"\"\" return validate_correct_length ( values , \"levels\" , \"flowwidths\" , \"totalwidths\" , length_name = \"numlevels\" , )","title":"check_list_lengths()"},{"location":"reference/dimr/","text":"DIMR xml files \u00b6 The input to the Deltares Integrated Model Runner ( DIMR ) is a single XML file, represented by the classes below. Model \u00b6 Component ( BaseModel , ABC ) pydantic-model \u00b6 Specification of a BMI-compliant model component instance that will be executed by DIMR. Attributes: Name Type Description library str The library name of the compoment. name str The component name. workingDir Path The working directory. inputFile Path The name of the input file. process Optional[int] Number of subprocesses in the component. setting Optional[List[hydrolib.core.dimr.models.KeyValuePair]] A list of variables that are provided to the BMI model before initialization. parameter Optional[List[hydrolib.core.dimr.models.KeyValuePair]] A list of variables that are provided to the BMI model after initialization. mpiCommunicator Optional[str] The MPI communicator value. model Optional[hydrolib.core.basemodel.FileModel] The model represented by this component. dict ( self , * args , ** kwargs ) \u00b6 Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dimr/models.py def dict ( self , * args , ** kwargs ): # Exclude the FileModel from any DIMR serialization. kwargs [ \"exclude\" ] = { \"model\" } return super () . dict ( * args , ** kwargs ) is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dimr/models.py def is_intermediate_link ( self ) -> bool : return True ComponentOrCouplerRef ( BaseModel ) pydantic-model \u00b6 Reference to a BMI-compliant model component instance. Attributes: Name Type Description name str Name of the reference to a BMI-compliant model component instance. ControlModel ( BaseModel ) pydantic-model \u00b6 Overrides to make sure that the control elements in the DIMR are parsed and serialized correctly. dict ( self , * args , ** kwargs ) \u00b6 Add control element prefixes for serialized data. Source code in hydrolib/core/dimr/models.py def dict ( self , * args , ** kwargs ): \"\"\"Add control element prefixes for serialized data.\"\"\" return { str ( self . _type ): super () . dict ( * args , ** kwargs ), } validate ( v ) classmethod \u00b6 Remove control element prefixes from parsed data. Source code in hydrolib/core/dimr/models.py @classmethod def validate ( cls , v ): \"\"\"Remove control element prefixes from parsed data.\"\"\" # should be replaced by discriminated unions once merged # https://github.com/samuelcolvin/pydantic/pull/2336 if isinstance ( v , dict ) and len ( v . keys ()) == 1 : key = list ( v . keys ())[ 0 ] v = v [ key ] return super () . validate ( v ) CoupledItem ( BaseModel ) pydantic-model \u00b6 Specification of an item that has to be exchanged. Attributes: Name Type Description sourceName str Name of the item at the source component. targetName str Name of the item at the target component. is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dimr/models.py def is_intermediate_link ( self ) -> bool : # TODO set to True once we replace Paths with FileModels return False Coupler ( BaseModel ) pydantic-model \u00b6 Specification of the coupling actions to be performed between two BMI-compliant model components. Attributes: Name Type Description name str The name of the coupler. sourceComponent str The component that provides the data to has to be exchanged. targetComponent str The component that consumes the data to has to be exchanged. item List[hydrolib.core.dimr.models.CoupledItem] A list of items that have to be exchanged. logger Optional[hydrolib.core.dimr.models.Logger] Logger for logging the values that get exchanged. is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dimr/models.py def is_intermediate_link ( self ) -> bool : # TODO set to True once we replace Paths with FileModels return False DIMR ( ParsableFileModel ) pydantic-model \u00b6 DIMR model representation. Attributes: Name Type Description documentation Documentation File metadata. control List[Union[Start, Parallel]] The element with a list of Start and Parallel sub-elements, which defines the (sequence of) program(s) to be run. May be empty while constructing, but must be non-empty when saving! Also, all referenced components must be present in component when saving. Similarly, all referenced couplers must be present in coupler . component List[Union[RRComponent, FMComponent, Component]] List of elements that defines which programs can be used inside the subelements. Must be non-empty when saving! coupler Optional[List[Coupler]] optional list of elements that defines which couplers can be used inside the elements under . waitFile Optional[str] Optional waitfile name for debugging. global_settings Optional[GlobalSettings] Optional global DIMR settings. dict ( self , * args , ** kwargs ) \u00b6 Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dimr/models.py def dict ( self , * args , ** kwargs ): kwargs [ \"exclude_none\" ] = True return super () . dict ( * args , ** kwargs ) Documentation ( BaseModel ) pydantic-model \u00b6 Information on the present DIMR configuration file. Attributes: Name Type Description fileVersion str The DIMR file version. createdBy str Creators of the DIMR file. creationDate datetime The creation date of the DIMR file. FMComponent ( Component ) pydantic-model \u00b6 Component to include the D-Flow FM program in a DIMR control flow. GlobalSettings ( BaseModel ) pydantic-model \u00b6 Global settings for the DIMR configuration. Attributes: Name Type Description logger_ncFormat int NetCDF format type for logging. KeyValuePair ( BaseModel ) pydantic-model \u00b6 Key value pair to specify settings and parameters. Attributes: Name Type Description key str The key. value str The value. Logger ( BaseModel ) pydantic-model \u00b6 Used to log values to the specified file in workingdir for each timestep Attributes: Name Type Description workingDir Path Directory where the log file is written. outputFile Path Name of the log file. Parallel ( ControlModel ) pydantic-model \u00b6 Specification of a parallel control flow: one main component and a group of related components and couplers. Step wise execution order according to order in parallel control flow. Attributes: Name Type Description startGroup StartGroup Group of components and couplers to be executed. start ComponentOrCouplerRef Main component to be executed step wise (provides start time, end time and time step). RRComponent ( Component ) pydantic-model \u00b6 Component to include the RainfallRunoff program in a DIMR control flow. Start ( ControlModel ) pydantic-model \u00b6 Specification of a serial control flow: one main component. Attributes: Name Type Description name str Name of the reference to a BMI-compliant model component instance StartGroup ( BaseModel ) pydantic-model \u00b6 Specification of model components and couplers to be executed with a certain frequency. Attributes: Name Type Description time str Time frame specification for the present group: start time, stop time and frequency. Expressed in terms of the time frame of the main component. start List[hydrolib.core.dimr.models.ComponentOrCouplerRef] Ordered list of components to be executed. coupler List[hydrolib.core.dimr.models.ComponentOrCouplerRef] Oredered list of couplers to be executed. Parser \u00b6 DIMRParser \u00b6 A parser for DIMR xml files. parse ( path : Path ) -> dict staticmethod \u00b6 Parses a DIMR file to a dictionary. Parameters: Name Type Description Default path Path Path to the DIMR configuration file. required Source code in hydrolib/core/dimr/parser.py @staticmethod def parse ( path : Path ) -> dict : \"\"\"Parses a DIMR file to a dictionary. Args: path (Path): Path to the DIMR configuration file. \"\"\" if not path . is_file (): warn ( f \"File: ` { path } ` not found, skipped parsing.\" ) return {} parser = etree . XMLParser ( remove_comments = True , resolve_entities = False , no_network = True ) root = etree . parse ( str ( path ), parser = parser ) . getroot () return DIMRParser . _node_to_dictionary ( root , True ) Serializer \u00b6 DIMRSerializer \u00b6 A serializer for DIMR files. serialize ( path : Path , data : dict , config : SerializerConfig , save_settings : ModelSaveSettings ) staticmethod \u00b6 Serializes the DIMR data to the file at the specified path. Attributes: Name Type Description path Path The path to the destination file. data Dict The data to be serialized. config SerializerConfig The serialization configuration. save_settings ModelSaveSettings The model save settings. Source code in hydrolib/core/dimr/serializer.py @staticmethod def serialize ( path : Path , data : dict , config : SerializerConfig , save_settings : ModelSaveSettings , ): \"\"\" Serializes the DIMR data to the file at the specified path. Attributes: path (Path): The path to the destination file. data (Dict): The data to be serialized. config (SerializerConfig): The serialization configuration. save_settings (ModelSaveSettings): The model save settings. \"\"\" path . parent . mkdir ( parents = True , exist_ok = True ) xmlns = \"http://schemas.deltares.nl/dimr\" xsi = \"http://www.w3.org/2001/XMLSchema-instance\" schema_location = \"http://content.oss.deltares.nl/schemas/dimr-1.3.xsd\" attrib = { e . QName ( xsi , \"schemaLocation\" ): f \" { xmlns } { schema_location } \" } namespaces = { None : xmlns , \"xsi\" : xsi } root = e . Element ( \"dimrConfig\" , attrib = attrib , nsmap = namespaces , ) path_style_converter = FilePathStyleConverter () DIMRSerializer . _build_tree ( root , data , config , save_settings , path_style_converter ) to_string = minidom . parseString ( e . tostring ( root )) xml = to_string . toprettyxml ( indent = \" \" , encoding = \"utf-8\" ) with path . open ( \"wb\" ) as f : f . write ( xml )","title":"DIMR xml files"},{"location":"reference/dimr/#dimr-xml-files","text":"The input to the Deltares Integrated Model Runner ( DIMR ) is a single XML file, represented by the classes below.","title":"DIMR xml files"},{"location":"reference/dimr/#model","text":"","title":"Model"},{"location":"reference/dimr/#hydrolib.core.dimr.models.Component","text":"Specification of a BMI-compliant model component instance that will be executed by DIMR. Attributes: Name Type Description library str The library name of the compoment. name str The component name. workingDir Path The working directory. inputFile Path The name of the input file. process Optional[int] Number of subprocesses in the component. setting Optional[List[hydrolib.core.dimr.models.KeyValuePair]] A list of variables that are provided to the BMI model before initialization. parameter Optional[List[hydrolib.core.dimr.models.KeyValuePair]] A list of variables that are provided to the BMI model after initialization. mpiCommunicator Optional[str] The MPI communicator value. model Optional[hydrolib.core.basemodel.FileModel] The model represented by this component.","title":"Component"},{"location":"reference/dimr/#hydrolib.core.dimr.models.Component.dict","text":"Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dimr/models.py def dict ( self , * args , ** kwargs ): # Exclude the FileModel from any DIMR serialization. kwargs [ \"exclude\" ] = { \"model\" } return super () . dict ( * args , ** kwargs )","title":"dict()"},{"location":"reference/dimr/#hydrolib.core.dimr.models.Component.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dimr/models.py def is_intermediate_link ( self ) -> bool : return True","title":"is_intermediate_link()"},{"location":"reference/dimr/#hydrolib.core.dimr.models.ComponentOrCouplerRef","text":"Reference to a BMI-compliant model component instance. Attributes: Name Type Description name str Name of the reference to a BMI-compliant model component instance.","title":"ComponentOrCouplerRef"},{"location":"reference/dimr/#hydrolib.core.dimr.models.ControlModel","text":"Overrides to make sure that the control elements in the DIMR are parsed and serialized correctly.","title":"ControlModel"},{"location":"reference/dimr/#hydrolib.core.dimr.models.ControlModel.dict","text":"Add control element prefixes for serialized data. Source code in hydrolib/core/dimr/models.py def dict ( self , * args , ** kwargs ): \"\"\"Add control element prefixes for serialized data.\"\"\" return { str ( self . _type ): super () . dict ( * args , ** kwargs ), }","title":"dict()"},{"location":"reference/dimr/#hydrolib.core.dimr.models.ControlModel.validate","text":"Remove control element prefixes from parsed data. Source code in hydrolib/core/dimr/models.py @classmethod def validate ( cls , v ): \"\"\"Remove control element prefixes from parsed data.\"\"\" # should be replaced by discriminated unions once merged # https://github.com/samuelcolvin/pydantic/pull/2336 if isinstance ( v , dict ) and len ( v . keys ()) == 1 : key = list ( v . keys ())[ 0 ] v = v [ key ] return super () . validate ( v )","title":"validate()"},{"location":"reference/dimr/#hydrolib.core.dimr.models.CoupledItem","text":"Specification of an item that has to be exchanged. Attributes: Name Type Description sourceName str Name of the item at the source component. targetName str Name of the item at the target component.","title":"CoupledItem"},{"location":"reference/dimr/#hydrolib.core.dimr.models.CoupledItem.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dimr/models.py def is_intermediate_link ( self ) -> bool : # TODO set to True once we replace Paths with FileModels return False","title":"is_intermediate_link()"},{"location":"reference/dimr/#hydrolib.core.dimr.models.Coupler","text":"Specification of the coupling actions to be performed between two BMI-compliant model components. Attributes: Name Type Description name str The name of the coupler. sourceComponent str The component that provides the data to has to be exchanged. targetComponent str The component that consumes the data to has to be exchanged. item List[hydrolib.core.dimr.models.CoupledItem] A list of items that have to be exchanged. logger Optional[hydrolib.core.dimr.models.Logger] Logger for logging the values that get exchanged.","title":"Coupler"},{"location":"reference/dimr/#hydrolib.core.dimr.models.Coupler.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dimr/models.py def is_intermediate_link ( self ) -> bool : # TODO set to True once we replace Paths with FileModels return False","title":"is_intermediate_link()"},{"location":"reference/dimr/#hydrolib.core.dimr.models.DIMR","text":"DIMR model representation. Attributes: Name Type Description documentation Documentation File metadata. control List[Union[Start, Parallel]] The element with a list of Start and Parallel sub-elements, which defines the (sequence of) program(s) to be run. May be empty while constructing, but must be non-empty when saving! Also, all referenced components must be present in component when saving. Similarly, all referenced couplers must be present in coupler . component List[Union[RRComponent, FMComponent, Component]] List of elements that defines which programs can be used inside the subelements. Must be non-empty when saving! coupler Optional[List[Coupler]] optional list of elements that defines which couplers can be used inside the elements under . waitFile Optional[str] Optional waitfile name for debugging. global_settings Optional[GlobalSettings] Optional global DIMR settings.","title":"DIMR"},{"location":"reference/dimr/#hydrolib.core.dimr.models.DIMR.dict","text":"Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dimr/models.py def dict ( self , * args , ** kwargs ): kwargs [ \"exclude_none\" ] = True return super () . dict ( * args , ** kwargs )","title":"dict()"},{"location":"reference/dimr/#hydrolib.core.dimr.models.Documentation","text":"Information on the present DIMR configuration file. Attributes: Name Type Description fileVersion str The DIMR file version. createdBy str Creators of the DIMR file. creationDate datetime The creation date of the DIMR file.","title":"Documentation"},{"location":"reference/dimr/#hydrolib.core.dimr.models.FMComponent","text":"Component to include the D-Flow FM program in a DIMR control flow.","title":"FMComponent"},{"location":"reference/dimr/#hydrolib.core.dimr.models.GlobalSettings","text":"Global settings for the DIMR configuration. Attributes: Name Type Description logger_ncFormat int NetCDF format type for logging.","title":"GlobalSettings"},{"location":"reference/dimr/#hydrolib.core.dimr.models.KeyValuePair","text":"Key value pair to specify settings and parameters. Attributes: Name Type Description key str The key. value str The value.","title":"KeyValuePair"},{"location":"reference/dimr/#hydrolib.core.dimr.models.Logger","text":"Used to log values to the specified file in workingdir for each timestep Attributes: Name Type Description workingDir Path Directory where the log file is written. outputFile Path Name of the log file.","title":"Logger"},{"location":"reference/dimr/#hydrolib.core.dimr.models.Parallel","text":"Specification of a parallel control flow: one main component and a group of related components and couplers. Step wise execution order according to order in parallel control flow. Attributes: Name Type Description startGroup StartGroup Group of components and couplers to be executed. start ComponentOrCouplerRef Main component to be executed step wise (provides start time, end time and time step).","title":"Parallel"},{"location":"reference/dimr/#hydrolib.core.dimr.models.RRComponent","text":"Component to include the RainfallRunoff program in a DIMR control flow.","title":"RRComponent"},{"location":"reference/dimr/#hydrolib.core.dimr.models.Start","text":"Specification of a serial control flow: one main component. Attributes: Name Type Description name str Name of the reference to a BMI-compliant model component instance","title":"Start"},{"location":"reference/dimr/#hydrolib.core.dimr.models.StartGroup","text":"Specification of model components and couplers to be executed with a certain frequency. Attributes: Name Type Description time str Time frame specification for the present group: start time, stop time and frequency. Expressed in terms of the time frame of the main component. start List[hydrolib.core.dimr.models.ComponentOrCouplerRef] Ordered list of components to be executed. coupler List[hydrolib.core.dimr.models.ComponentOrCouplerRef] Oredered list of couplers to be executed.","title":"StartGroup"},{"location":"reference/dimr/#parser","text":"","title":"Parser"},{"location":"reference/dimr/#hydrolib.core.dimr.parser.DIMRParser","text":"A parser for DIMR xml files.","title":"DIMRParser"},{"location":"reference/dimr/#hydrolib.core.dimr.parser.DIMRParser.parse","text":"Parses a DIMR file to a dictionary. Parameters: Name Type Description Default path Path Path to the DIMR configuration file. required Source code in hydrolib/core/dimr/parser.py @staticmethod def parse ( path : Path ) -> dict : \"\"\"Parses a DIMR file to a dictionary. Args: path (Path): Path to the DIMR configuration file. \"\"\" if not path . is_file (): warn ( f \"File: ` { path } ` not found, skipped parsing.\" ) return {} parser = etree . XMLParser ( remove_comments = True , resolve_entities = False , no_network = True ) root = etree . parse ( str ( path ), parser = parser ) . getroot () return DIMRParser . _node_to_dictionary ( root , True )","title":"parse()"},{"location":"reference/dimr/#serializer","text":"","title":"Serializer"},{"location":"reference/dimr/#hydrolib.core.dimr.serializer.DIMRSerializer","text":"A serializer for DIMR files.","title":"DIMRSerializer"},{"location":"reference/dimr/#hydrolib.core.dimr.serializer.DIMRSerializer.serialize","text":"Serializes the DIMR data to the file at the specified path. Attributes: Name Type Description path Path The path to the destination file. data Dict The data to be serialized. config SerializerConfig The serialization configuration. save_settings ModelSaveSettings The model save settings. Source code in hydrolib/core/dimr/serializer.py @staticmethod def serialize ( path : Path , data : dict , config : SerializerConfig , save_settings : ModelSaveSettings , ): \"\"\" Serializes the DIMR data to the file at the specified path. Attributes: path (Path): The path to the destination file. data (Dict): The data to be serialized. config (SerializerConfig): The serialization configuration. save_settings (ModelSaveSettings): The model save settings. \"\"\" path . parent . mkdir ( parents = True , exist_ok = True ) xmlns = \"http://schemas.deltares.nl/dimr\" xsi = \"http://www.w3.org/2001/XMLSchema-instance\" schema_location = \"http://content.oss.deltares.nl/schemas/dimr-1.3.xsd\" attrib = { e . QName ( xsi , \"schemaLocation\" ): f \" { xmlns } { schema_location } \" } namespaces = { None : xmlns , \"xsi\" : xsi } root = e . Element ( \"dimrConfig\" , attrib = attrib , nsmap = namespaces , ) path_style_converter = FilePathStyleConverter () DIMRSerializer . _build_tree ( root , data , config , save_settings , path_style_converter ) to_string = minidom . parseString ( e . tostring ( root )) xml = to_string . toprettyxml ( indent = \" \" , encoding = \"utf-8\" ) with path . open ( \"wb\" ) as f : f . write ( xml )","title":"serialize()"},{"location":"reference/ext/","text":"External forcings file \u00b6 The external forcing .ext file contains the forcing data for a D-Flow FM model. This includes open boundaries, lateral discharges and meteorological forcings. The documentation below only concerns the 'new' format ( ExtForceFileNew in the MDU file). Model \u00b6 Boundary ( INIBasedModel ) pydantic-model \u00b6 A [Boundary] block for use inside an external forcings file, i.e., a ExtModel . All lowercased attributes match with the boundary input as described in UM Sec.C.5.2.1 . check_nodeid_or_locationfile_present ( values : Dict ) classmethod \u00b6 Verifies that either nodeid or locationfile properties have been set. Parameters: Name Type Description Default values Dict Dictionary with values already validated. required Exceptions: Type Description ValueError When none of the values are present. Returns: Type Description Dict Validated dictionary of values for Boundary. Source code in hydrolib/core/dflowfm/ext/models.py @root_validator @classmethod def check_nodeid_or_locationfile_present ( cls , values : Dict ): \"\"\" Verifies that either nodeid or locationfile properties have been set. Args: values (Dict): Dictionary with values already validated. Raises: ValueError: When none of the values are present. Returns: Dict: Validated dictionary of values for Boundary. \"\"\" node_id = values . get ( \"nodeid\" , None ) location_file = values . get ( \"locationfile\" , None ) if str_is_empty_or_none ( node_id ) and not cls . _is_valid_locationfile_data ( location_file ): raise ValueError ( \"Either nodeId or locationFile fields should be specified.\" ) return values forcing : ForcingBase property readonly \u00b6 Retrieves the corresponding forcing data for this boundary. Returns: Type Description ForcingBase The corresponding forcing data. None when this boundary does not have a forcing file or when the data cannot be found. is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/ext/models.py def is_intermediate_link ( self ) -> bool : return True ExtGeneral ( INIGeneral ) pydantic-model \u00b6 The external forcing file's [General] section with file meta data. ExtModel ( INIModel ) pydantic-model \u00b6 The overall external forcings model that contains the contents of one external forcings file (new format). This model is typically referenced under a FMModel .external_forcing.extforcefilenew . Attributes: Name Type Description general ExtGeneral [General] block with file metadata. boundary List[Boundary] List of [Boundary] blocks for all boundary conditions. lateral List[Lateral] List of [Lateral] blocks for all lateral discharges. meteo List[Meteo] List of [Meteo] blocks for all meteorological forcings. Lateral ( INIBasedModel ) pydantic-model \u00b6 A [Lateral] block for use inside an external forcings file, i.e., a ExtModel . All lowercased attributes match with the lateral input as described in UM Sec.C.5.2.2 . is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/ext/models.py def is_intermediate_link ( self ) -> bool : return True validate_location_type ( v : str ) -> str classmethod \u00b6 Method to validate whether the specified location type is correct. Parameters: Name Type Description Default v str Given value for the locationtype field. required Exceptions: Type Description ValueError When the value given for locationtype is unknown. Returns: Type Description str Validated locationtype string. Source code in hydrolib/core/dflowfm/ext/models.py @validator ( \"locationtype\" ) @classmethod def validate_location_type ( cls , v : str ) -> str : \"\"\" Method to validate whether the specified location type is correct. Args: v (str): Given value for the locationtype field. Raises: ValueError: When the value given for locationtype is unknown. Returns: str: Validated locationtype string. \"\"\" possible_values = [ \"1d\" , \"2d\" , \"all\" ] if v . lower () not in possible_values : raise ValueError ( \"Value given ( {} ) not accepted, should be one of: {} \" . format ( v , \", \" . join ( possible_values ) ) ) return v validate_that_location_specification_is_correct ( values : Dict ) -> Dict classmethod \u00b6 Validates that the correct location specification is given. Source code in hydrolib/core/dflowfm/ext/models.py @root_validator ( allow_reuse = True ) def validate_that_location_specification_is_correct ( cls , values : Dict ) -> Dict : \"\"\"Validates that the correct location specification is given.\"\"\" return validate_location_specification ( values , config = LocationValidationConfiguration ( minimum_num_coordinates = 1 ) ) Meteo ( INIBasedModel ) pydantic-model \u00b6 A [Meteo] block for use inside an external forcings file, i.e., a ExtModel . All lowercased attributes match with the meteo input as described in UM Sec.C.5.2.3 . is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/ext/models.py def is_intermediate_link ( self ) -> bool : return True MeteoForcingFileType ( str , Enum ) \u00b6 Enum class containing the valid values for the forcingFileType attribute in Meteo class. bcascii \u00b6 str: Space-uniform time series in <*.bc> file. netcdf \u00b6 str: NetCDF, either with gridded data, or multiple station time series. uniform \u00b6 str: Space-uniform time series in <*.tim> file. MeteoInterpolationMethod ( str , Enum ) \u00b6 Enum class containing the valid values for the interpolationMethod attribute in Meteo class. nearestnb \u00b6 str: Nearest-neighbour interpolation, only with station-data in forcingFileType=netcdf","title":"External forcings file"},{"location":"reference/ext/#external-forcings-file","text":"The external forcing .ext file contains the forcing data for a D-Flow FM model. This includes open boundaries, lateral discharges and meteorological forcings. The documentation below only concerns the 'new' format ( ExtForceFileNew in the MDU file).","title":"External forcings file"},{"location":"reference/ext/#model","text":"","title":"Model"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Boundary","text":"A [Boundary] block for use inside an external forcings file, i.e., a ExtModel . All lowercased attributes match with the boundary input as described in UM Sec.C.5.2.1 .","title":"Boundary"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Boundary.check_nodeid_or_locationfile_present","text":"Verifies that either nodeid or locationfile properties have been set. Parameters: Name Type Description Default values Dict Dictionary with values already validated. required Exceptions: Type Description ValueError When none of the values are present. Returns: Type Description Dict Validated dictionary of values for Boundary. Source code in hydrolib/core/dflowfm/ext/models.py @root_validator @classmethod def check_nodeid_or_locationfile_present ( cls , values : Dict ): \"\"\" Verifies that either nodeid or locationfile properties have been set. Args: values (Dict): Dictionary with values already validated. Raises: ValueError: When none of the values are present. Returns: Dict: Validated dictionary of values for Boundary. \"\"\" node_id = values . get ( \"nodeid\" , None ) location_file = values . get ( \"locationfile\" , None ) if str_is_empty_or_none ( node_id ) and not cls . _is_valid_locationfile_data ( location_file ): raise ValueError ( \"Either nodeId or locationFile fields should be specified.\" ) return values","title":"check_nodeid_or_locationfile_present()"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Boundary.forcing","text":"Retrieves the corresponding forcing data for this boundary. Returns: Type Description ForcingBase The corresponding forcing data. None when this boundary does not have a forcing file or when the data cannot be found.","title":"forcing"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Boundary.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/ext/models.py def is_intermediate_link ( self ) -> bool : return True","title":"is_intermediate_link()"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.ExtGeneral","text":"The external forcing file's [General] section with file meta data.","title":"ExtGeneral"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.ExtModel","text":"The overall external forcings model that contains the contents of one external forcings file (new format). This model is typically referenced under a FMModel .external_forcing.extforcefilenew . Attributes: Name Type Description general ExtGeneral [General] block with file metadata. boundary List[Boundary] List of [Boundary] blocks for all boundary conditions. lateral List[Lateral] List of [Lateral] blocks for all lateral discharges. meteo List[Meteo] List of [Meteo] blocks for all meteorological forcings.","title":"ExtModel"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Lateral","text":"A [Lateral] block for use inside an external forcings file, i.e., a ExtModel . All lowercased attributes match with the lateral input as described in UM Sec.C.5.2.2 .","title":"Lateral"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Lateral.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/ext/models.py def is_intermediate_link ( self ) -> bool : return True","title":"is_intermediate_link()"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Lateral.validate_location_type","text":"Method to validate whether the specified location type is correct. Parameters: Name Type Description Default v str Given value for the locationtype field. required Exceptions: Type Description ValueError When the value given for locationtype is unknown. Returns: Type Description str Validated locationtype string. Source code in hydrolib/core/dflowfm/ext/models.py @validator ( \"locationtype\" ) @classmethod def validate_location_type ( cls , v : str ) -> str : \"\"\" Method to validate whether the specified location type is correct. Args: v (str): Given value for the locationtype field. Raises: ValueError: When the value given for locationtype is unknown. Returns: str: Validated locationtype string. \"\"\" possible_values = [ \"1d\" , \"2d\" , \"all\" ] if v . lower () not in possible_values : raise ValueError ( \"Value given ( {} ) not accepted, should be one of: {} \" . format ( v , \", \" . join ( possible_values ) ) ) return v","title":"validate_location_type()"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Lateral.validate_that_location_specification_is_correct","text":"Validates that the correct location specification is given. Source code in hydrolib/core/dflowfm/ext/models.py @root_validator ( allow_reuse = True ) def validate_that_location_specification_is_correct ( cls , values : Dict ) -> Dict : \"\"\"Validates that the correct location specification is given.\"\"\" return validate_location_specification ( values , config = LocationValidationConfiguration ( minimum_num_coordinates = 1 ) )","title":"validate_that_location_specification_is_correct()"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Meteo","text":"A [Meteo] block for use inside an external forcings file, i.e., a ExtModel . All lowercased attributes match with the meteo input as described in UM Sec.C.5.2.3 .","title":"Meteo"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.Meteo.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/ext/models.py def is_intermediate_link ( self ) -> bool : return True","title":"is_intermediate_link()"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.MeteoForcingFileType","text":"Enum class containing the valid values for the forcingFileType attribute in Meteo class.","title":"MeteoForcingFileType"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.MeteoForcingFileType.bcascii","text":"str: Space-uniform time series in <*.bc> file.","title":"bcascii"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.MeteoForcingFileType.netcdf","text":"str: NetCDF, either with gridded data, or multiple station time series.","title":"netcdf"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.MeteoForcingFileType.uniform","text":"str: Space-uniform time series in <*.tim> file.","title":"uniform"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.MeteoInterpolationMethod","text":"Enum class containing the valid values for the interpolationMethod attribute in Meteo class.","title":"MeteoInterpolationMethod"},{"location":"reference/ext/#hydrolib.core.dflowfm.ext.models.MeteoInterpolationMethod.nearestnb","text":"str: Nearest-neighbour interpolation, only with station-data in forcingFileType=netcdf","title":"nearestnb"},{"location":"reference/extold/","text":"External forcings file \u00b6 The external forcing .ext file contains the forcing data for a D-Flow FM model. This includes open boundaries, lateral discharges and meteorological forcings. The documentation below only concerns the 'old' format ( ExtForceFile in the MDU file). Model \u00b6 ExtOldExtrapolationMethod ( IntEnum ) \u00b6 Enum class containing the valid values for the extrapolation_method attribute in the ExtOldForcing class. NoSpatialExtrapolation \u00b6 No spatial extrapolation. SpatialExtrapolationOutsideOfSourceDataBoundingBox \u00b6 Do spatial extrapolation outside of source data bounding box. ExtOldFileType ( IntEnum ) \u00b6 Enum class containing the valid values for the filetype attribute in the ExtOldForcing class. ArcInfo \u00b6 ArcInfo CurvilinearData \u00b6 Space-time data on curvilinear grid NetCDFGridData \u00b6 NetCDF grid data (e.g. meteo fields) NetCDFWaveData \u00b6 NetCDF wave data Polyfile \u00b6 Polyfile (< .pol/ .pli>-file). uniform value inside polygon for INITIAL fields Polyline \u00b6 Polyline (<*.pli>-file) Samples \u00b6 Samples SpatiallyVaryingWindPressure \u00b6 Spatially varying wind and pressure SpiderWebData \u00b6 Spiderweb data (cyclones) TimeSeries \u00b6 Time series TimeSeriesMagnitudeAndDirection \u00b6 Time series magnitude and direction TriangulationMagnitudeAndDirection \u00b6 Triangulation magnitude and direction ExtOldForcing ( BaseModel ) pydantic-model \u00b6 Class holding the external forcing values. ExtOldMethod ( IntEnum ) \u00b6 Enum class containing the valid values for the method attribute in the ExtOldForcing class. AveragingSpace \u00b6 Averaging in space InterpolateExtrapolateTime \u00b6 Interpolate/Extrapolate time InterpolateSpace \u00b6 Interpolate space InterpolateTime \u00b6 Interpolate time InterpolateTimeAndSpace \u00b6 Interpolate time and space InterpolateTimeAndSpaceSaveWeights \u00b6 Interpolate time and space, save weights PassThrough \u00b6 Pass through (no interpolation) ExtOldModel ( ParsableFileModel ) pydantic-model \u00b6 The overall external forcings model that contains the contents of one external forcings file (old format). This model is typically referenced under a FMModel .external_forcing.extforcefile . dict ( self , * args , ** kwargs ) \u00b6 Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dflowfm/extold/models.py def dict ( self , * args , ** kwargs ): return dict ( comment = self . comment , forcing = [ dict ( f ) for f in self . forcing ]) ExtOldQuantity ( str , Enum ) \u00b6 Enum class containing the valid values for the boundary conditions category of the external forcings. AdvectionType \u00b6 Type of advection scheme AirDensity \u00b6 Air density AirPressure \u00b6 AirPressure AirPressureWindXWindY \u00b6 Atmospheric pressure and wind components AirPressureWindXWindYCharnock \u00b6 Atmospheric pressure and wind components Charnock AirTemperature \u00b6 AirTemperature AirpressureStressXStressY \u00b6 Airpressure, eastward and northward wind stress AtmosphericPressure \u00b6 Atmospheric pressure BedLevel \u00b6 Bed level Charnock \u00b6 Charnock coefficient Cloudiness \u00b6 Cloudiness, or cloud cover (fraction) DamLevel \u00b6 Dam level DewPointAirTemperatureCloudiness \u00b6 Dew point air temperature cloudiness Dewpoint \u00b6 Dewpoint temperature DewpointAirTemperatureCloudinessSolarradiation \u00b6 Dewpoint temperature, air temperature, cloudiness, solarradiation DischargeBnd \u00b6 Discharge DischargeSalinityTemperatureSorSin \u00b6 Discharge, salinity temperature source-sinks FrictionCoefficient \u00b6 Friction coefficient GateLowerEdgeLevel \u00b6 Gate lower edge level GeneralStructure \u00b6 General structure HorizontalEddyDiffusivityCoefficient \u00b6 Horizontal eddy diffusivity coefficient HorizontalEddyViscosityCoefficient \u00b6 Horizontal eddy viscosity coefficient Humidity \u00b6 Humidity HumidityAirTemperatureCloudiness \u00b6 Combined heat flux terms HumidityAirTemperatureCloudinessSolarRadiation \u00b6 Combined heat flux terms IBotLevType \u00b6 Type of bed-level handling InitialSalinity \u00b6 Initial salinity InitialSalinityTop \u00b6 Initial salinity top layer InitialTemperature \u00b6 Initial temperature InitialVerticalSalinityProfile \u00b6 Initial vertical salinity profile InitialVerticalTemperatureProfile \u00b6 Initial vertical temperature profile InitialWaterLevel \u00b6 Initial water level InternalTidesFrictionCoefficient \u00b6 Internal tides friction coefficient LongWaveRadiation \u00b6 Long wave radiation MovingStationXY \u00b6 Moving observation point for output (time, x, y) NeumannBnd \u00b6 Water level gradient NormalVelocityBnd \u00b6 Normal velocity NudgeSalinityTemperature \u00b6 Nudging salinity and temperature OutflowBnd \u00b6 Outflow Pump \u00b6 Pump capacity QhBnd \u00b6 Discharge-water level dependency Rainfall \u00b6 Precipitation RainfallRate \u00b6 Precipitation RiemannBnd \u00b6 Riemann invariant RiemannVelocityBnd \u00b6 Riemann invariant velocity SalinityBnd \u00b6 Salinity SedimentBnd \u00b6 Suspended sediment ShiptXY \u00b6 shiptxy SolarRadiation \u00b6 Solar radiation StressX \u00b6 eastward wind stress StressXY \u00b6 eastward and northward wind stress StressY \u00b6 northward wind stress TangentialVelocityBnd \u00b6 Tangentional velocity TemperatureBnd \u00b6 Temperature UXUYAdvectionVelocityBnd \u00b6 ux-uy advection velocity VelocityBnd \u00b6 Velocity WaterLevelBnd \u00b6 Water level WavePeriod \u00b6 Wave period WaveSignificantHeight \u00b6 Wave significant height WindFromDirection \u00b6 WindFromDirection WindSpeed \u00b6 WindSpeed WindX \u00b6 Wind x component WindXY \u00b6 Wind vector WindY \u00b6 Wind y component ExtOldTracerQuantity ( str , Enum ) \u00b6 Enum class containing the valid values for the boundary conditions category of the external forcings that are specific to tracers. InitialTracer \u00b6 Initial tracer TracerBnd \u00b6 User-defined tracer","title":"External forcings file"},{"location":"reference/extold/#external-forcings-file","text":"The external forcing .ext file contains the forcing data for a D-Flow FM model. This includes open boundaries, lateral discharges and meteorological forcings. The documentation below only concerns the 'old' format ( ExtForceFile in the MDU file).","title":"External forcings file"},{"location":"reference/extold/#model","text":"","title":"Model"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldExtrapolationMethod","text":"Enum class containing the valid values for the extrapolation_method attribute in the ExtOldForcing class.","title":"ExtOldExtrapolationMethod"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldExtrapolationMethod.NoSpatialExtrapolation","text":"No spatial extrapolation.","title":"NoSpatialExtrapolation"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldExtrapolationMethod.SpatialExtrapolationOutsideOfSourceDataBoundingBox","text":"Do spatial extrapolation outside of source data bounding box.","title":"SpatialExtrapolationOutsideOfSourceDataBoundingBox"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType","text":"Enum class containing the valid values for the filetype attribute in the ExtOldForcing class.","title":"ExtOldFileType"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.ArcInfo","text":"ArcInfo","title":"ArcInfo"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.CurvilinearData","text":"Space-time data on curvilinear grid","title":"CurvilinearData"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.NetCDFGridData","text":"NetCDF grid data (e.g. meteo fields)","title":"NetCDFGridData"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.NetCDFWaveData","text":"NetCDF wave data","title":"NetCDFWaveData"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.Polyfile","text":"Polyfile (< .pol/ .pli>-file). uniform value inside polygon for INITIAL fields","title":"Polyfile"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.Polyline","text":"Polyline (<*.pli>-file)","title":"Polyline"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.Samples","text":"Samples","title":"Samples"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.SpatiallyVaryingWindPressure","text":"Spatially varying wind and pressure","title":"SpatiallyVaryingWindPressure"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.SpiderWebData","text":"Spiderweb data (cyclones)","title":"SpiderWebData"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.TimeSeries","text":"Time series","title":"TimeSeries"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.TimeSeriesMagnitudeAndDirection","text":"Time series magnitude and direction","title":"TimeSeriesMagnitudeAndDirection"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldFileType.TriangulationMagnitudeAndDirection","text":"Triangulation magnitude and direction","title":"TriangulationMagnitudeAndDirection"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldForcing","text":"Class holding the external forcing values.","title":"ExtOldForcing"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldMethod","text":"Enum class containing the valid values for the method attribute in the ExtOldForcing class.","title":"ExtOldMethod"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldMethod.AveragingSpace","text":"Averaging in space","title":"AveragingSpace"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldMethod.InterpolateExtrapolateTime","text":"Interpolate/Extrapolate time","title":"InterpolateExtrapolateTime"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldMethod.InterpolateSpace","text":"Interpolate space","title":"InterpolateSpace"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldMethod.InterpolateTime","text":"Interpolate time","title":"InterpolateTime"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldMethod.InterpolateTimeAndSpace","text":"Interpolate time and space","title":"InterpolateTimeAndSpace"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldMethod.InterpolateTimeAndSpaceSaveWeights","text":"Interpolate time and space, save weights","title":"InterpolateTimeAndSpaceSaveWeights"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldMethod.PassThrough","text":"Pass through (no interpolation)","title":"PassThrough"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldModel","text":"The overall external forcings model that contains the contents of one external forcings file (old format). This model is typically referenced under a FMModel .external_forcing.extforcefile .","title":"ExtOldModel"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldModel.dict","text":"Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dflowfm/extold/models.py def dict ( self , * args , ** kwargs ): return dict ( comment = self . comment , forcing = [ dict ( f ) for f in self . forcing ])","title":"dict()"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity","text":"Enum class containing the valid values for the boundary conditions category of the external forcings.","title":"ExtOldQuantity"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.AdvectionType","text":"Type of advection scheme","title":"AdvectionType"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.AirDensity","text":"Air density","title":"AirDensity"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.AirPressure","text":"AirPressure","title":"AirPressure"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.AirPressureWindXWindY","text":"Atmospheric pressure and wind components","title":"AirPressureWindXWindY"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.AirPressureWindXWindYCharnock","text":"Atmospheric pressure and wind components Charnock","title":"AirPressureWindXWindYCharnock"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.AirTemperature","text":"AirTemperature","title":"AirTemperature"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.AirpressureStressXStressY","text":"Airpressure, eastward and northward wind stress","title":"AirpressureStressXStressY"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.AtmosphericPressure","text":"Atmospheric pressure","title":"AtmosphericPressure"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.BedLevel","text":"Bed level","title":"BedLevel"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.Charnock","text":"Charnock coefficient","title":"Charnock"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.Cloudiness","text":"Cloudiness, or cloud cover (fraction)","title":"Cloudiness"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.DamLevel","text":"Dam level","title":"DamLevel"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.DewPointAirTemperatureCloudiness","text":"Dew point air temperature cloudiness","title":"DewPointAirTemperatureCloudiness"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.Dewpoint","text":"Dewpoint temperature","title":"Dewpoint"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.DewpointAirTemperatureCloudinessSolarradiation","text":"Dewpoint temperature, air temperature, cloudiness, solarradiation","title":"DewpointAirTemperatureCloudinessSolarradiation"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.DischargeBnd","text":"Discharge","title":"DischargeBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.DischargeSalinityTemperatureSorSin","text":"Discharge, salinity temperature source-sinks","title":"DischargeSalinityTemperatureSorSin"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.FrictionCoefficient","text":"Friction coefficient","title":"FrictionCoefficient"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.GateLowerEdgeLevel","text":"Gate lower edge level","title":"GateLowerEdgeLevel"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.GeneralStructure","text":"General structure","title":"GeneralStructure"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.HorizontalEddyDiffusivityCoefficient","text":"Horizontal eddy diffusivity coefficient","title":"HorizontalEddyDiffusivityCoefficient"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.HorizontalEddyViscosityCoefficient","text":"Horizontal eddy viscosity coefficient","title":"HorizontalEddyViscosityCoefficient"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.Humidity","text":"Humidity","title":"Humidity"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.HumidityAirTemperatureCloudiness","text":"Combined heat flux terms","title":"HumidityAirTemperatureCloudiness"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.HumidityAirTemperatureCloudinessSolarRadiation","text":"Combined heat flux terms","title":"HumidityAirTemperatureCloudinessSolarRadiation"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.IBotLevType","text":"Type of bed-level handling","title":"IBotLevType"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.InitialSalinity","text":"Initial salinity","title":"InitialSalinity"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.InitialSalinityTop","text":"Initial salinity top layer","title":"InitialSalinityTop"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.InitialTemperature","text":"Initial temperature","title":"InitialTemperature"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.InitialVerticalSalinityProfile","text":"Initial vertical salinity profile","title":"InitialVerticalSalinityProfile"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.InitialVerticalTemperatureProfile","text":"Initial vertical temperature profile","title":"InitialVerticalTemperatureProfile"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.InitialWaterLevel","text":"Initial water level","title":"InitialWaterLevel"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.InternalTidesFrictionCoefficient","text":"Internal tides friction coefficient","title":"InternalTidesFrictionCoefficient"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.LongWaveRadiation","text":"Long wave radiation","title":"LongWaveRadiation"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.MovingStationXY","text":"Moving observation point for output (time, x, y)","title":"MovingStationXY"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.NeumannBnd","text":"Water level gradient","title":"NeumannBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.NormalVelocityBnd","text":"Normal velocity","title":"NormalVelocityBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.NudgeSalinityTemperature","text":"Nudging salinity and temperature","title":"NudgeSalinityTemperature"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.OutflowBnd","text":"Outflow","title":"OutflowBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.Pump","text":"Pump capacity","title":"Pump"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.QhBnd","text":"Discharge-water level dependency","title":"QhBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.Rainfall","text":"Precipitation","title":"Rainfall"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.RainfallRate","text":"Precipitation","title":"RainfallRate"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.RiemannBnd","text":"Riemann invariant","title":"RiemannBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.RiemannVelocityBnd","text":"Riemann invariant velocity","title":"RiemannVelocityBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.SalinityBnd","text":"Salinity","title":"SalinityBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.SedimentBnd","text":"Suspended sediment","title":"SedimentBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.ShiptXY","text":"shiptxy","title":"ShiptXY"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.SolarRadiation","text":"Solar radiation","title":"SolarRadiation"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.StressX","text":"eastward wind stress","title":"StressX"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.StressXY","text":"eastward and northward wind stress","title":"StressXY"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.StressY","text":"northward wind stress","title":"StressY"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.TangentialVelocityBnd","text":"Tangentional velocity","title":"TangentialVelocityBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.TemperatureBnd","text":"Temperature","title":"TemperatureBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.UXUYAdvectionVelocityBnd","text":"ux-uy advection velocity","title":"UXUYAdvectionVelocityBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.VelocityBnd","text":"Velocity","title":"VelocityBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.WaterLevelBnd","text":"Water level","title":"WaterLevelBnd"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.WavePeriod","text":"Wave period","title":"WavePeriod"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.WaveSignificantHeight","text":"Wave significant height","title":"WaveSignificantHeight"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.WindFromDirection","text":"WindFromDirection","title":"WindFromDirection"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.WindSpeed","text":"WindSpeed","title":"WindSpeed"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.WindX","text":"Wind x component","title":"WindX"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.WindXY","text":"Wind vector","title":"WindXY"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldQuantity.WindY","text":"Wind y component","title":"WindY"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldTracerQuantity","text":"Enum class containing the valid values for the boundary conditions category of the external forcings that are specific to tracers.","title":"ExtOldTracerQuantity"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldTracerQuantity.InitialTracer","text":"Initial tracer","title":"InitialTracer"},{"location":"reference/extold/#hydrolib.core.dflowfm.extold.models.ExtOldTracerQuantity.TracerBnd","text":"User-defined tracer","title":"TracerBnd"},{"location":"reference/forcing/","text":"Forcings .bc file \u00b6 The forcings .bc files contain forcing data for point locations, for example time series input for a boundary condition. Various quantities and function types are supported. The forcings file is represented by the classes below. Model \u00b6 Representation of a .bc file in various classes. Most relevant classes are: ForcingModel: toplevel class containing the whole .bc file contents. ForcingBase subclasses: containing the actual data columns, for example: TimeSeries, HarmonicComponent, AstronomicComponent, HarmonicCorrection, AstronomicCorrection, Constant, T3D. Astronomic ( ForcingBase ) pydantic-model \u00b6 Subclass for a .bc file [Forcing] block with astronomic components data. AstronomicCorrection ( ForcingBase ) pydantic-model \u00b6 Subclass for a .bc file [Forcing] block with astronomic components correction data. Constant ( ForcingBase ) pydantic-model \u00b6 Subclass for a .bc file [Forcing] block with constant value data. ForcingBase ( DataBlockINIBasedModel ) pydantic-model \u00b6 The base class of a single [Forcing] block in a .bc forcings file. Typically subclassed, for the specific types of forcing data, e.g, Harmonic. This model is for example referenced under a ForcingModel .forcing[..] . validate ( v ) classmethod \u00b6 Try to initialize subclass based on the function field. This field is compared to each function field of the derived models of ForcingBase or models derived from derived models. The derived model with an equal function type will be initialized. Exceptions: Type Description ValueError When the given type is not a known structure type. Source code in hydrolib/core/dflowfm/bc/models.py @classmethod def validate ( cls , v ): \"\"\"Try to initialize subclass based on the `function` field. This field is compared to each `function` field of the derived models of `ForcingBase` or models derived from derived models. The derived model with an equal function type will be initialized. Raises: ValueError: When the given type is not a known structure type. \"\"\" # should be replaced by discriminated unions once merged # https://github.com/samuelcolvin/pydantic/pull/2336 if isinstance ( v , dict ): function_string = v . get ( \"function\" , \"\" ) . lower () function_type = get_type_based_on_subclass_default_value ( cls , \"function\" , function_string ) if function_type is not None : return function_type ( ** v ) else : raise ValueError ( f \"Function of { cls . __name__ } with name= { v . get ( 'name' , '' ) } and function= { v . get ( 'function' , '' ) } is not recognized.\" ) return v ForcingData \u00b6 Data type that selects from three different types of forcing data: * a scalar float constant * \"realtime\" keyword, indicating externally controlled. * A ForcingModel coming from a .bc file. ForcingGeneral ( INIGeneral ) pydantic-model \u00b6 [General] section with .bc file metadata. ForcingModel ( INIModel ) pydantic-model \u00b6 The overall model that contains the contents of one .bc forcings file. This model is for example referenced under a ExtModel .boundary[..].forcingfile[..] . Harmonic ( ForcingBase ) pydantic-model \u00b6 Subclass for a .bc file [Forcing] block with harmonic components data. HarmonicCorrection ( ForcingBase ) pydantic-model \u00b6 Subclass for a .bc file [Forcing] block with harmonic components correction data. QHTable ( ForcingBase ) pydantic-model \u00b6 Subclass for a .bc file [Forcing] block with Q-h table data. QuantityUnitPair ( BaseModel ) pydantic-model \u00b6 A .bc file header lines tuple containing a quantity name, its unit and optionally a vertical position index. RealTime ( str , Enum ) \u00b6 Enum class containing the valid value for the \"realtime\" reserved keyword for real-time controlled forcing data, e.g., for hydraulic structures. This class is used inside the ForcingData Union, to force detection of the realtime keyword, prior to considering it a filename. realtime \u00b6 str: Realtime data source, externally provided T3D ( VectorForcingBase ) pydantic-model \u00b6 Subclass for a .bc file [Forcing] block with 3D timeseries data. get_number_of_repetitions ( values : Dict ) -> int classmethod \u00b6 Gets the number of expected quantityunitpairs for each vector element. Defaults to 1. Source code in hydrolib/core/dflowfm/bc/models.py @classmethod def get_number_of_repetitions ( cls , values : Dict ) -> int : verticalpositions = values . get ( \"vertpositions\" ) # Since the renaming root validator may not have been run yet, in this # method we explicitly check old keywords for backwards compatibility: if verticalpositions is None : # try to get the value from any of the older keywords for old_keyword in cls . _keys_to_rename [ \"vertpositions\" ]: verticalpositions = values . get ( old_keyword ) if verticalpositions is not None : break if verticalpositions is None : raise ValueError ( \"vertPositions is not provided\" ) number_of_verticalpositions = ( len ( verticalpositions ) if isinstance ( verticalpositions , List ) else len ( verticalpositions . split ()) ) return number_of_verticalpositions rename_keys ( values : Dict ) -> Dict classmethod \u00b6 Renames some old keywords to the currently supported keywords. Source code in hydrolib/core/dflowfm/bc/models.py @root_validator ( allow_reuse = True , pre = True ) def rename_keys ( cls , values : Dict ) -> Dict : \"\"\"Renames some old keywords to the currently supported keywords.\"\"\" return rename_keys_for_backwards_compatibility ( values , cls . _keys_to_rename ) TimeInterpolation ( str , Enum ) \u00b6 Enum class containing the valid values for the time interpolation. block_from \u00b6 str: Equal to that at the start of the time interval (latest specified time value). block_to \u00b6 str: Equal to that at the end of the time interval (upcoming specified time value). linear \u00b6 str: Linear interpolation between times. TimeSeries ( VectorForcingBase ) pydantic-model \u00b6 Subclass for a .bc file [Forcing] block with timeseries data. rename_keys ( values : Dict ) -> Dict classmethod \u00b6 Renames some old keywords to the currently supported keywords. Source code in hydrolib/core/dflowfm/bc/models.py @root_validator ( allow_reuse = True , pre = True ) def rename_keys ( cls , values : Dict ) -> Dict : \"\"\"Renames some old keywords to the currently supported keywords.\"\"\" return rename_keys_for_backwards_compatibility ( values , { \"timeinterpolation\" : [ \"time_interpolation\" ], }, ) VectorForcingBase ( ForcingBase ) pydantic-model \u00b6 The base class of a single [Forcing] block that supports vectors in a .bc forcings file. get_number_of_repetitions ( values : Dict ) -> int classmethod \u00b6 Gets the number of expected quantityunitpairs for each vector element. Defaults to 1. Source code in hydrolib/core/dflowfm/bc/models.py @classmethod def get_number_of_repetitions ( cls , values : Dict ) -> int : \"\"\"Gets the number of expected quantityunitpairs for each vector element. Defaults to 1.\"\"\" return 1 validate_and_update_quantityunitpairs ( values : Dict ) -> Dict classmethod \u00b6 Validates and, if required, updates vector quantity unit pairs. Parameters: Name Type Description Default values Dict Dictionary of values to be used to validate or required Exceptions: Type Description ValueError When a quantity unit pair is found in a vector where it does not belong. ValueError When the number of quantity unit pairs in a vectors is not as expected. Returns: Type Description Dict Dictionary of validates values. Source code in hydrolib/core/dflowfm/bc/models.py @root_validator ( pre = True ) def validate_and_update_quantityunitpairs ( cls , values : Dict ) -> Dict : \"\"\" Validates and, if required, updates vector quantity unit pairs. Args: values (Dict): Dictionary of values to be used to validate or update vector quantity unit pairs. Raises: ValueError: When a quantity unit pair is found in a vector where it does not belong. ValueError: When the number of quantity unit pairs in a vectors is not as expected. Returns: Dict: Dictionary of validates values. \"\"\" quantityunitpairs = values [ \"quantityunitpair\" ] vector = values . get ( \"vector\" ) number_of_element_repetitions = cls . get_number_of_repetitions ( values ) VectorForcingBase . _process_vectordefinition_or_check_quantityunitpairs ( vector , quantityunitpairs , number_of_element_repetitions ) return values VectorQuantityUnitPairs ( BaseModel ) pydantic-model \u00b6 A subset of .bc file header lines containing a vector quantity definition, followed by all component quantity names, their unit and optionally their vertical position indexes. VerticalInterpolation ( str , Enum ) \u00b6 Enum class containing the valid values for the vertical position type, which defines what the numeric values for vertical position specification mean. block \u00b6 str: Equal to the value at the directly lower specified vertical position. linear \u00b6 str: Linear interpolation between vertical positions. log \u00b6 str: Logarithmic interpolation between vertical positions (e.g. vertical velocity profiles). VerticalPositionType ( str , Enum ) \u00b6 Enum class containing the valid values for the vertical position type. percentage_bed \u00b6 str: Percentage with respect to the water depth from the bed upward. z_bed \u00b6 str: Absolute distance from the bed upward. z_datum \u00b6 str: z-coordinate with respect to the reference level of the model. z_surf \u00b6 str: Absolute distance from the free surface downward.","title":"Forcings .bc file"},{"location":"reference/forcing/#forcings-bc-file","text":"The forcings .bc files contain forcing data for point locations, for example time series input for a boundary condition. Various quantities and function types are supported. The forcings file is represented by the classes below.","title":"Forcings .bc file"},{"location":"reference/forcing/#model","text":"Representation of a .bc file in various classes. Most relevant classes are: ForcingModel: toplevel class containing the whole .bc file contents. ForcingBase subclasses: containing the actual data columns, for example: TimeSeries, HarmonicComponent, AstronomicComponent, HarmonicCorrection, AstronomicCorrection, Constant, T3D.","title":"Model"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.Astronomic","text":"Subclass for a .bc file [Forcing] block with astronomic components data.","title":"Astronomic"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.AstronomicCorrection","text":"Subclass for a .bc file [Forcing] block with astronomic components correction data.","title":"AstronomicCorrection"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.Constant","text":"Subclass for a .bc file [Forcing] block with constant value data.","title":"Constant"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.ForcingBase","text":"The base class of a single [Forcing] block in a .bc forcings file. Typically subclassed, for the specific types of forcing data, e.g, Harmonic. This model is for example referenced under a ForcingModel .forcing[..] .","title":"ForcingBase"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.ForcingBase.validate","text":"Try to initialize subclass based on the function field. This field is compared to each function field of the derived models of ForcingBase or models derived from derived models. The derived model with an equal function type will be initialized. Exceptions: Type Description ValueError When the given type is not a known structure type. Source code in hydrolib/core/dflowfm/bc/models.py @classmethod def validate ( cls , v ): \"\"\"Try to initialize subclass based on the `function` field. This field is compared to each `function` field of the derived models of `ForcingBase` or models derived from derived models. The derived model with an equal function type will be initialized. Raises: ValueError: When the given type is not a known structure type. \"\"\" # should be replaced by discriminated unions once merged # https://github.com/samuelcolvin/pydantic/pull/2336 if isinstance ( v , dict ): function_string = v . get ( \"function\" , \"\" ) . lower () function_type = get_type_based_on_subclass_default_value ( cls , \"function\" , function_string ) if function_type is not None : return function_type ( ** v ) else : raise ValueError ( f \"Function of { cls . __name__ } with name= { v . get ( 'name' , '' ) } and function= { v . get ( 'function' , '' ) } is not recognized.\" ) return v","title":"validate()"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.ForcingData","text":"Data type that selects from three different types of forcing data: * a scalar float constant * \"realtime\" keyword, indicating externally controlled. * A ForcingModel coming from a .bc file.","title":"ForcingData"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.ForcingGeneral","text":"[General] section with .bc file metadata.","title":"ForcingGeneral"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.ForcingModel","text":"The overall model that contains the contents of one .bc forcings file. This model is for example referenced under a ExtModel .boundary[..].forcingfile[..] .","title":"ForcingModel"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.Harmonic","text":"Subclass for a .bc file [Forcing] block with harmonic components data.","title":"Harmonic"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.HarmonicCorrection","text":"Subclass for a .bc file [Forcing] block with harmonic components correction data.","title":"HarmonicCorrection"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.QHTable","text":"Subclass for a .bc file [Forcing] block with Q-h table data.","title":"QHTable"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.QuantityUnitPair","text":"A .bc file header lines tuple containing a quantity name, its unit and optionally a vertical position index.","title":"QuantityUnitPair"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.RealTime","text":"Enum class containing the valid value for the \"realtime\" reserved keyword for real-time controlled forcing data, e.g., for hydraulic structures. This class is used inside the ForcingData Union, to force detection of the realtime keyword, prior to considering it a filename.","title":"RealTime"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.RealTime.realtime","text":"str: Realtime data source, externally provided","title":"realtime"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.T3D","text":"Subclass for a .bc file [Forcing] block with 3D timeseries data.","title":"T3D"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.T3D.get_number_of_repetitions","text":"Gets the number of expected quantityunitpairs for each vector element. Defaults to 1. Source code in hydrolib/core/dflowfm/bc/models.py @classmethod def get_number_of_repetitions ( cls , values : Dict ) -> int : verticalpositions = values . get ( \"vertpositions\" ) # Since the renaming root validator may not have been run yet, in this # method we explicitly check old keywords for backwards compatibility: if verticalpositions is None : # try to get the value from any of the older keywords for old_keyword in cls . _keys_to_rename [ \"vertpositions\" ]: verticalpositions = values . get ( old_keyword ) if verticalpositions is not None : break if verticalpositions is None : raise ValueError ( \"vertPositions is not provided\" ) number_of_verticalpositions = ( len ( verticalpositions ) if isinstance ( verticalpositions , List ) else len ( verticalpositions . split ()) ) return number_of_verticalpositions","title":"get_number_of_repetitions()"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.T3D.rename_keys","text":"Renames some old keywords to the currently supported keywords. Source code in hydrolib/core/dflowfm/bc/models.py @root_validator ( allow_reuse = True , pre = True ) def rename_keys ( cls , values : Dict ) -> Dict : \"\"\"Renames some old keywords to the currently supported keywords.\"\"\" return rename_keys_for_backwards_compatibility ( values , cls . _keys_to_rename )","title":"rename_keys()"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.TimeInterpolation","text":"Enum class containing the valid values for the time interpolation.","title":"TimeInterpolation"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.TimeInterpolation.block_from","text":"str: Equal to that at the start of the time interval (latest specified time value).","title":"block_from"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.TimeInterpolation.block_to","text":"str: Equal to that at the end of the time interval (upcoming specified time value).","title":"block_to"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.TimeInterpolation.linear","text":"str: Linear interpolation between times.","title":"linear"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.TimeSeries","text":"Subclass for a .bc file [Forcing] block with timeseries data.","title":"TimeSeries"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.TimeSeries.rename_keys","text":"Renames some old keywords to the currently supported keywords. Source code in hydrolib/core/dflowfm/bc/models.py @root_validator ( allow_reuse = True , pre = True ) def rename_keys ( cls , values : Dict ) -> Dict : \"\"\"Renames some old keywords to the currently supported keywords.\"\"\" return rename_keys_for_backwards_compatibility ( values , { \"timeinterpolation\" : [ \"time_interpolation\" ], }, )","title":"rename_keys()"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VectorForcingBase","text":"The base class of a single [Forcing] block that supports vectors in a .bc forcings file.","title":"VectorForcingBase"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VectorForcingBase.get_number_of_repetitions","text":"Gets the number of expected quantityunitpairs for each vector element. Defaults to 1. Source code in hydrolib/core/dflowfm/bc/models.py @classmethod def get_number_of_repetitions ( cls , values : Dict ) -> int : \"\"\"Gets the number of expected quantityunitpairs for each vector element. Defaults to 1.\"\"\" return 1","title":"get_number_of_repetitions()"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VectorForcingBase.validate_and_update_quantityunitpairs","text":"Validates and, if required, updates vector quantity unit pairs. Parameters: Name Type Description Default values Dict Dictionary of values to be used to validate or required Exceptions: Type Description ValueError When a quantity unit pair is found in a vector where it does not belong. ValueError When the number of quantity unit pairs in a vectors is not as expected. Returns: Type Description Dict Dictionary of validates values. Source code in hydrolib/core/dflowfm/bc/models.py @root_validator ( pre = True ) def validate_and_update_quantityunitpairs ( cls , values : Dict ) -> Dict : \"\"\" Validates and, if required, updates vector quantity unit pairs. Args: values (Dict): Dictionary of values to be used to validate or update vector quantity unit pairs. Raises: ValueError: When a quantity unit pair is found in a vector where it does not belong. ValueError: When the number of quantity unit pairs in a vectors is not as expected. Returns: Dict: Dictionary of validates values. \"\"\" quantityunitpairs = values [ \"quantityunitpair\" ] vector = values . get ( \"vector\" ) number_of_element_repetitions = cls . get_number_of_repetitions ( values ) VectorForcingBase . _process_vectordefinition_or_check_quantityunitpairs ( vector , quantityunitpairs , number_of_element_repetitions ) return values","title":"validate_and_update_quantityunitpairs()"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VectorQuantityUnitPairs","text":"A subset of .bc file header lines containing a vector quantity definition, followed by all component quantity names, their unit and optionally their vertical position indexes.","title":"VectorQuantityUnitPairs"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VerticalInterpolation","text":"Enum class containing the valid values for the vertical position type, which defines what the numeric values for vertical position specification mean.","title":"VerticalInterpolation"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VerticalInterpolation.block","text":"str: Equal to the value at the directly lower specified vertical position.","title":"block"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VerticalInterpolation.linear","text":"str: Linear interpolation between vertical positions.","title":"linear"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VerticalInterpolation.log","text":"str: Logarithmic interpolation between vertical positions (e.g. vertical velocity profiles).","title":"log"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VerticalPositionType","text":"Enum class containing the valid values for the vertical position type.","title":"VerticalPositionType"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VerticalPositionType.percentage_bed","text":"str: Percentage with respect to the water depth from the bed upward.","title":"percentage_bed"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VerticalPositionType.z_bed","text":"str: Absolute distance from the bed upward.","title":"z_bed"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VerticalPositionType.z_datum","text":"str: z-coordinate with respect to the reference level of the model.","title":"z_datum"},{"location":"reference/forcing/#hydrolib.core.dflowfm.bc.models.VerticalPositionType.z_surf","text":"str: Absolute distance from the free surface downward.","title":"z_surf"},{"location":"reference/friction/","text":"1D roughness .ini files \u00b6 The friction module provides the specific logic for accessing friction/1D roughness files for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. A 1D roughness file is described by the classes below. Model \u00b6 FrictBranch ( INIBasedModel ) pydantic-model \u00b6 A [Branch] block for use inside a friction file. Each block can define the roughness value(s) on a particular branch. FrictGeneral ( INIGeneral ) pydantic-model \u00b6 The friction file's [General] section with file meta data. FrictGlobal ( INIBasedModel ) pydantic-model \u00b6 A [Global] block for use inside a friction file. Multiple of such blocks may be present to define multiple frictionId classes. FrictionModel ( INIModel ) pydantic-model \u00b6 The overall friction model that contains the contents of one friction file. This model is typically referenced under a FMModel .geometry.frictfile[..] . Attributes: Name Type Description general FrictGeneral [General] block with file metadata. global_ List[FrictGlobal] Definitions of [Global] friction classes. branch List[FrictBranch] Definitions of [Branch] friction values. FrictionType ( str , Enum ) \u00b6 Enum class containing the valid values for the frictionType attribute in several subclasses of Structure/CrossSection/friction.models. chezy \u00b6 str: Ch\u00e9zy C [m 1/2 /s] debosbijkerk \u00b6 str: De Bos-Bijkerk \u03b3 [1/s] manning \u00b6 str: Manning n [s/m 1/3 ] strickler \u00b6 str: Strickler k_s [m 1/3 /s] stricklernikuradse \u00b6 str: Nikuradse k_n [m] walllawnikuradse \u00b6 str: Nikuradse k_n [m] whitecolebrook \u00b6 str: Nikuradse k_n [m]","title":"Friction"},{"location":"reference/friction/#1d-roughness-ini-files","text":"The friction module provides the specific logic for accessing friction/1D roughness files for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. A 1D roughness file is described by the classes below.","title":"1D roughness .ini files"},{"location":"reference/friction/#model","text":"","title":"Model"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictBranch","text":"A [Branch] block for use inside a friction file. Each block can define the roughness value(s) on a particular branch.","title":"FrictBranch"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictGeneral","text":"The friction file's [General] section with file meta data.","title":"FrictGeneral"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictGlobal","text":"A [Global] block for use inside a friction file. Multiple of such blocks may be present to define multiple frictionId classes.","title":"FrictGlobal"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictionModel","text":"The overall friction model that contains the contents of one friction file. This model is typically referenced under a FMModel .geometry.frictfile[..] . Attributes: Name Type Description general FrictGeneral [General] block with file metadata. global_ List[FrictGlobal] Definitions of [Global] friction classes. branch List[FrictBranch] Definitions of [Branch] friction values.","title":"FrictionModel"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictionType","text":"Enum class containing the valid values for the frictionType attribute in several subclasses of Structure/CrossSection/friction.models.","title":"FrictionType"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictionType.chezy","text":"str: Ch\u00e9zy C [m 1/2 /s]","title":"chezy"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictionType.debosbijkerk","text":"str: De Bos-Bijkerk \u03b3 [1/s]","title":"debosbijkerk"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictionType.manning","text":"str: Manning n [s/m 1/3 ]","title":"manning"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictionType.strickler","text":"str: Strickler k_s [m 1/3 /s]","title":"strickler"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictionType.stricklernikuradse","text":"str: Nikuradse k_n [m]","title":"stricklernikuradse"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictionType.walllawnikuradse","text":"str: Nikuradse k_n [m]","title":"walllawnikuradse"},{"location":"reference/friction/#hydrolib.core.dflowfm.friction.models.FrictionType.whitecolebrook","text":"str: Nikuradse k_n [m]","title":"whitecolebrook"},{"location":"reference/glossary/","text":"Glossary \u00b6 The list below is a nonexhaustive list of terminology and concepts used in HYDROLIB(-core) and Delft3D Flexible Mesh. A \u00b6 B \u00b6 BC file \u00b6 Input file containing the actual forcing data for model forcings specified elsewhere in the model input, for example time series or astronomical components. Originates from boundary conditions as specified in the external forcings file , but nowadays also used in structure files . More details about the syntax and the various supported function types in the Delft3D FM User Manual . Boundary condition \u00b6 Flow (or constituent) boundary condition that forces a D-Flow FM model, such as waterlevel and discharge boundary conditions. Defined in the external forcings file . More details in the Delft3D FM User Manual . Branch \u00b6 The network edges in a network topology of 1D models. The computational grid points are positioned on these branches using branch id and a chainage value. Branch Id \u00b6 Identification text string for a particular branch in a 1D network. C \u00b6 Chainage \u00b6 The distance along a 1D network branch to define a specific location on that branch. Always used in combination with a branch Id . CF conventions \u00b6 Established metadata conventions for storing all kinds of data, e.g., model input and output, in NetCDF files. More details on: https://cfconventions.org/. HYDROLIB-core and Delft3D Flexible Mesh rely on CF, and extend this with UGRID conventions where unstructured grids are applicable. Computational backend \u00b6 Computational core, also called kernel. The program/library of simulation software that does the actual calculations. Often also available with a graphical user interface on top of it. Cross section files \u00b6 Input files for D-Flow FM that define the 1D network's cross sections. Two parts: cross section definition file and cross section location files . Not to be confused with observation cross section files ! Cross section definition file \u00b6 Input file for D-Flow FM that defines the various cross section shapes in a model with a 1D network. Format is INI-like. More details in the Delft3D FM User Manual . Cross section location file \u00b6 Input file for D-Flow FM that defines the location of cross section shapes in a model with a 1D network. Each location refers to a (possible shared) cross section definition . Format is INI-like. More details in the Delft3D FM User Manual . D \u00b6 Deltares conventions \u00b6 A proposal for additional NetCDF conventions that build on the existing UGRID conventions , intended to properly describe 1D network topologies as a coordinate space on which 1D computational grids are defined. Also 1D2D grid couplings are included. More details in: the Delft3D FM User Manual . D-Flow FM \u00b6 D-Flow Flexible Mesh. The computational backend that solves 1D/2D/3D hydrodynamics in the Delf3D Flexible Mesh Suite. Toplevel input is the MDU file . More details in the Delft3D FM User Manual . D-HYDRO Suite 1D2D (Beta) \u00b6 Integral software suite for hydraulic 1D2D modelling, including rainfall runoff and realtime control. More details on: https://www.deltares.nl/nl/d-hydro-suite-1d2d-beta/. DIMR \u00b6 Deltares Integrated Model Runner. Executable/library that runs integrated models by coupling multiple computational backends in a simulation timeloop. Uses a single DIMR config file as input. DIMR config file \u00b6 Input file for DIMR (typically dimr_config.xml ) for an integrated model run, describing which models are coupled and which quantities need to be exchanged. E \u00b6 Edge (mesh) \u00b6 A geometrical \"line\" in a 1D, 2D or 3D mesh. Connects two mesh nodes as its end points. Building block of the UGRID-conventions . External forcings file \u00b6 Input file for D-Flow FM describing model forcings such as boundary conditions , laterals and meteo . Format is INI-like. More details in the Delft3D FM User Manual . F \u00b6 Face (mesh) \u00b6 A geometrical \"cell\" in a 2D mesh. Formed by 3 or more mesh nodes as its vertices. Building block of the UGRID-conventions . Flow link \u00b6 An open connection/interface between two flow nodes in the staggered D-Flow FM model grid. Is the same as a \"velocity point\", and corresponds with (but is not equal to) an edge , both in 1D and in 2D. In 3D a flow link corresponds with a 3D face between two volumes . Flow node \u00b6 A single finite volume \"cell\" in the staggered D-Flow FM model grid. Is the same as a \"pressure point\", and is in fact a face in 2D/3D or a node in 1D. G \u00b6 Grid \u00b6 The computational grid on which a flow simulation is done. The grid for D-Flow FM is defined in an input net file , and also appears (slightly differently) in the output map file . Grid snapping \u00b6 The snapping of D-Flow FM model input in x,y-coordinates to discrete locations in the staggered model grid . This process makes most model input independent of the chosen model grid and grid resolution. Snapping is done either to (sets of) flow nodes or (sequence of) flow links , depending on whether pressure-point data or velocity-point data is concerned. H \u00b6 His file \u00b6 Output file of D-Flow FM containing model results as time series on a specific set of discrete locations, which are typically the hydraulic structures, observation stations and more. More details in the Delft3D FM User Manual . I \u00b6 Integrated model \u00b6 Model consisting of more than one model. Typically used when multiple computational backends are coupled, for example D-Flow FM and Rainfall Runoff or D-Flow FM and Real Time Control . Integrated models can be run using the Deltares Integrated Model Runner (DIMR) . INI-files \u00b6 Delft3D FM uses several input files that are formatted in an INI-like syntax. The abstract syntax depends on the particular file type, see: cross section files , initial field file , external forcings file , MDU file , observation files , rougness file , structure file . Initial field file \u00b6 Input file for D-Flow FM describing initial conditions and other spatially varying parameter fields. Format is INI-like. More details in the Delft3D FM User Manual . J \u00b6 K \u00b6 L \u00b6 Lateral \u00b6 Lateral discharge in D-Flow FM , which acts as a source (or sink) of volume. Defined in the external forcings file . The actual forcing data may come from timeseries in a .bc file or from RR a coupled/integrated model. More details in the Delft3D FM User Manual . M \u00b6 Map file \u00b6 Output file of D-Flow FM containing the model results on all grid points. More details in the Delft3D FM User Manual . MDU file \u00b6 Main input file of D-Flow FM . Format is INI-like. More details in the Delft3D FM User Manual . meteo \u00b6 Meteorological forcings of a model. Typically sources (or sinks) of volume via precipitation and evaporation, or forcing via wind. For D-Flow FM defined in the external forcings file . More details in the Delft3D FM User Manual . mesh \u00b6 See grid . N \u00b6 Net file \u00b6 Or grid file. Input file for D-Flow FM containing the computational model grid. Format is NetCDF, adhering to CF - and UGRID -conventions, and optionally also the Deltares-extension for 1D network topology and geometry. NetCDF \u00b6 File format used by HYDROLIB-core and Delft3D Flexible Mesh for the model input grid and for model results in output files. These files typically adhere to the CF conventions and sometimes UGRID conventions . Node (mesh) \u00b6 A geometrical \"point\" in a 1D, 2D or 3D mesh. Defined by x- and y-coordinate, in 3D also a z-coordinate. Can be connected by mesh edges , and can form the vertices of a mesh face . Building block of the UGRID-conventions . O \u00b6 Observation files \u00b6 Files that define the model locations for which output should be produced in the his file . Two types: observation point file and observation cross section file . Observation cross section file \u00b6 Input file for D-Flow FM that describes the model locations for which (cumulative) flow \"flux\" output should be produced in the his file . For example: cumulative discharge, salinity transport. Applies both to 1D, 2D, 1D2D and 3D models. Format is INI-like. More details in the Delft3D FM User Manual . Observation point file \u00b6 Input file for D-Flow FM that describes the model point locations for which local output should be produced in the his file . For example: waterlevel, velocity vector/magnitude, tracer concentration as instantanous values. Applies both to 1D, 2D, 1D2D and 3D models. Format is INI-like. More details in the Delft3D FM User Manual . P \u00b6 Polyline file \u00b6 File containing a sequence of polylines in model coordinates. Each polyline has header lines with a label and row+column count, and at least a list of x, y-points. More than 2 columns may be present (z, data1, ...) for particular model inputs, see for example the fixed weir file . More details in the Delft3D FM User Manual . Polygon file \u00b6 See polyline file . The point sequences are interpreted as closed polygons. Q \u00b6 R \u00b6 Rainfall Runoff \u00b6 RR for short. The computational backend that solves lumped rainfall runoff, offering various runoff concepts. Toplevel input is the sobek_3b.fnm file. Part of the D-Hydrology software module. More details on: https://www.deltares.nl/en/software/module/d-hydrology . Real Time Control \u00b6 RTC for short. The computational backend for real-time control of hydraulic model components (typically hydraulic structures). Toplevel input is in various rtc*.xml files. Part of the D-Real Time Control software module. More details on: https://www.deltares.nl/en/software/module/d-real-time-control . Roughness file \u00b6 Input file for D-Flow FM describing roughness values on the 1D network. Format is INI-like. More details in the Delft3D FM User Manual . S \u00b6 Sample file \u00b6 File containing an unstructured set of sample point values. Typically used as input file for initial fields or other spatially varying fields in the initial fields file . More details in the Delft3D FM User Manual . Staggered grid \u00b6 Discretization method used in D-Flow FM where the PDE variables are not all defined on the same topological grid locations. Water level, concentrations and other volume-related variables are defined on the pressure points (also: flow nodes ), and the fluxes and other transport-related variables are defined on the velocity points (also: flow links ). Structure file \u00b6 Input file for D-Flow FM containing the hydraulic structures. Format is INI-like. More details in the Delft3D FM User Manual . T \u00b6 U \u00b6 UGRID conventions \u00b6 Metadata conventions for storing unstructured grids in NetCDF files. More details on: http://ugrid-conventions.github.io/ugrid-conventions/ . V \u00b6 volume (mesh) \u00b6 A geometrical \"cell\" in a 3D mesh. Formed by 4 or more mesh nodes as its vertices (or: 4 or more mesh faces as its \"sides\"). Building block of the UGRID-conventions . W \u00b6 X \u00b6 XYZ file \u00b6 See sample file . Y \u00b6 Z \u00b6","title":"Glossary"},{"location":"reference/glossary/#glossary","text":"The list below is a nonexhaustive list of terminology and concepts used in HYDROLIB(-core) and Delft3D Flexible Mesh.","title":"Glossary"},{"location":"reference/glossary/#a","text":"","title":"A"},{"location":"reference/glossary/#b","text":"","title":"B"},{"location":"reference/glossary/#bc-file","text":"Input file containing the actual forcing data for model forcings specified elsewhere in the model input, for example time series or astronomical components. Originates from boundary conditions as specified in the external forcings file , but nowadays also used in structure files . More details about the syntax and the various supported function types in the Delft3D FM User Manual .","title":"BC file"},{"location":"reference/glossary/#boundary-condition","text":"Flow (or constituent) boundary condition that forces a D-Flow FM model, such as waterlevel and discharge boundary conditions. Defined in the external forcings file . More details in the Delft3D FM User Manual .","title":"Boundary condition"},{"location":"reference/glossary/#branch","text":"The network edges in a network topology of 1D models. The computational grid points are positioned on these branches using branch id and a chainage value.","title":"Branch"},{"location":"reference/glossary/#branch-id","text":"Identification text string for a particular branch in a 1D network.","title":"Branch Id"},{"location":"reference/glossary/#c","text":"","title":"C"},{"location":"reference/glossary/#chainage","text":"The distance along a 1D network branch to define a specific location on that branch. Always used in combination with a branch Id .","title":"Chainage"},{"location":"reference/glossary/#cf-conventions","text":"Established metadata conventions for storing all kinds of data, e.g., model input and output, in NetCDF files. More details on: https://cfconventions.org/. HYDROLIB-core and Delft3D Flexible Mesh rely on CF, and extend this with UGRID conventions where unstructured grids are applicable.","title":"CF conventions"},{"location":"reference/glossary/#computational-backend","text":"Computational core, also called kernel. The program/library of simulation software that does the actual calculations. Often also available with a graphical user interface on top of it.","title":"Computational backend"},{"location":"reference/glossary/#cross-section-files","text":"Input files for D-Flow FM that define the 1D network's cross sections. Two parts: cross section definition file and cross section location files . Not to be confused with observation cross section files !","title":"Cross section files"},{"location":"reference/glossary/#cross-section-definition-file","text":"Input file for D-Flow FM that defines the various cross section shapes in a model with a 1D network. Format is INI-like. More details in the Delft3D FM User Manual .","title":"Cross section definition file"},{"location":"reference/glossary/#cross-section-location-file","text":"Input file for D-Flow FM that defines the location of cross section shapes in a model with a 1D network. Each location refers to a (possible shared) cross section definition . Format is INI-like. More details in the Delft3D FM User Manual .","title":"Cross section location file"},{"location":"reference/glossary/#d","text":"","title":"D"},{"location":"reference/glossary/#deltares-conventions","text":"A proposal for additional NetCDF conventions that build on the existing UGRID conventions , intended to properly describe 1D network topologies as a coordinate space on which 1D computational grids are defined. Also 1D2D grid couplings are included. More details in: the Delft3D FM User Manual .","title":"Deltares conventions"},{"location":"reference/glossary/#d-flow-fm","text":"D-Flow Flexible Mesh. The computational backend that solves 1D/2D/3D hydrodynamics in the Delf3D Flexible Mesh Suite. Toplevel input is the MDU file . More details in the Delft3D FM User Manual .","title":"D-Flow FM"},{"location":"reference/glossary/#d-hydro-suite-1d2d-beta","text":"Integral software suite for hydraulic 1D2D modelling, including rainfall runoff and realtime control. More details on: https://www.deltares.nl/nl/d-hydro-suite-1d2d-beta/.","title":"D-HYDRO Suite 1D2D (Beta)"},{"location":"reference/glossary/#dimr","text":"Deltares Integrated Model Runner. Executable/library that runs integrated models by coupling multiple computational backends in a simulation timeloop. Uses a single DIMR config file as input.","title":"DIMR"},{"location":"reference/glossary/#dimr-config-file","text":"Input file for DIMR (typically dimr_config.xml ) for an integrated model run, describing which models are coupled and which quantities need to be exchanged.","title":"DIMR config file"},{"location":"reference/glossary/#e","text":"","title":"E"},{"location":"reference/glossary/#edge-mesh","text":"A geometrical \"line\" in a 1D, 2D or 3D mesh. Connects two mesh nodes as its end points. Building block of the UGRID-conventions .","title":"Edge (mesh)"},{"location":"reference/glossary/#external-forcings-file","text":"Input file for D-Flow FM describing model forcings such as boundary conditions , laterals and meteo . Format is INI-like. More details in the Delft3D FM User Manual .","title":"External forcings file"},{"location":"reference/glossary/#f","text":"","title":"F"},{"location":"reference/glossary/#face-mesh","text":"A geometrical \"cell\" in a 2D mesh. Formed by 3 or more mesh nodes as its vertices. Building block of the UGRID-conventions .","title":"Face (mesh)"},{"location":"reference/glossary/#flow-link","text":"An open connection/interface between two flow nodes in the staggered D-Flow FM model grid. Is the same as a \"velocity point\", and corresponds with (but is not equal to) an edge , both in 1D and in 2D. In 3D a flow link corresponds with a 3D face between two volumes .","title":"Flow link"},{"location":"reference/glossary/#flow-node","text":"A single finite volume \"cell\" in the staggered D-Flow FM model grid. Is the same as a \"pressure point\", and is in fact a face in 2D/3D or a node in 1D.","title":"Flow node"},{"location":"reference/glossary/#g","text":"","title":"G"},{"location":"reference/glossary/#grid","text":"The computational grid on which a flow simulation is done. The grid for D-Flow FM is defined in an input net file , and also appears (slightly differently) in the output map file .","title":"Grid"},{"location":"reference/glossary/#grid-snapping","text":"The snapping of D-Flow FM model input in x,y-coordinates to discrete locations in the staggered model grid . This process makes most model input independent of the chosen model grid and grid resolution. Snapping is done either to (sets of) flow nodes or (sequence of) flow links , depending on whether pressure-point data or velocity-point data is concerned.","title":"Grid snapping"},{"location":"reference/glossary/#h","text":"","title":"H"},{"location":"reference/glossary/#his-file","text":"Output file of D-Flow FM containing model results as time series on a specific set of discrete locations, which are typically the hydraulic structures, observation stations and more. More details in the Delft3D FM User Manual .","title":"His file"},{"location":"reference/glossary/#i","text":"","title":"I"},{"location":"reference/glossary/#integrated-model","text":"Model consisting of more than one model. Typically used when multiple computational backends are coupled, for example D-Flow FM and Rainfall Runoff or D-Flow FM and Real Time Control . Integrated models can be run using the Deltares Integrated Model Runner (DIMR) .","title":"Integrated model"},{"location":"reference/glossary/#ini-files","text":"Delft3D FM uses several input files that are formatted in an INI-like syntax. The abstract syntax depends on the particular file type, see: cross section files , initial field file , external forcings file , MDU file , observation files , rougness file , structure file .","title":"INI-files"},{"location":"reference/glossary/#initial-field-file","text":"Input file for D-Flow FM describing initial conditions and other spatially varying parameter fields. Format is INI-like. More details in the Delft3D FM User Manual .","title":"Initial field file"},{"location":"reference/glossary/#j","text":"","title":"J"},{"location":"reference/glossary/#k","text":"","title":"K"},{"location":"reference/glossary/#l","text":"","title":"L"},{"location":"reference/glossary/#lateral","text":"Lateral discharge in D-Flow FM , which acts as a source (or sink) of volume. Defined in the external forcings file . The actual forcing data may come from timeseries in a .bc file or from RR a coupled/integrated model. More details in the Delft3D FM User Manual .","title":"Lateral"},{"location":"reference/glossary/#m","text":"","title":"M"},{"location":"reference/glossary/#map-file","text":"Output file of D-Flow FM containing the model results on all grid points. More details in the Delft3D FM User Manual .","title":"Map file"},{"location":"reference/glossary/#mdu-file","text":"Main input file of D-Flow FM . Format is INI-like. More details in the Delft3D FM User Manual .","title":"MDU file"},{"location":"reference/glossary/#meteo","text":"Meteorological forcings of a model. Typically sources (or sinks) of volume via precipitation and evaporation, or forcing via wind. For D-Flow FM defined in the external forcings file . More details in the Delft3D FM User Manual .","title":"meteo"},{"location":"reference/glossary/#mesh","text":"See grid .","title":"mesh"},{"location":"reference/glossary/#n","text":"","title":"N"},{"location":"reference/glossary/#net-file","text":"Or grid file. Input file for D-Flow FM containing the computational model grid. Format is NetCDF, adhering to CF - and UGRID -conventions, and optionally also the Deltares-extension for 1D network topology and geometry.","title":"Net file"},{"location":"reference/glossary/#netcdf","text":"File format used by HYDROLIB-core and Delft3D Flexible Mesh for the model input grid and for model results in output files. These files typically adhere to the CF conventions and sometimes UGRID conventions .","title":"NetCDF"},{"location":"reference/glossary/#node-mesh","text":"A geometrical \"point\" in a 1D, 2D or 3D mesh. Defined by x- and y-coordinate, in 3D also a z-coordinate. Can be connected by mesh edges , and can form the vertices of a mesh face . Building block of the UGRID-conventions .","title":"Node (mesh)"},{"location":"reference/glossary/#o","text":"","title":"O"},{"location":"reference/glossary/#observation-files","text":"Files that define the model locations for which output should be produced in the his file . Two types: observation point file and observation cross section file .","title":"Observation files"},{"location":"reference/glossary/#observation-cross-section-file","text":"Input file for D-Flow FM that describes the model locations for which (cumulative) flow \"flux\" output should be produced in the his file . For example: cumulative discharge, salinity transport. Applies both to 1D, 2D, 1D2D and 3D models. Format is INI-like. More details in the Delft3D FM User Manual .","title":"Observation cross section file"},{"location":"reference/glossary/#observation-point-file","text":"Input file for D-Flow FM that describes the model point locations for which local output should be produced in the his file . For example: waterlevel, velocity vector/magnitude, tracer concentration as instantanous values. Applies both to 1D, 2D, 1D2D and 3D models. Format is INI-like. More details in the Delft3D FM User Manual .","title":"Observation point file"},{"location":"reference/glossary/#p","text":"","title":"P"},{"location":"reference/glossary/#polyline-file","text":"File containing a sequence of polylines in model coordinates. Each polyline has header lines with a label and row+column count, and at least a list of x, y-points. More than 2 columns may be present (z, data1, ...) for particular model inputs, see for example the fixed weir file . More details in the Delft3D FM User Manual .","title":"Polyline file"},{"location":"reference/glossary/#polygon-file","text":"See polyline file . The point sequences are interpreted as closed polygons.","title":"Polygon file"},{"location":"reference/glossary/#q","text":"","title":"Q"},{"location":"reference/glossary/#r","text":"","title":"R"},{"location":"reference/glossary/#rainfall-runoff","text":"RR for short. The computational backend that solves lumped rainfall runoff, offering various runoff concepts. Toplevel input is the sobek_3b.fnm file. Part of the D-Hydrology software module. More details on: https://www.deltares.nl/en/software/module/d-hydrology .","title":"Rainfall Runoff"},{"location":"reference/glossary/#real-time-control","text":"RTC for short. The computational backend for real-time control of hydraulic model components (typically hydraulic structures). Toplevel input is in various rtc*.xml files. Part of the D-Real Time Control software module. More details on: https://www.deltares.nl/en/software/module/d-real-time-control .","title":"Real Time Control"},{"location":"reference/glossary/#roughness-file","text":"Input file for D-Flow FM describing roughness values on the 1D network. Format is INI-like. More details in the Delft3D FM User Manual .","title":"Roughness file"},{"location":"reference/glossary/#s","text":"","title":"S"},{"location":"reference/glossary/#sample-file","text":"File containing an unstructured set of sample point values. Typically used as input file for initial fields or other spatially varying fields in the initial fields file . More details in the Delft3D FM User Manual .","title":"Sample file"},{"location":"reference/glossary/#staggered-grid","text":"Discretization method used in D-Flow FM where the PDE variables are not all defined on the same topological grid locations. Water level, concentrations and other volume-related variables are defined on the pressure points (also: flow nodes ), and the fluxes and other transport-related variables are defined on the velocity points (also: flow links ).","title":"Staggered grid"},{"location":"reference/glossary/#structure-file","text":"Input file for D-Flow FM containing the hydraulic structures. Format is INI-like. More details in the Delft3D FM User Manual .","title":"Structure file"},{"location":"reference/glossary/#t","text":"","title":"T"},{"location":"reference/glossary/#u","text":"","title":"U"},{"location":"reference/glossary/#ugrid-conventions","text":"Metadata conventions for storing unstructured grids in NetCDF files. More details on: http://ugrid-conventions.github.io/ugrid-conventions/ .","title":"UGRID conventions"},{"location":"reference/glossary/#v","text":"","title":"V"},{"location":"reference/glossary/#volume-mesh","text":"A geometrical \"cell\" in a 3D mesh. Formed by 4 or more mesh nodes as its vertices (or: 4 or more mesh faces as its \"sides\"). Building block of the UGRID-conventions .","title":"volume (mesh)"},{"location":"reference/glossary/#w","text":"","title":"W"},{"location":"reference/glossary/#x","text":"","title":"X"},{"location":"reference/glossary/#xyz-file","text":"See sample file .","title":"XYZ file"},{"location":"reference/glossary/#y","text":"","title":"Y"},{"location":"reference/glossary/#z","text":"","title":"Z"},{"location":"reference/gui/","text":"GUI files \u00b6 The GUI module provides the logic to create and validate GUI specific models for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. A .gui file is described by the classes below. GUI models \u00b6 namespace for storing the branches as branches.gui file Branch ( INIBasedModel ) pydantic-model \u00b6 A branch that is included in the branches.gui file. BranchGeneral ( INIGeneral ) pydantic-model \u00b6 The branches.gui file's [General] section with file meta data. BranchModel ( INIModel ) pydantic-model \u00b6 The overall branch model that contains the contents of one branches.gui file. This model is not referenced under a FMModel . Attributes: Name Type Description general BranchGeneral [General] block with file metadata. branch(List[Branch]) List of [Branch] blocks for all branches.","title":"GUI files"},{"location":"reference/gui/#gui-files","text":"The GUI module provides the logic to create and validate GUI specific models for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. A .gui file is described by the classes below.","title":"GUI files"},{"location":"reference/gui/#gui-models","text":"namespace for storing the branches as branches.gui file","title":"GUI models"},{"location":"reference/gui/#hydrolib.core.dflowfm.gui.models.Branch","text":"A branch that is included in the branches.gui file.","title":"Branch"},{"location":"reference/gui/#hydrolib.core.dflowfm.gui.models.BranchGeneral","text":"The branches.gui file's [General] section with file meta data.","title":"BranchGeneral"},{"location":"reference/gui/#hydrolib.core.dflowfm.gui.models.BranchModel","text":"The overall branch model that contains the contents of one branches.gui file. This model is not referenced under a FMModel . Attributes: Name Type Description general BranchGeneral [General] block with file metadata. branch(List[Branch]) List of [Branch] blocks for all branches.","title":"BranchModel"},{"location":"reference/ini/","text":"INI format \u00b6 The ini module provides the generic logic for parsing Deltares ini based files, such as the mdu, structures files, as well as more complex files such as the boundary condition (bc) files. Note that specific attribute files that employ this ini format often have their own dedicated module (and separate API doc page). These include: MDU file ( hydrolib.core.dflowfm.mdu ) External forcing file ( hydrolib.core.dflowfm.ext ) Initial fields and parameter file ( hydrolib.core.dflowfm.inifield ) Structure file ( hydrolib.core.dflowfm.structure ) 1D roughness ( hydrolib.core.dflowfm.friction ) Cross section files ( hydrolib.core.dflowfm.crosssection ) Storage node file ( hydrolib.core.dflowfm.storagenode ) Following below is the documentation for the INI format base classes. Model \u00b6 DataBlockINIBasedModel ( INIBasedModel ) pydantic-model \u00b6 DataBlockINIBasedModel defines the base model for ini models with datablocks. Attributes: Name Type Description datablock Datablock (class attribute) the actual data columns. INIBasedModel ( BaseModel , ABC ) pydantic-model \u00b6 INIBasedModel defines the base model for blocks/chapters inside an INIModel (*.ini file). INIBasedModel instances can be created from Section instances obtained through parsing ini documents. It further supports adding arbitrary fields to it, which will be written to file. Lastly, no arbitrary types are allowed for the defined fields. Attributes: Name Type Description comments Optional[Comments] Optional Comments if defined by the user, containing descriptions for all data fields. Comments ( BaseModel , ABC ) pydantic-model \u00b6 Comments defines the comments of an INIBasedModel get_list_delimiter () -> str classmethod \u00b6 List delimiter string that will be used for serializing list field values for any IniBasedModel, if that field has no custom list delimiter. This function should be overridden by any subclass for a particular filetype that needs a specific/different list separator. Source code in hydrolib/core/dflowfm/ini/models.py @classmethod def get_list_delimiter ( cls ) -> str : \"\"\"List delimiter string that will be used for serializing list field values for any IniBasedModel, **if** that field has no custom list delimiter. This function should be overridden by any subclass for a particular filetype that needs a specific/different list separator. \"\"\" return \" \" get_list_field_delimiter ( field_key : str ) -> str classmethod \u00b6 List delimiter string that will be used for serializing the given field's value. The returned delimiter is either the field's custom list delimiter if that was specified using Field(.., delimiter=\"..\"), or the default list delimiter for the model class that this field belongs to. Parameters: Name Type Description Default field_key str the original field key (not its alias). required Source code in hydrolib/core/dflowfm/ini/models.py @classmethod def get_list_field_delimiter ( cls , field_key : str ) -> str : \"\"\"List delimiter string that will be used for serializing the given field's value. The returned delimiter is either the field's custom list delimiter if that was specified using Field(.., delimiter=\"..\"), or the default list delimiter for the model class that this field belongs to. Args: field_key (str): the original field key (not its alias). \"\"\" delimiter = None if ( field := cls . __fields__ . get ( field_key )) and isinstance ( field , ModelField ): delimiter = field . field_info . extra . get ( \"delimiter\" ) if not delimiter : delimiter = cls . get_list_delimiter () return delimiter INIModel ( ParsableFileModel ) pydantic-model \u00b6 INI Model representation of a *.ini file. Typically subclasses will implement the various sorts of ini files, specifically for their fileType/contents. Child elements of this class associated with chapters/blocks in the ini file will be (sub)class of INIBasedModel. Parser \u00b6 Parser \u00b6 Parser defines a generic Parser for Deltares ini files. The Parser can be configured with a ParserConfig object. __init__ ( self , config : ParserConfig ) -> None special \u00b6 Creates a new Parser configured with the provided config Parameters: Name Type Description Default config ParserConfig The configuration of this Parser required Source code in hydrolib/core/dflowfm/ini/parser.py def __init__ ( self , config : ParserConfig ) -> None : \"\"\"Creates a new Parser configured with the provided config Args: config (ParserConfig): The configuration of this Parser \"\"\" self . _config = config self . _document = Document () self . _current_section : Optional [ _IntermediateSection ] = None self . _current_header_block : Optional [ _IntermediateCommentBlock ] = None self . _state = self . _StateType . NO_SECTION_FOUND self . _line_index = 0 # TODO add invalid blocks self . _feed_line : Dict [ Parser . _StateType , List [ Tuple [ Callable [[ str ], bool ], Callable [[ str ], None ]]] ] = { Parser . _StateType . NO_SECTION_FOUND : [ ( self . _is_comment , self . _handle_header_comment ), ( self . _is_section_header , self . _handle_next_section_header ), ], Parser . _StateType . PARSING_PROPERTIES : [ ( self . _is_comment , self . _handle_section_comment ), ( self . _is_section_header , self . _handle_next_section_header ), ( self . _is_property , self . _handle_property ), ( self . _is_datarow , self . _handle_new_datarow ), ], Parser . _StateType . PARSING_DATABLOCK : [ ( self . _is_section_header , self . _handle_next_section_header ), ( self . _is_datarow , self . _handle_datarow ), ], } self . _handle_emptyline : Dict [ Parser . _StateType , Callable [[], None ]] = { self . _StateType . NO_SECTION_FOUND : self . _finish_current_header_block , self . _StateType . PARSING_PROPERTIES : self . _noop , self . _StateType . PARSING_DATABLOCK : self . _noop , } feed_line ( self , line : str ) -> None \u00b6 Parse the next line with this Parser. Parameters: Name Type Description Default line str The line to parse required Source code in hydrolib/core/dflowfm/ini/parser.py def feed_line ( self , line : str ) -> None : \"\"\"Parse the next line with this Parser. Args: line (str): The line to parse \"\"\" if not self . _is_empty_line ( line ): for ( is_line_type , handle_line_type ) in self . _feed_line [ self . _state ]: if is_line_type ( line ): handle_line_type ( line ) break else : # handle exception pass else : self . _handle_emptyline [ self . _state ]() self . _increment_line () finalize ( self ) -> Document \u00b6 Finalize parsing and return the constructed Document. Returns: Type Description Document A Document describing the parsed ini file. Source code in hydrolib/core/dflowfm/ini/parser.py def finalize ( self ) -> Document : \"\"\"Finalize parsing and return the constructed Document. Returns: Document: A Document describing the parsed ini file. \"\"\" # TODO handle invalid block self . _finish_current_header_block () self . _finalise_current_section () return self . _document parse ( filepath : Path , config : ParserConfig = None ) -> Document classmethod \u00b6 Parses an INI file without a specific model type and returns it as a Document. Parameters: Name Type Description Default filepath Path File path to the INI-format file. required config ParserConfig Parser configuration to use. Defaults to None. None Returns: Type Description Document Representation of the parsed INI-file. Source code in hydrolib/core/dflowfm/ini/parser.py @classmethod def parse ( cls , filepath : Path , config : ParserConfig = None ) -> Document : \"\"\" Parses an INI file without a specific model type and returns it as a Document. Args: filepath (Path): File path to the INI-format file. config (ParserConfig, optional): Parser configuration to use. Defaults to None. Returns: Document: Representation of the parsed INI-file. \"\"\" if not config : config = ParserConfig () parser = cls ( config ) progline = re . compile ( r \"^([^#]*=\\s*)([^#]*)(#.*)?\" ) # matches whole line: \"Field = Value Maybe more # optional comment\" progfloat = re . compile ( r \"([\\d.]+)([dD])([+\\-]?\\d{1,3})\" ) # matches a float value: 1d9, 1D-3, 1.D+4, etc. with filepath . open ( encoding = \"utf8\" ) as f : for line in f : # Replace Fortran scientific notation for doubles # Match number d/D +/- number (e.g. 1d-05 or 1.23D+01 or 1.d-4) match = progline . match ( line ) if match : # Only process value line = ( match . group ( 1 ) + progfloat . sub ( r \"\\1e\\3\" , match . group ( 2 )) + str ( match . group ( 3 ) or \"\" ) ) else : # Process full line line = progfloat . sub ( r \"\\1e\\3\" , line ) parser . feed_line ( line ) return parser . finalize () parse_as_dict ( filepath : Path , config : ParserConfig = None ) -> dict classmethod \u00b6 Parses an INI file without a specific model type and returns it as a dictionary. Parameters: Name Type Description Default filepath Path File path to the INI-format file. required config ParserConfig Parser configuration to use. Defaults to None. None Returns: Type Description dict Representation of the parsed INI-file. Source code in hydrolib/core/dflowfm/ini/parser.py @classmethod def parse_as_dict ( cls , filepath : Path , config : ParserConfig = None ) -> dict : \"\"\" Parses an INI file without a specific model type and returns it as a dictionary. Args: filepath (Path): File path to the INI-format file. config (ParserConfig, optional): Parser configuration to use. Defaults to None. Returns: dict: Representation of the parsed INI-file. \"\"\" return cls . parse ( filepath , config ) . flatten () ParserConfig ( BaseModel ) pydantic-model \u00b6 ParserConfig defines the configuration options of the Parser Note that we cannot set both allow_only_keywords and parse_datablocks to True because we cannot distinguish between datablocks and key only properties. As such this will lead to a validation error. Attributes: Name Type Description allow_only_keywords bool Whether to allow properties with only keys (no '=' or value). Defaults to False. parse_datablocks bool Whether to allow parsing of datablocks at the bottom of sections. Defaults to False. parse_comments bool Whether we allow parsing of comments defined with the comment_delimeter. Defaults to True. comment_delimiter str The character or sequence of character used to define a comment. Defaults to '#'. Serializer \u00b6 DataBlockINIBasedSerializerConfig ( INISerializerConfig ) pydantic-model \u00b6 Class that holds the configuration settings for INI files with data blocks serialization. INISerializerConfig ( SerializerConfig ) pydantic-model \u00b6 SerializerConfig defines the configuration options of the Serializer Attributes: Name Type Description section_indent int The number of spaces with which whole sections should be indented. Defaults to 0. property_indent int The number of spaces with which properties should be indented relative to the section header (i.e. the full indent equals the section_indent plus property_indent). Defaults to 4. datablock_indent int The number of spaces with which datablock rows are indented relative to the section header (i.e. the full indent equals the section_indent plus datablock_indent). Defaults to 8. datablock_spacing int The number of spaces between datablock columns. Note that there might be additional offset to ensure . is lined out. Defaults to 2. comment_delimiter str The character used to delimit comments. Defaults to '#'. skip_empty_properties bool Whether or not to skip properties with a value that is empty or None. Defaults to True. total_datablock_indent : int property readonly \u00b6 The combined datablock indentation, i.e. section_indent + datablock_indent total_property_indent : int property readonly \u00b6 The combined property indentation, i.e. section_indent + property_indent MaxLengths ( BaseModel ) pydantic-model \u00b6 MaxLengths defines the maxmimum lengths of the parts of a section Attributes: Name Type Description key int The maximum length of all the keys of the properties within a section. If no properties are present it should be 0. value int The maximum length of all the non None values of the properties within a section. If no properties are present, or all values are None, it should be 0. datablock Optional[Sequence[int]] The maximum length of the values of each column of the Datablock. If no datablock is present it defaults to None. from_section ( section : Section ) -> MaxLengths classmethod \u00b6 Generate a MaxLengths instance from the given Section Parameters: Name Type Description Default section Section The section of which the MaxLengths are calculated required Returns: Type Description MaxLengths The MaxLengths corresponding with the provided section Source code in hydrolib/core/dflowfm/ini/serializer.py @classmethod def from_section ( cls , section : Section ) -> \"MaxLengths\" : \"\"\"Generate a MaxLengths instance from the given Section Args: section (Section): The section of which the MaxLengths are calculated Returns: MaxLengths: The MaxLengths corresponding with the provided section \"\"\" properties = list ( p for p in section . content if isinstance ( p , Property )) keys = ( prop . key for prop in properties ) values = ( prop . value for prop in properties if prop . value is not None ) max_key_length = max (( len ( k ) for k in keys ), default = 0 ) max_value_length = max (( len ( v ) for v in values ), default = 0 ) max_datablock_lengths = MaxLengths . _of_datablock ( section . datablock ) return cls ( key = max_key_length , value = max_value_length , datablock = max_datablock_lengths , ) SectionSerializer \u00b6 SectionSerializer provides the serialize method to serialize a Section The entrypoint of this method is the serialize method, which will construct an actual instance and serializes the Section with it. __init__ ( self , config : INISerializerConfig , max_length : MaxLengths ) special \u00b6 Create a new SectionSerializer Parameters: Name Type Description Default config SerializerConfig The config describing the serialization options required max_length MaxLengths The max lengths of the section being serialized required Source code in hydrolib/core/dflowfm/ini/serializer.py def __init__ ( self , config : INISerializerConfig , max_length : MaxLengths ): \"\"\"Create a new SectionSerializer Args: config (SerializerConfig): The config describing the serialization options max_length (MaxLengths): The max lengths of the section being serialized \"\"\" self . _config = config self . _max_length = max_length config : INISerializerConfig property readonly \u00b6 The SerializerConfig used while serializing the section. max_length : MaxLengths property readonly \u00b6 The MaxLengths of the Section being serialized by this SectionSerializer. serialize ( section : Section , config : INISerializerConfig ) -> Iterable [ str ] classmethod \u00b6 Serialize the provided section with the given config Parameters: Name Type Description Default section Section The section to serialize required config SerializerConfig The config describing the serialization options required Returns: Type Description Lines The iterable lines of the serialized section Source code in hydrolib/core/dflowfm/ini/serializer.py @classmethod def serialize ( cls , section : Section , config : INISerializerConfig ) -> Lines : \"\"\"Serialize the provided section with the given config Args: section (Section): The section to serialize config (SerializerConfig): The config describing the serialization options Returns: Lines: The iterable lines of the serialized section \"\"\" serializer = cls ( config , MaxLengths . from_section ( section )) return serializer . _serialize_section ( section ) Serializer \u00b6 Serializer serializes Document to its corresponding lines. __init__ ( self , config : INISerializerConfig ) special \u00b6 Creates a new Serializer with the provided configuration. Parameters: Name Type Description Default config SerializerConfig The configuration of this Serializer. required Source code in hydrolib/core/dflowfm/ini/serializer.py def __init__ ( self , config : INISerializerConfig ): \"\"\"Creates a new Serializer with the provided configuration. Args: config (SerializerConfig): The configuration of this Serializer. \"\"\" self . _config = config serialize ( self , document : Document ) -> Iterable [ str ] \u00b6 Serialize the provided document into an iterable of lines. Parameters: Name Type Description Default document Document The Document to serialize. required Returns: Type Description Lines An iterable returning each line of the serialized Document. Source code in hydrolib/core/dflowfm/ini/serializer.py def serialize ( self , document : Document ) -> Lines : \"\"\"Serialize the provided document into an iterable of lines. Args: document (Document): The Document to serialize. Returns: Lines: An iterable returning each line of the serialized Document. \"\"\" header_iterable = self . _serialize_document_header ( document . header_comment ) serialize_section = lambda s : SectionSerializer . serialize ( s , self . _config ) sections = ( serialize_section ( section ) for section in document . sections ) sections_with_spacing = Serializer . _interweave ( sections , [ \"\" ]) sections_iterable = chain . from_iterable ( sections_with_spacing ) return chain ( header_iterable , sections_iterable ) write_ini ( path : Path , document : Document , config : INISerializerConfig ) -> None \u00b6 Write the provided document to the specified path If the provided path already exists, it will be overwritten. If the parent folder do not exist, they will be created. Parameters: Name Type Description Default path Path The path to which the document should be written. required document Document The document to serialize to the specified path. required config INISerializerConfig The configuration settings for the serializer. required Source code in hydrolib/core/dflowfm/ini/serializer.py def write_ini ( path : Path , document : Document , config : INISerializerConfig ) -> None : \"\"\"Write the provided document to the specified path If the provided path already exists, it will be overwritten. If the parent folder do not exist, they will be created. Args: path (Path): The path to which the document should be written. document (Document): The document to serialize to the specified path. config (INISerializerConfig): The configuration settings for the serializer. \"\"\" serializer = Serializer ( config ) path . parent . mkdir ( parents = True , exist_ok = True ) with path . open ( \"w\" , encoding = \"utf8\" ) as f : for line in serializer . serialize ( document ): f . write ( line + \" \\n \" )","title":"INI format"},{"location":"reference/ini/#ini-format","text":"The ini module provides the generic logic for parsing Deltares ini based files, such as the mdu, structures files, as well as more complex files such as the boundary condition (bc) files. Note that specific attribute files that employ this ini format often have their own dedicated module (and separate API doc page). These include: MDU file ( hydrolib.core.dflowfm.mdu ) External forcing file ( hydrolib.core.dflowfm.ext ) Initial fields and parameter file ( hydrolib.core.dflowfm.inifield ) Structure file ( hydrolib.core.dflowfm.structure ) 1D roughness ( hydrolib.core.dflowfm.friction ) Cross section files ( hydrolib.core.dflowfm.crosssection ) Storage node file ( hydrolib.core.dflowfm.storagenode ) Following below is the documentation for the INI format base classes.","title":"INI format"},{"location":"reference/ini/#model","text":"","title":"Model"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.models.DataBlockINIBasedModel","text":"DataBlockINIBasedModel defines the base model for ini models with datablocks. Attributes: Name Type Description datablock Datablock (class attribute) the actual data columns.","title":"DataBlockINIBasedModel"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.models.INIBasedModel","text":"INIBasedModel defines the base model for blocks/chapters inside an INIModel (*.ini file). INIBasedModel instances can be created from Section instances obtained through parsing ini documents. It further supports adding arbitrary fields to it, which will be written to file. Lastly, no arbitrary types are allowed for the defined fields. Attributes: Name Type Description comments Optional[Comments] Optional Comments if defined by the user, containing descriptions for all data fields.","title":"INIBasedModel"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.models.INIBasedModel.Comments","text":"Comments defines the comments of an INIBasedModel","title":"Comments"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.models.INIBasedModel.get_list_delimiter","text":"List delimiter string that will be used for serializing list field values for any IniBasedModel, if that field has no custom list delimiter. This function should be overridden by any subclass for a particular filetype that needs a specific/different list separator. Source code in hydrolib/core/dflowfm/ini/models.py @classmethod def get_list_delimiter ( cls ) -> str : \"\"\"List delimiter string that will be used for serializing list field values for any IniBasedModel, **if** that field has no custom list delimiter. This function should be overridden by any subclass for a particular filetype that needs a specific/different list separator. \"\"\" return \" \"","title":"get_list_delimiter()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.models.INIBasedModel.get_list_field_delimiter","text":"List delimiter string that will be used for serializing the given field's value. The returned delimiter is either the field's custom list delimiter if that was specified using Field(.., delimiter=\"..\"), or the default list delimiter for the model class that this field belongs to. Parameters: Name Type Description Default field_key str the original field key (not its alias). required Source code in hydrolib/core/dflowfm/ini/models.py @classmethod def get_list_field_delimiter ( cls , field_key : str ) -> str : \"\"\"List delimiter string that will be used for serializing the given field's value. The returned delimiter is either the field's custom list delimiter if that was specified using Field(.., delimiter=\"..\"), or the default list delimiter for the model class that this field belongs to. Args: field_key (str): the original field key (not its alias). \"\"\" delimiter = None if ( field := cls . __fields__ . get ( field_key )) and isinstance ( field , ModelField ): delimiter = field . field_info . extra . get ( \"delimiter\" ) if not delimiter : delimiter = cls . get_list_delimiter () return delimiter","title":"get_list_field_delimiter()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.models.INIModel","text":"INI Model representation of a *.ini file. Typically subclasses will implement the various sorts of ini files, specifically for their fileType/contents. Child elements of this class associated with chapters/blocks in the ini file will be (sub)class of INIBasedModel.","title":"INIModel"},{"location":"reference/ini/#parser","text":"","title":"Parser"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.parser.Parser","text":"Parser defines a generic Parser for Deltares ini files. The Parser can be configured with a ParserConfig object.","title":"Parser"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.parser.Parser.__init__","text":"Creates a new Parser configured with the provided config Parameters: Name Type Description Default config ParserConfig The configuration of this Parser required Source code in hydrolib/core/dflowfm/ini/parser.py def __init__ ( self , config : ParserConfig ) -> None : \"\"\"Creates a new Parser configured with the provided config Args: config (ParserConfig): The configuration of this Parser \"\"\" self . _config = config self . _document = Document () self . _current_section : Optional [ _IntermediateSection ] = None self . _current_header_block : Optional [ _IntermediateCommentBlock ] = None self . _state = self . _StateType . NO_SECTION_FOUND self . _line_index = 0 # TODO add invalid blocks self . _feed_line : Dict [ Parser . _StateType , List [ Tuple [ Callable [[ str ], bool ], Callable [[ str ], None ]]] ] = { Parser . _StateType . NO_SECTION_FOUND : [ ( self . _is_comment , self . _handle_header_comment ), ( self . _is_section_header , self . _handle_next_section_header ), ], Parser . _StateType . PARSING_PROPERTIES : [ ( self . _is_comment , self . _handle_section_comment ), ( self . _is_section_header , self . _handle_next_section_header ), ( self . _is_property , self . _handle_property ), ( self . _is_datarow , self . _handle_new_datarow ), ], Parser . _StateType . PARSING_DATABLOCK : [ ( self . _is_section_header , self . _handle_next_section_header ), ( self . _is_datarow , self . _handle_datarow ), ], } self . _handle_emptyline : Dict [ Parser . _StateType , Callable [[], None ]] = { self . _StateType . NO_SECTION_FOUND : self . _finish_current_header_block , self . _StateType . PARSING_PROPERTIES : self . _noop , self . _StateType . PARSING_DATABLOCK : self . _noop , }","title":"__init__()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.parser.Parser.feed_line","text":"Parse the next line with this Parser. Parameters: Name Type Description Default line str The line to parse required Source code in hydrolib/core/dflowfm/ini/parser.py def feed_line ( self , line : str ) -> None : \"\"\"Parse the next line with this Parser. Args: line (str): The line to parse \"\"\" if not self . _is_empty_line ( line ): for ( is_line_type , handle_line_type ) in self . _feed_line [ self . _state ]: if is_line_type ( line ): handle_line_type ( line ) break else : # handle exception pass else : self . _handle_emptyline [ self . _state ]() self . _increment_line ()","title":"feed_line()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.parser.Parser.finalize","text":"Finalize parsing and return the constructed Document. Returns: Type Description Document A Document describing the parsed ini file. Source code in hydrolib/core/dflowfm/ini/parser.py def finalize ( self ) -> Document : \"\"\"Finalize parsing and return the constructed Document. Returns: Document: A Document describing the parsed ini file. \"\"\" # TODO handle invalid block self . _finish_current_header_block () self . _finalise_current_section () return self . _document","title":"finalize()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.parser.Parser.parse","text":"Parses an INI file without a specific model type and returns it as a Document. Parameters: Name Type Description Default filepath Path File path to the INI-format file. required config ParserConfig Parser configuration to use. Defaults to None. None Returns: Type Description Document Representation of the parsed INI-file. Source code in hydrolib/core/dflowfm/ini/parser.py @classmethod def parse ( cls , filepath : Path , config : ParserConfig = None ) -> Document : \"\"\" Parses an INI file without a specific model type and returns it as a Document. Args: filepath (Path): File path to the INI-format file. config (ParserConfig, optional): Parser configuration to use. Defaults to None. Returns: Document: Representation of the parsed INI-file. \"\"\" if not config : config = ParserConfig () parser = cls ( config ) progline = re . compile ( r \"^([^#]*=\\s*)([^#]*)(#.*)?\" ) # matches whole line: \"Field = Value Maybe more # optional comment\" progfloat = re . compile ( r \"([\\d.]+)([dD])([+\\-]?\\d{1,3})\" ) # matches a float value: 1d9, 1D-3, 1.D+4, etc. with filepath . open ( encoding = \"utf8\" ) as f : for line in f : # Replace Fortran scientific notation for doubles # Match number d/D +/- number (e.g. 1d-05 or 1.23D+01 or 1.d-4) match = progline . match ( line ) if match : # Only process value line = ( match . group ( 1 ) + progfloat . sub ( r \"\\1e\\3\" , match . group ( 2 )) + str ( match . group ( 3 ) or \"\" ) ) else : # Process full line line = progfloat . sub ( r \"\\1e\\3\" , line ) parser . feed_line ( line ) return parser . finalize ()","title":"parse()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.parser.Parser.parse_as_dict","text":"Parses an INI file without a specific model type and returns it as a dictionary. Parameters: Name Type Description Default filepath Path File path to the INI-format file. required config ParserConfig Parser configuration to use. Defaults to None. None Returns: Type Description dict Representation of the parsed INI-file. Source code in hydrolib/core/dflowfm/ini/parser.py @classmethod def parse_as_dict ( cls , filepath : Path , config : ParserConfig = None ) -> dict : \"\"\" Parses an INI file without a specific model type and returns it as a dictionary. Args: filepath (Path): File path to the INI-format file. config (ParserConfig, optional): Parser configuration to use. Defaults to None. Returns: dict: Representation of the parsed INI-file. \"\"\" return cls . parse ( filepath , config ) . flatten ()","title":"parse_as_dict()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.parser.ParserConfig","text":"ParserConfig defines the configuration options of the Parser Note that we cannot set both allow_only_keywords and parse_datablocks to True because we cannot distinguish between datablocks and key only properties. As such this will lead to a validation error. Attributes: Name Type Description allow_only_keywords bool Whether to allow properties with only keys (no '=' or value). Defaults to False. parse_datablocks bool Whether to allow parsing of datablocks at the bottom of sections. Defaults to False. parse_comments bool Whether we allow parsing of comments defined with the comment_delimeter. Defaults to True. comment_delimiter str The character or sequence of character used to define a comment. Defaults to '#'.","title":"ParserConfig"},{"location":"reference/ini/#serializer","text":"","title":"Serializer"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.DataBlockINIBasedSerializerConfig","text":"Class that holds the configuration settings for INI files with data blocks serialization.","title":"DataBlockINIBasedSerializerConfig"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.INISerializerConfig","text":"SerializerConfig defines the configuration options of the Serializer Attributes: Name Type Description section_indent int The number of spaces with which whole sections should be indented. Defaults to 0. property_indent int The number of spaces with which properties should be indented relative to the section header (i.e. the full indent equals the section_indent plus property_indent). Defaults to 4. datablock_indent int The number of spaces with which datablock rows are indented relative to the section header (i.e. the full indent equals the section_indent plus datablock_indent). Defaults to 8. datablock_spacing int The number of spaces between datablock columns. Note that there might be additional offset to ensure . is lined out. Defaults to 2. comment_delimiter str The character used to delimit comments. Defaults to '#'. skip_empty_properties bool Whether or not to skip properties with a value that is empty or None. Defaults to True.","title":"INISerializerConfig"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.INISerializerConfig.total_datablock_indent","text":"The combined datablock indentation, i.e. section_indent + datablock_indent","title":"total_datablock_indent"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.INISerializerConfig.total_property_indent","text":"The combined property indentation, i.e. section_indent + property_indent","title":"total_property_indent"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.MaxLengths","text":"MaxLengths defines the maxmimum lengths of the parts of a section Attributes: Name Type Description key int The maximum length of all the keys of the properties within a section. If no properties are present it should be 0. value int The maximum length of all the non None values of the properties within a section. If no properties are present, or all values are None, it should be 0. datablock Optional[Sequence[int]] The maximum length of the values of each column of the Datablock. If no datablock is present it defaults to None.","title":"MaxLengths"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.MaxLengths.from_section","text":"Generate a MaxLengths instance from the given Section Parameters: Name Type Description Default section Section The section of which the MaxLengths are calculated required Returns: Type Description MaxLengths The MaxLengths corresponding with the provided section Source code in hydrolib/core/dflowfm/ini/serializer.py @classmethod def from_section ( cls , section : Section ) -> \"MaxLengths\" : \"\"\"Generate a MaxLengths instance from the given Section Args: section (Section): The section of which the MaxLengths are calculated Returns: MaxLengths: The MaxLengths corresponding with the provided section \"\"\" properties = list ( p for p in section . content if isinstance ( p , Property )) keys = ( prop . key for prop in properties ) values = ( prop . value for prop in properties if prop . value is not None ) max_key_length = max (( len ( k ) for k in keys ), default = 0 ) max_value_length = max (( len ( v ) for v in values ), default = 0 ) max_datablock_lengths = MaxLengths . _of_datablock ( section . datablock ) return cls ( key = max_key_length , value = max_value_length , datablock = max_datablock_lengths , )","title":"from_section()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.SectionSerializer","text":"SectionSerializer provides the serialize method to serialize a Section The entrypoint of this method is the serialize method, which will construct an actual instance and serializes the Section with it.","title":"SectionSerializer"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.SectionSerializer.__init__","text":"Create a new SectionSerializer Parameters: Name Type Description Default config SerializerConfig The config describing the serialization options required max_length MaxLengths The max lengths of the section being serialized required Source code in hydrolib/core/dflowfm/ini/serializer.py def __init__ ( self , config : INISerializerConfig , max_length : MaxLengths ): \"\"\"Create a new SectionSerializer Args: config (SerializerConfig): The config describing the serialization options max_length (MaxLengths): The max lengths of the section being serialized \"\"\" self . _config = config self . _max_length = max_length","title":"__init__()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.SectionSerializer.config","text":"The SerializerConfig used while serializing the section.","title":"config"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.SectionSerializer.max_length","text":"The MaxLengths of the Section being serialized by this SectionSerializer.","title":"max_length"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.SectionSerializer.serialize","text":"Serialize the provided section with the given config Parameters: Name Type Description Default section Section The section to serialize required config SerializerConfig The config describing the serialization options required Returns: Type Description Lines The iterable lines of the serialized section Source code in hydrolib/core/dflowfm/ini/serializer.py @classmethod def serialize ( cls , section : Section , config : INISerializerConfig ) -> Lines : \"\"\"Serialize the provided section with the given config Args: section (Section): The section to serialize config (SerializerConfig): The config describing the serialization options Returns: Lines: The iterable lines of the serialized section \"\"\" serializer = cls ( config , MaxLengths . from_section ( section )) return serializer . _serialize_section ( section )","title":"serialize()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.Serializer","text":"Serializer serializes Document to its corresponding lines.","title":"Serializer"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.Serializer.__init__","text":"Creates a new Serializer with the provided configuration. Parameters: Name Type Description Default config SerializerConfig The configuration of this Serializer. required Source code in hydrolib/core/dflowfm/ini/serializer.py def __init__ ( self , config : INISerializerConfig ): \"\"\"Creates a new Serializer with the provided configuration. Args: config (SerializerConfig): The configuration of this Serializer. \"\"\" self . _config = config","title":"__init__()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.Serializer.serialize","text":"Serialize the provided document into an iterable of lines. Parameters: Name Type Description Default document Document The Document to serialize. required Returns: Type Description Lines An iterable returning each line of the serialized Document. Source code in hydrolib/core/dflowfm/ini/serializer.py def serialize ( self , document : Document ) -> Lines : \"\"\"Serialize the provided document into an iterable of lines. Args: document (Document): The Document to serialize. Returns: Lines: An iterable returning each line of the serialized Document. \"\"\" header_iterable = self . _serialize_document_header ( document . header_comment ) serialize_section = lambda s : SectionSerializer . serialize ( s , self . _config ) sections = ( serialize_section ( section ) for section in document . sections ) sections_with_spacing = Serializer . _interweave ( sections , [ \"\" ]) sections_iterable = chain . from_iterable ( sections_with_spacing ) return chain ( header_iterable , sections_iterable )","title":"serialize()"},{"location":"reference/ini/#hydrolib.core.dflowfm.ini.serializer.write_ini","text":"Write the provided document to the specified path If the provided path already exists, it will be overwritten. If the parent folder do not exist, they will be created. Parameters: Name Type Description Default path Path The path to which the document should be written. required document Document The document to serialize to the specified path. required config INISerializerConfig The configuration settings for the serializer. required Source code in hydrolib/core/dflowfm/ini/serializer.py def write_ini ( path : Path , document : Document , config : INISerializerConfig ) -> None : \"\"\"Write the provided document to the specified path If the provided path already exists, it will be overwritten. If the parent folder do not exist, they will be created. Args: path (Path): The path to which the document should be written. document (Document): The document to serialize to the specified path. config (INISerializerConfig): The configuration settings for the serializer. \"\"\" serializer = Serializer ( config ) path . parent . mkdir ( parents = True , exist_ok = True ) with path . open ( \"w\" , encoding = \"utf8\" ) as f : for line in serializer . serialize ( document ): f . write ( line + \" \\n \" )","title":"write_ini()"},{"location":"reference/inifield/","text":"Initial and parameter field files \u00b6 The inifield file contains the initial conditions and spatial parameter input fields for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. The inifield file is represented by the classes below. Model \u00b6 AbstractSpatialField ( INIBasedModel , ABC ) pydantic-model \u00b6 Abstract base class for [Initial] and [Parameter] block data in inifield files. Defines all common fields. Used via subclasses InitialField and ParameterField. validate_that_value_is_present_for_polygons ( values : Dict ) -> Dict classmethod \u00b6 Validates that the value is provided when dealing with polygons. Source code in hydrolib/core/dflowfm/inifield/models.py @root_validator ( allow_reuse = True ) def validate_that_value_is_present_for_polygons ( cls , values : Dict ) -> Dict : \"\"\"Validates that the value is provided when dealing with polygons.\"\"\" return validate_required_fields ( values , \"value\" , conditional_field_name = \"datafiletype\" , conditional_value = DataFileType . polygon , ) AveragingType ( str , Enum ) \u00b6 Enum class containing the valid values for the averagingType attribute in several subclasses of AbstractIniField. DataFileType ( str , Enum ) \u00b6 Enum class containing the valid values for the dataFileType attribute in several subclasses of AbstractIniField. IniFieldGeneral ( INIGeneral ) pydantic-model \u00b6 The initial field file's [General] section with file meta data. IniFieldModel ( INIModel ) pydantic-model \u00b6 The overall inifield model that contains the contents of one initial field and parameter file. This model is typically referenced under a FMModel .geometry.inifieldfile[..] . Attributes: Name Type Description general IniFieldGeneral [General] block with file metadata. initial List[InitialField] List of [Initial] blocks with initial condition definitions. parameter List[ParameterField] List of [Parameter] blocks with spatial parameter definitions. InitialField ( AbstractSpatialField ) pydantic-model \u00b6 Initial condition field definition, represents an [Initial] block in an inifield file. Typically inside the definition list of a FMModel .geometry.inifieldfile.initial[..] InterpolationMethod ( str , Enum ) \u00b6 Enum class containing the valid values for the interpolationMethod attribute in several subclasses of AbstractIniField. ParameterField ( AbstractSpatialField ) pydantic-model \u00b6 Parameter field definition, represents a [Parameter] block in an inifield file. Typically inside the definition list of a FMModel .geometry.inifieldfile.parameter[..]","title":"Initial and parameter field files"},{"location":"reference/inifield/#initial-and-parameter-field-files","text":"The inifield file contains the initial conditions and spatial parameter input fields for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. The inifield file is represented by the classes below.","title":"Initial and parameter field files"},{"location":"reference/inifield/#model","text":"","title":"Model"},{"location":"reference/inifield/#hydrolib.core.dflowfm.inifield.models.AbstractSpatialField","text":"Abstract base class for [Initial] and [Parameter] block data in inifield files. Defines all common fields. Used via subclasses InitialField and ParameterField.","title":"AbstractSpatialField"},{"location":"reference/inifield/#hydrolib.core.dflowfm.inifield.models.AbstractSpatialField.validate_that_value_is_present_for_polygons","text":"Validates that the value is provided when dealing with polygons. Source code in hydrolib/core/dflowfm/inifield/models.py @root_validator ( allow_reuse = True ) def validate_that_value_is_present_for_polygons ( cls , values : Dict ) -> Dict : \"\"\"Validates that the value is provided when dealing with polygons.\"\"\" return validate_required_fields ( values , \"value\" , conditional_field_name = \"datafiletype\" , conditional_value = DataFileType . polygon , )","title":"validate_that_value_is_present_for_polygons()"},{"location":"reference/inifield/#hydrolib.core.dflowfm.inifield.models.AveragingType","text":"Enum class containing the valid values for the averagingType attribute in several subclasses of AbstractIniField.","title":"AveragingType"},{"location":"reference/inifield/#hydrolib.core.dflowfm.inifield.models.DataFileType","text":"Enum class containing the valid values for the dataFileType attribute in several subclasses of AbstractIniField.","title":"DataFileType"},{"location":"reference/inifield/#hydrolib.core.dflowfm.inifield.models.IniFieldGeneral","text":"The initial field file's [General] section with file meta data.","title":"IniFieldGeneral"},{"location":"reference/inifield/#hydrolib.core.dflowfm.inifield.models.IniFieldModel","text":"The overall inifield model that contains the contents of one initial field and parameter file. This model is typically referenced under a FMModel .geometry.inifieldfile[..] . Attributes: Name Type Description general IniFieldGeneral [General] block with file metadata. initial List[InitialField] List of [Initial] blocks with initial condition definitions. parameter List[ParameterField] List of [Parameter] blocks with spatial parameter definitions.","title":"IniFieldModel"},{"location":"reference/inifield/#hydrolib.core.dflowfm.inifield.models.InitialField","text":"Initial condition field definition, represents an [Initial] block in an inifield file. Typically inside the definition list of a FMModel .geometry.inifieldfile.initial[..]","title":"InitialField"},{"location":"reference/inifield/#hydrolib.core.dflowfm.inifield.models.InterpolationMethod","text":"Enum class containing the valid values for the interpolationMethod attribute in several subclasses of AbstractIniField.","title":"InterpolationMethod"},{"location":"reference/inifield/#hydrolib.core.dflowfm.inifield.models.ParameterField","text":"Parameter field definition, represents a [Parameter] block in an inifield file. Typically inside the definition list of a FMModel .geometry.inifieldfile.parameter[..]","title":"ParameterField"},{"location":"reference/mdu/","text":"MDU file \u00b6 The MDU file is the main input file for D-Flow FM . It is represented by the classes below. Model \u00b6 AutoStartOption ( IntEnum ) \u00b6 Enum class containing the valid values for the AutoStart attribute in the General class. Calibration ( INIBasedModel ) pydantic-model \u00b6 The [Calibration] section in an MDU file. This model is typically referenced under FMModel .calibration . All lowercased attributes match with the [Calibration] input as described in UM Sec.A.3 . ExternalForcing ( INIBasedModel ) pydantic-model \u00b6 The [External Forcing] section in an MDU file. This model is typically referenced under FMModel .external_forcing . All lowercased attributes match with the [External Forcing] input as described in UM Sec.A.1 . is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/mdu/models.py def is_intermediate_link ( self ) -> bool : return True FMModel ( INIModel ) pydantic-model \u00b6 The overall FM model that contains the contents of the toplevel MDU file. All lowercased attributes match with the supported \"[section]\"s as described in UM Sec.A . Each of these class attributes refers to an underlying model class for that particular section. General ( INIGeneral ) pydantic-model \u00b6 The MDU file's [General] section with file meta data. Geometry ( INIBasedModel ) pydantic-model \u00b6 The [Geometry] section in an MDU file. This model is typically referenced under FMModel .geometry . All lowercased attributes match with the [Geometry] input as described in UM Sec.A.1 . is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/mdu/models.py def is_intermediate_link ( self ) -> bool : return True GroundWater ( INIBasedModel ) pydantic-model \u00b6 The [Grw] section in an MDU file. This model is typically referenced under FMModel .grw . All lowercased attributes match with the [Grw] input as described in UM Sec.A.3 . Hydrology ( INIBasedModel ) pydantic-model \u00b6 The [Hydrology] section in an MDU file. This model is typically referenced under FMModel .hydrology . All lowercased attributes match with the [Hydrology] input as described in UM Sec.A.1 . InfiltrationMethod ( IntEnum ) \u00b6 Enum class containing the valid values for the Infiltrationmodel attribute in the GroundWater class. Numerics ( INIBasedModel ) pydantic-model \u00b6 The [Numerics] section in an MDU file. This model is typically referenced under FMModel .numerics . All lowercased attributes match with the [Numerics] input as described in UM Sec.A.1 . Output ( INIBasedModel ) pydantic-model \u00b6 The [Output] section in an MDU file. This model is typically referenced under FMModel .output . All lowercased attributes match with the [Output] input as described in UM Sec.A.1 . is_intermediate_link ( self ) -> bool \u00b6 Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/mdu/models.py def is_intermediate_link ( self ) -> bool : return True Particles ( INIBasedModel ) pydantic-model \u00b6 The [Particles] section in an MDU file. This model is typically referenced under FMModel .particles . All lowercased attributes match with the [Particles] input as described in UM Sec.A.3 . ParticlesThreeDType ( IntEnum ) \u00b6 Enum class containing the valid values for the 3Dtype attribute in the Particles class. Physics ( INIBasedModel ) pydantic-model \u00b6 The [Physics] section in an MDU file. This model is typically referenced under FMModel .physics . All lowercased attributes match with the [Physics] input as described in UM Sec.A.1 . ProcessFluxIntegration ( IntEnum ) \u00b6 Enum class containing the valid values for the ProcessFluxIntegration attribute in the Processes class. Processes ( INIBasedModel ) pydantic-model \u00b6 The [Processes] section in an MDU file. This model is typically referenced under FMModel .processes . All lowercased attributes match with the [Processes] input as described in UM Sec.A.3 . Restart ( INIBasedModel ) pydantic-model \u00b6 The [Restart] section in an MDU file. This model is typically referenced under FMModel .restart . All lowercased attributes match with the [Restart] input as described in UM Sec.A.1 . Time ( INIBasedModel ) pydantic-model \u00b6 The [Time] section in an MDU file. This model is typically referenced under FMModel .time . All lowercased attributes match with the [Time] input as described in UM Sec.A.1 . Trachytopes ( INIBasedModel ) pydantic-model \u00b6 The [Trachytopes] section in an MDU file. This model is typically referenced under FMModel .trachytopes . All lowercased attributes match with the [Trachytopes] input as described in UM Sec.A.1 . Vegetation ( INIBasedModel ) pydantic-model \u00b6 The [Veg] section in an MDU file. This model is typically referenced under FMModel .veg . All lowercased attributes match with the [Veg] input as described in UM Sec.A.3 . VegetationModelNr ( IntEnum ) \u00b6 Enum class containing the valid values for the VegetationModelNr attribute in the Vegetation class. VolumeTables ( INIBasedModel ) pydantic-model \u00b6 The [VolumeTables] section in an MDU file. This model is typically referenced under FMModel .volumetables . All lowercased attributes match with the [VolumeTables] input as described in UM Sec.A.1 . Waves ( INIBasedModel ) pydantic-model \u00b6 The [Waves] section in an MDU file. This model is typically referenced under FMModel .waves . All lowercased attributes match with the [Waves] input as described in UM Sec.A.1 . Wind ( INIBasedModel ) pydantic-model \u00b6 The [Wind] section in an MDU file. This model is typically referenced under FMModel .wind . All lowercased attributes match with the [Wind] input as described in UM Sec.A.1 .","title":"MDU file"},{"location":"reference/mdu/#mdu-file","text":"The MDU file is the main input file for D-Flow FM . It is represented by the classes below.","title":"MDU file"},{"location":"reference/mdu/#model","text":"","title":"Model"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.AutoStartOption","text":"Enum class containing the valid values for the AutoStart attribute in the General class.","title":"AutoStartOption"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Calibration","text":"The [Calibration] section in an MDU file. This model is typically referenced under FMModel .calibration . All lowercased attributes match with the [Calibration] input as described in UM Sec.A.3 .","title":"Calibration"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.ExternalForcing","text":"The [External Forcing] section in an MDU file. This model is typically referenced under FMModel .external_forcing . All lowercased attributes match with the [External Forcing] input as described in UM Sec.A.1 .","title":"ExternalForcing"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.ExternalForcing.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/mdu/models.py def is_intermediate_link ( self ) -> bool : return True","title":"is_intermediate_link()"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.FMModel","text":"The overall FM model that contains the contents of the toplevel MDU file. All lowercased attributes match with the supported \"[section]\"s as described in UM Sec.A . Each of these class attributes refers to an underlying model class for that particular section.","title":"FMModel"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.General","text":"The MDU file's [General] section with file meta data.","title":"General"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Geometry","text":"The [Geometry] section in an MDU file. This model is typically referenced under FMModel .geometry . All lowercased attributes match with the [Geometry] input as described in UM Sec.A.1 .","title":"Geometry"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Geometry.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/mdu/models.py def is_intermediate_link ( self ) -> bool : return True","title":"is_intermediate_link()"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.GroundWater","text":"The [Grw] section in an MDU file. This model is typically referenced under FMModel .grw . All lowercased attributes match with the [Grw] input as described in UM Sec.A.3 .","title":"GroundWater"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Hydrology","text":"The [Hydrology] section in an MDU file. This model is typically referenced under FMModel .hydrology . All lowercased attributes match with the [Hydrology] input as described in UM Sec.A.1 .","title":"Hydrology"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.InfiltrationMethod","text":"Enum class containing the valid values for the Infiltrationmodel attribute in the GroundWater class.","title":"InfiltrationMethod"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Numerics","text":"The [Numerics] section in an MDU file. This model is typically referenced under FMModel .numerics . All lowercased attributes match with the [Numerics] input as described in UM Sec.A.1 .","title":"Numerics"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Output","text":"The [Output] section in an MDU file. This model is typically referenced under FMModel .output . All lowercased attributes match with the [Output] input as described in UM Sec.A.1 .","title":"Output"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Output.is_intermediate_link","text":"Generic attribute for models that have children fields that could contain files. Source code in hydrolib/core/dflowfm/mdu/models.py def is_intermediate_link ( self ) -> bool : return True","title":"is_intermediate_link()"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Particles","text":"The [Particles] section in an MDU file. This model is typically referenced under FMModel .particles . All lowercased attributes match with the [Particles] input as described in UM Sec.A.3 .","title":"Particles"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.ParticlesThreeDType","text":"Enum class containing the valid values for the 3Dtype attribute in the Particles class.","title":"ParticlesThreeDType"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Physics","text":"The [Physics] section in an MDU file. This model is typically referenced under FMModel .physics . All lowercased attributes match with the [Physics] input as described in UM Sec.A.1 .","title":"Physics"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.ProcessFluxIntegration","text":"Enum class containing the valid values for the ProcessFluxIntegration attribute in the Processes class.","title":"ProcessFluxIntegration"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Processes","text":"The [Processes] section in an MDU file. This model is typically referenced under FMModel .processes . All lowercased attributes match with the [Processes] input as described in UM Sec.A.3 .","title":"Processes"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Restart","text":"The [Restart] section in an MDU file. This model is typically referenced under FMModel .restart . All lowercased attributes match with the [Restart] input as described in UM Sec.A.1 .","title":"Restart"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Time","text":"The [Time] section in an MDU file. This model is typically referenced under FMModel .time . All lowercased attributes match with the [Time] input as described in UM Sec.A.1 .","title":"Time"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Trachytopes","text":"The [Trachytopes] section in an MDU file. This model is typically referenced under FMModel .trachytopes . All lowercased attributes match with the [Trachytopes] input as described in UM Sec.A.1 .","title":"Trachytopes"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Vegetation","text":"The [Veg] section in an MDU file. This model is typically referenced under FMModel .veg . All lowercased attributes match with the [Veg] input as described in UM Sec.A.3 .","title":"Vegetation"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.VegetationModelNr","text":"Enum class containing the valid values for the VegetationModelNr attribute in the Vegetation class.","title":"VegetationModelNr"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.VolumeTables","text":"The [VolumeTables] section in an MDU file. This model is typically referenced under FMModel .volumetables . All lowercased attributes match with the [VolumeTables] input as described in UM Sec.A.1 .","title":"VolumeTables"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Waves","text":"The [Waves] section in an MDU file. This model is typically referenced under FMModel .waves . All lowercased attributes match with the [Waves] input as described in UM Sec.A.1 .","title":"Waves"},{"location":"reference/mdu/#hydrolib.core.dflowfm.mdu.models.Wind","text":"The [Wind] section in an MDU file. This model is typically referenced under FMModel .wind . All lowercased attributes match with the [Wind] input as described in UM Sec.A.1 .","title":"Wind"},{"location":"reference/net/","text":"Net/grid file \u00b6 The computational grid for D-Flow FM is stored in the net file. It is an unstructured grid, where 1D and 2D can be combined. The file format is NetCDF , using the CF -, UGRID - and Deltares -conventions. The net file is represented by the classes below. Model \u00b6 Branch \u00b6 generate_nodes ( self , mesh1d_edge_length : float , structure_chainage : Optional [ List [ float ]] = None , max_dist_to_struc : Optional [ float ] = None ) \u00b6 Generate the branch offsets and the nodes. Parameters: Name Type Description Default mesh1d_edge_length float The edge length of the 1d mesh. required structure_chainage Optional[List[float]] A list with the structure chainages. If not specified, calculation will not take it into account. Defaults to None. None max_dist_to_struc Optional[float] The maximum distance from a node to a structure. If not specified, calculation will not take it into account. Defaults to None. None Exceptions: Type Description ValueError Raised when any of the structure offsets, if specified, is smaller than zero. ValueError Raised when any of the structure offsets, if specified, is greater than the branch length. Source code in hydrolib/core/dflowfm/net/models.py def generate_nodes ( self , mesh1d_edge_length : float , structure_chainage : Optional [ List [ float ]] = None , max_dist_to_struc : Optional [ float ] = None , ): \"\"\"Generate the branch offsets and the nodes. Args: mesh1d_edge_length (float): The edge length of the 1d mesh. structure_chainage (Optional[List[float]], optional): A list with the structure chainages. If not specified, calculation will not take it into account. Defaults to None. max_dist_to_struc (Optional[float], optional): The maximum distance from a node to a structure. If not specified, calculation will not take it into account. Defaults to None. Raises: ValueError: Raised when any of the structure offsets, if specified, is smaller than zero. ValueError: Raised when any of the structure offsets, if specified, is greater than the branch length. \"\"\" # Generate offsets self . branch_offsets = self . _generate_offsets ( mesh1d_edge_length , structure_chainage , max_dist_to_struc ) # Calculate node positions self . node_xy = self . interpolate ( self . branch_offsets ) # Add mask (all False) self . mask = np . full ( self . branch_offsets . shape , False ) interpolate ( self , distance : npt . ArrayLike ) -> np . ndarray \u00b6 Interpolate coordinates along branch by length Parameters: Name Type Description Default distance npt.ArrayLike Length required Source code in hydrolib/core/dflowfm/net/models.py def interpolate ( self , distance : npt . ArrayLike ) -> np . ndarray : \"\"\"Interpolate coordinates along branch by length Args: distance (npt.ArrayLike): Length \"\"\" intpcoords = np . stack ( [ np . interp ( distance , self . _distance , self . _x_coordinates ), np . interp ( distance , self . _distance , self . _y_coordinates ), ], axis = 1 , ) return intpcoords Link1d2d ( BaseModel ) pydantic-model \u00b6 Link1d2d defines the 1D2D Links of a model network. Attributes: Name Type Description meshkernel Optional[mk.MeshKernel] The MeshKernel used to interact with this Link1d2d link1d2d_id np.ndarray The id of this Link1d2d link1d2d_long_name np.ndarray The long name of this Link1d2d link1d2d_contact_type np.ndarray The contact type of this Link1d2d link1d2d np.ndarray The underlying data object of this Link1d2d clear ( self ) -> None \u00b6 Remove all saved links from the links administration Source code in hydrolib/core/dflowfm/net/models.py def clear ( self ) -> None : \"\"\"Remove all saved links from the links administration\"\"\" self . link1d2d_id = np . empty ( 0 , object ) self . link1d2d_long_name = np . empty ( 0 , object ) self . link1d2d_contact_type = np . empty ( 0 , np . int32 ) self . link1d2d = np . empty (( 0 , 2 ), np . int32 ) # The meshkernel object needs to be resetted self . meshkernel . _deallocate_state () self . meshkernel . _allocate_state ( self . meshkernel . get_projection ()) self . meshkernel . contacts_get () is_empty ( self ) -> bool \u00b6 Whether this Link1d2d is currently empty. Returns: Type Description bool True if the Link1d2d is currently empty; False otherwise. Source code in hydrolib/core/dflowfm/net/models.py def is_empty ( self ) -> bool : \"\"\"Whether this Link1d2d is currently empty. Returns: bool: True if the Link1d2d is currently empty; False otherwise. \"\"\" return self . link1d2d . size == 0 read_file ( self , file_path : Path ) -> None \u00b6 Read the Link1d2d data from the specified netCDF file at file_path into this Parameters: Name Type Description Default file_path Path Path to the netCDF file. required Source code in hydrolib/core/dflowfm/net/models.py def read_file ( self , file_path : Path ) -> None : \"\"\"Read the Link1d2d data from the specified netCDF file at file_path into this Args: file_path (Path): Path to the netCDF file. \"\"\" reader = UgridReader ( file_path ) reader . read_link1d2d ( self ) Mesh1d ( BaseModel ) pydantic-model \u00b6 get_node_mask ( self , branchids : List [ str ] = None ) \u00b6 Get node mask, give a mask with True for each node that is in the given branchid list Source code in hydrolib/core/dflowfm/net/models.py def get_node_mask ( self , branchids : List [ str ] = None ): \"\"\"Get node mask, give a mask with True for each node that is in the given branchid list\"\"\" mask = np . full ( self . mesh1d_node_id . shape , False , dtype = bool ) if branchids is None : mask [:] = True return mask # Get number (index) of given branches idx = np . where ( np . isin ( self . network1d_branch_id , branchids ))[ 0 ] if idx . size == 0 : raise KeyError ( \"No branches corresponding to the given keys were found.\" ) mask [ np . isin ( self . mesh1d_node_branch_id , idx )] = True return mask Mesh2d ( BaseModel ) pydantic-model \u00b6 Mesh2d defines a single two dimensional grid. Attributes: Name Type Description meshkernel mk.MeshKernel The meshkernel used to manimpulate this Mesh2d. mesh2d_node_z np.ndarray The node positions on the z-axis. Defaults to np.empty(0, dtype=np.double). mesh2d_face_z np.ndarray The face positions on the z-axis. Defaults to np.empty(0, dtype=np.double). clip ( self , geometrylist : mk . GeometryList , deletemeshoption : mk . DeleteMeshOption = < DeleteMeshOption . INSIDE_NOT_INTERSECTED : 0 > , inside = False ) -> None \u00b6 Clip the 2D mesh by a polygon. Both outside the exterior and inside the interiors is clipped Parameters: Name Type Description Default geometrylist GeometryList Polygon stored as GeometryList required deletemeshoption int [description]. Defaults to 1. Source code in hydrolib/core/dflowfm/net/models.py def clip ( self , geometrylist : mk . GeometryList , deletemeshoption : mk . DeleteMeshOption = mk . DeleteMeshOption . INSIDE_NOT_INTERSECTED , inside = False , ) -> None : \"\"\"Clip the 2D mesh by a polygon. Both outside the exterior and inside the interiors is clipped Args: geometrylist (GeometryList): Polygon stored as GeometryList deletemeshoption (int, optional): [description]. Defaults to 1. \"\"\" # For clipping outside if not inside : # Check if a multipolygon was provided when clipping outside if geometrylist . geometry_separator in geometrylist . x_coordinates : raise NotImplementedError ( \"Deleting outside more than a single exterior (MultiPolygon) is not implemented.\" ) # Get exterior and interiors parts = split_by ( geometrylist , geometrylist . inner_outer_separator ) exteriors = [ parts [ 0 ]] interiors = parts [ 1 :] # Inside else : # Check if any polygon contains holes, when clipping inside if geometrylist . inner_outer_separator in geometrylist . x_coordinates : raise NotImplementedError ( \"Deleting inside a (Multi)Polygon with holes is not implemented.\" ) # Get exterior and interiors parts = split_by ( geometrylist , geometrylist . geometry_separator ) exteriors = parts [:] interiors = [] # Check if parts are closed for part in exteriors + interiors : if ( part . x_coordinates [ 0 ], part . y_coordinates [ 0 ]) != ( part . x_coordinates [ - 1 ], part . y_coordinates [ - 1 ], ): raise ValueError ( \"First and last coordinate of each GeometryList part should match.\" ) # Delete everything outside the (Multi)Polygon for exterior in exteriors : self . meshkernel . mesh2d_delete ( geometry_list = exterior , delete_option = deletemeshoption , invert_deletion = not inside , ) # Delete all holes. for interior in interiors : self . meshkernel . mesh2d_delete ( geometry_list = interior , delete_option = deletemeshoption , invert_deletion = inside , ) create_rectilinear ( self , extent : tuple , dx : float , dy : float ) -> None \u00b6 Create a rectilinear mesh within a polygon. A rectangular grid is generated within the polygon bounds Parameters: Name Type Description Default extent tuple Bounding box of mesh (left, bottom, right, top) required dx float Horizontal distance required dy float Vertical distance required Exceptions: Type Description NotImplementedError MultiPolygons Source code in hydrolib/core/dflowfm/net/models.py def create_rectilinear ( self , extent : tuple , dx : float , dy : float ) -> None : \"\"\"Create a rectilinear mesh within a polygon. A rectangular grid is generated within the polygon bounds Args: extent (tuple): Bounding box of mesh (left, bottom, right, top) dx (float): Horizontal distance dy (float): Vertical distance Raises: NotImplementedError: MultiPolygons \"\"\" xmin , ymin , xmax , ymax = extent rows = int (( ymax - ymin ) / dy ) columns = int (( xmax - xmin ) / dx ) params = mk . MakeGridParameters ( num_columns = columns , num_rows = rows , origin_x = xmin , origin_y = ymin , block_size_x = dx , block_size_y = dy , ) mesh2d_input = self . meshkernel # mk.MeshKernel() mesh2d_input . curvilinear_compute_rectangular_grid ( params ) mesh2d_input . curvilinear_convert_to_mesh2d () # convert to ugrid/mesh2d create_triangular ( self , geometry_list : mk . GeometryList ) -> None \u00b6 Create triangular grid within GeometryList object Parameters: Name Type Description Default geometry_list mk.GeometryList GeometryList represeting a polygon within which the mesh is generated. required Source code in hydrolib/core/dflowfm/net/models.py def create_triangular ( self , geometry_list : mk . GeometryList ) -> None : \"\"\"Create triangular grid within GeometryList object Args: geometry_list (mk.GeometryList): GeometryList represeting a polygon within which the mesh is generated. \"\"\" # Call meshkernel self . meshkernel . mesh2d_make_triangular_mesh_from_polygon ( geometry_list ) get_mesh2d ( self ) -> mk . Mesh2d \u00b6 Get the mesh2d as represented in the MeshKernel Returns: Type Description (mk.Mesh2d) The mesh2d as represented in the MeshKernel Source code in hydrolib/core/dflowfm/net/models.py def get_mesh2d ( self ) -> mk . Mesh2d : \"\"\"Get the mesh2d as represented in the MeshKernel Returns: (mk.Mesh2d): The mesh2d as represented in the MeshKernel \"\"\" return self . meshkernel . mesh2d_get () is_empty ( self ) -> bool \u00b6 Determine whether this Mesh2d is empty. Returns: Type Description (bool) Whether this Mesh2d is empty. Source code in hydrolib/core/dflowfm/net/models.py def is_empty ( self ) -> bool : \"\"\"Determine whether this Mesh2d is empty. Returns: (bool): Whether this Mesh2d is empty. \"\"\" return self . mesh2d_node_x . size == 0 mesh2d_edge_nodes : np . ndarray [ int , int ] property readonly \u00b6 The node indices of the mesh edges. Returns: Type Description np.ndarray[int, int] A 2D integer array (nEdges, 2) containg the two node indices for each edge. mesh2d_edge_x : np . ndarray [ float ] property readonly \u00b6 The x-coordinates of the mesh edges' middle points. Returns: Type Description ndarray[float] A 1D double array describing x-coordinates of the mesh edges' middle points. mesh2d_edge_y : np . ndarray [ float ] property readonly \u00b6 The y-coordinates of the mesh edges' middle points. Returns: Type Description ndarray[float] A 1D double array describing y-coordinates of the mesh edges' middle points. mesh2d_face_nodes : np . ndarray [ int , int ] property readonly \u00b6 The node indices of the mesh faces Returns: Type Description np.ndarray[int, int] A 2D integer array describing the nodes composing each mesh 2d face. A 2D integer array (nFaces, maxNodesPerFace) containg the node indices for each face. mesh2d_face_x : np . ndarray [ float ] property readonly \u00b6 The x-coordinates of the mesh faces' mass centers. Returns: Type Description ndarray[float] A 1D double array describing x-coordinates of the mesh faces' mass centers. mesh2d_face_y : np . ndarray [ float ] property readonly \u00b6 The y-coordinates of the mesh faces' mass centers. Returns: Type Description ndarray[float] A 1D double array describing y-coordinates of the mesh faces' mass centers. mesh2d_node_x : np . ndarray [ float ] property readonly \u00b6 The x-coordinates of the nodes in the mesh. Returns: Type Description ndarray[float] A 1D double array describing the x-coordinates of the nodes. mesh2d_node_y : np . ndarray [ float ] property readonly \u00b6 The y-coordinates of the nodes in the mesh. Returns: Type Description ndarray[float] A 1D double array describing the y-coordinates of the nodes. read_file ( self , file_path : Path ) -> None \u00b6 Read the Mesh2d from the file at file_path. Parameters: Name Type Description Default file_path Path Path to the file to be read. required Source code in hydrolib/core/dflowfm/net/models.py def read_file ( self , file_path : Path ) -> None : \"\"\"Read the Mesh2d from the file at file_path. Args: file_path (Path): Path to the file to be read. \"\"\" reader = UgridReader ( file_path ) reader . read_mesh2d ( self ) refine ( self , polygon : mk . GeometryList , level : int , min_edge_size = 10.0 ) \u00b6 Refine the mesh within a polygon, by a number of steps (level) Parameters: Name Type Description Default polygon GeometryList Polygon in which to refine required level int Number of refinement steps required Source code in hydrolib/core/dflowfm/net/models.py def refine ( self , polygon : mk . GeometryList , level : int , min_edge_size = 10.0 ): \"\"\"Refine the mesh within a polygon, by a number of steps (level) Args: polygon (GeometryList): Polygon in which to refine level (int): Number of refinement steps \"\"\" # Check if parts are closed # if not (polygon.x_coordinates[0], polygon.y_coordinates[0]) == ( # polygon.x_coordinates[-1], # polygon.y_coordinates[-1], # ): # raise ValueError(\"First and last coordinate of each GeometryList part should match.\") parameters = mk . MeshRefinementParameters ( refine_intersected = True , use_mass_center_when_refining = False , min_edge_size = min_edge_size , # Does nothing? refinement_type = 1 , # No effect? connect_hanging_nodes = True , account_for_samples_outside_face = False , max_refinement_iterations = level , ) self . meshkernel . mesh2d_refine_based_on_polygon ( polygon , parameters ) Network \u00b6 from_file ( file_path : Path ) -> Network classmethod \u00b6 Read network from file. This classmethod checks what mesh components (mesh1d & network1d, mesh2d, link1d2d) are present, and loads them one by one. Parameters: Name Type Description Default file_path Path path to netcdf file with network data required Returns: Type Description Network The instance of the class itself that is returned Source code in hydrolib/core/dflowfm/net/models.py @classmethod def from_file ( cls , file_path : Path ) -> Network : \"\"\"Read network from file. This classmethod checks what mesh components (mesh1d & network1d, mesh2d, link1d2d) are present, and loads them one by one. Args: file_path (Path): path to netcdf file with network data Returns: Network: The instance of the class itself that is returned \"\"\" network = cls () ds = nc . Dataset ( file_path ) # type: ignore[import] reader = UgridReader ( file_path ) reader . read_mesh1d_network1d ( network . _mesh1d ) reader . read_mesh2d ( network . _mesh2d ) reader . read_link1d2d ( network . _link1d2d ) ds . close () return network is_geographic : bool property readonly \u00b6 Whether or not this network has a geographic projection. Returns: Type Description bool True if this network is geographic; otherwise, False. mesh2d_create_triangular_within_polygon ( self , polygon : mk . GeometryList ) -> None \u00b6 Create triangular grid within GeometryList object. Calls _mesh2d.create_triangular directly, but is easier accessible for users. Parameters: Name Type Description Default polygon mk.GeometryList GeometryList representing a polygon within which the mesh is generated. required Source code in hydrolib/core/dflowfm/net/models.py def mesh2d_create_triangular_within_polygon ( self , polygon : mk . GeometryList ) -> None : \"\"\"Create triangular grid within GeometryList object. Calls _mesh2d.create_triangular directly, but is easier accessible for users. Args: polygon (mk.GeometryList): GeometryList representing a polygon within which the mesh is generated. \"\"\" self . _mesh2d . create_triangular ( geometry_list = polygon ) plot ( self , ax = None ) \u00b6 Create a plot of the 1d2d links and edges within this network. Parameters: Name Type Description Default ax matplotlib.pyplot.Axes The axes where to plot the edges. Defaults to None. None Source code in hydrolib/core/dflowfm/net/models.py def plot ( self , ax = None ): \"\"\"Create a plot of the 1d2d links and edges within this network. Args: ax (matplotlib.pyplot.Axes, optional): The axes where to plot the edges. Defaults to None. \"\"\" import matplotlib.pyplot as plt if ax is None : _ , ax = plt . subplots () mesh2d_output = self . _mesh2d . get_mesh2d () mesh1d_output = self . _mesh1d . _get_mesh1d () links_output = self . _link1d2d . meshkernel . contacts_get () mesh2d_output . plot_edges ( ax = ax , color = \"r\" ) mesh1d_output . plot_edges ( ax = ax , color = \"g\" ) links_output . plot_edges ( ax = ax , mesh1d = mesh1d_output , mesh2d = mesh2d_output , color = \"k\" ) to_file ( self , file : Path ) -> None \u00b6 Write network to file Parameters: Name Type Description Default file Path File where _net.nc is written to. required Source code in hydrolib/core/dflowfm/net/models.py def to_file ( self , file : Path ) -> None : \"\"\"Write network to file Args: file (Path): File where _net.nc is written to. \"\"\" writer = UgridWriter () writer . write ( self , file ) NetworkModel ( ParsableFileModel ) pydantic-model \u00b6 Network model representation. split_by ( gl : mk . GeometryList , by : float ) -> list \u00b6 Function to split mk.GeometryList by seperator. Parameters: Name Type Description Default gl mk.GeometryList The geometry list to split. required by float The value by which to split the gl. required Returns: Type Description list The split lists. Source code in hydrolib/core/dflowfm/net/models.py def split_by ( gl : mk . GeometryList , by : float ) -> list : \"\"\"Function to split mk.GeometryList by seperator. Args: gl (mk.GeometryList): The geometry list to split. by (float): The value by which to split the gl. Returns: list: The split lists. \"\"\" x , y = gl . x_coordinates . copy (), gl . y_coordinates . copy () idx = np . where ( x == by )[ 0 ] xparts = np . split ( x , idx ) yparts = np . split ( y , idx ) lists = [ mk . GeometryList ( xp [ min ( i , 1 ) :], yp [ min ( i , 1 ) :]) for i , ( xp , yp ) in enumerate ( zip ( xparts , yparts )) ] return lists","title":"Net/grid file"},{"location":"reference/net/#netgrid-file","text":"The computational grid for D-Flow FM is stored in the net file. It is an unstructured grid, where 1D and 2D can be combined. The file format is NetCDF , using the CF -, UGRID - and Deltares -conventions. The net file is represented by the classes below.","title":"Net/grid file"},{"location":"reference/net/#model","text":"","title":"Model"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Branch","text":"","title":"Branch"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Branch.generate_nodes","text":"Generate the branch offsets and the nodes. Parameters: Name Type Description Default mesh1d_edge_length float The edge length of the 1d mesh. required structure_chainage Optional[List[float]] A list with the structure chainages. If not specified, calculation will not take it into account. Defaults to None. None max_dist_to_struc Optional[float] The maximum distance from a node to a structure. If not specified, calculation will not take it into account. Defaults to None. None Exceptions: Type Description ValueError Raised when any of the structure offsets, if specified, is smaller than zero. ValueError Raised when any of the structure offsets, if specified, is greater than the branch length. Source code in hydrolib/core/dflowfm/net/models.py def generate_nodes ( self , mesh1d_edge_length : float , structure_chainage : Optional [ List [ float ]] = None , max_dist_to_struc : Optional [ float ] = None , ): \"\"\"Generate the branch offsets and the nodes. Args: mesh1d_edge_length (float): The edge length of the 1d mesh. structure_chainage (Optional[List[float]], optional): A list with the structure chainages. If not specified, calculation will not take it into account. Defaults to None. max_dist_to_struc (Optional[float], optional): The maximum distance from a node to a structure. If not specified, calculation will not take it into account. Defaults to None. Raises: ValueError: Raised when any of the structure offsets, if specified, is smaller than zero. ValueError: Raised when any of the structure offsets, if specified, is greater than the branch length. \"\"\" # Generate offsets self . branch_offsets = self . _generate_offsets ( mesh1d_edge_length , structure_chainage , max_dist_to_struc ) # Calculate node positions self . node_xy = self . interpolate ( self . branch_offsets ) # Add mask (all False) self . mask = np . full ( self . branch_offsets . shape , False )","title":"generate_nodes()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Branch.interpolate","text":"Interpolate coordinates along branch by length Parameters: Name Type Description Default distance npt.ArrayLike Length required Source code in hydrolib/core/dflowfm/net/models.py def interpolate ( self , distance : npt . ArrayLike ) -> np . ndarray : \"\"\"Interpolate coordinates along branch by length Args: distance (npt.ArrayLike): Length \"\"\" intpcoords = np . stack ( [ np . interp ( distance , self . _distance , self . _x_coordinates ), np . interp ( distance , self . _distance , self . _y_coordinates ), ], axis = 1 , ) return intpcoords","title":"interpolate()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Link1d2d","text":"Link1d2d defines the 1D2D Links of a model network. Attributes: Name Type Description meshkernel Optional[mk.MeshKernel] The MeshKernel used to interact with this Link1d2d link1d2d_id np.ndarray The id of this Link1d2d link1d2d_long_name np.ndarray The long name of this Link1d2d link1d2d_contact_type np.ndarray The contact type of this Link1d2d link1d2d np.ndarray The underlying data object of this Link1d2d","title":"Link1d2d"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Link1d2d.clear","text":"Remove all saved links from the links administration Source code in hydrolib/core/dflowfm/net/models.py def clear ( self ) -> None : \"\"\"Remove all saved links from the links administration\"\"\" self . link1d2d_id = np . empty ( 0 , object ) self . link1d2d_long_name = np . empty ( 0 , object ) self . link1d2d_contact_type = np . empty ( 0 , np . int32 ) self . link1d2d = np . empty (( 0 , 2 ), np . int32 ) # The meshkernel object needs to be resetted self . meshkernel . _deallocate_state () self . meshkernel . _allocate_state ( self . meshkernel . get_projection ()) self . meshkernel . contacts_get ()","title":"clear()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Link1d2d.is_empty","text":"Whether this Link1d2d is currently empty. Returns: Type Description bool True if the Link1d2d is currently empty; False otherwise. Source code in hydrolib/core/dflowfm/net/models.py def is_empty ( self ) -> bool : \"\"\"Whether this Link1d2d is currently empty. Returns: bool: True if the Link1d2d is currently empty; False otherwise. \"\"\" return self . link1d2d . size == 0","title":"is_empty()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Link1d2d.read_file","text":"Read the Link1d2d data from the specified netCDF file at file_path into this Parameters: Name Type Description Default file_path Path Path to the netCDF file. required Source code in hydrolib/core/dflowfm/net/models.py def read_file ( self , file_path : Path ) -> None : \"\"\"Read the Link1d2d data from the specified netCDF file at file_path into this Args: file_path (Path): Path to the netCDF file. \"\"\" reader = UgridReader ( file_path ) reader . read_link1d2d ( self )","title":"read_file()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh1d","text":"","title":"Mesh1d"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh1d.get_node_mask","text":"Get node mask, give a mask with True for each node that is in the given branchid list Source code in hydrolib/core/dflowfm/net/models.py def get_node_mask ( self , branchids : List [ str ] = None ): \"\"\"Get node mask, give a mask with True for each node that is in the given branchid list\"\"\" mask = np . full ( self . mesh1d_node_id . shape , False , dtype = bool ) if branchids is None : mask [:] = True return mask # Get number (index) of given branches idx = np . where ( np . isin ( self . network1d_branch_id , branchids ))[ 0 ] if idx . size == 0 : raise KeyError ( \"No branches corresponding to the given keys were found.\" ) mask [ np . isin ( self . mesh1d_node_branch_id , idx )] = True return mask","title":"get_node_mask()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d","text":"Mesh2d defines a single two dimensional grid. Attributes: Name Type Description meshkernel mk.MeshKernel The meshkernel used to manimpulate this Mesh2d. mesh2d_node_z np.ndarray The node positions on the z-axis. Defaults to np.empty(0, dtype=np.double). mesh2d_face_z np.ndarray The face positions on the z-axis. Defaults to np.empty(0, dtype=np.double).","title":"Mesh2d"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.clip","text":"Clip the 2D mesh by a polygon. Both outside the exterior and inside the interiors is clipped Parameters: Name Type Description Default geometrylist GeometryList Polygon stored as GeometryList required deletemeshoption int [description]. Defaults to 1. Source code in hydrolib/core/dflowfm/net/models.py def clip ( self , geometrylist : mk . GeometryList , deletemeshoption : mk . DeleteMeshOption = mk . DeleteMeshOption . INSIDE_NOT_INTERSECTED , inside = False , ) -> None : \"\"\"Clip the 2D mesh by a polygon. Both outside the exterior and inside the interiors is clipped Args: geometrylist (GeometryList): Polygon stored as GeometryList deletemeshoption (int, optional): [description]. Defaults to 1. \"\"\" # For clipping outside if not inside : # Check if a multipolygon was provided when clipping outside if geometrylist . geometry_separator in geometrylist . x_coordinates : raise NotImplementedError ( \"Deleting outside more than a single exterior (MultiPolygon) is not implemented.\" ) # Get exterior and interiors parts = split_by ( geometrylist , geometrylist . inner_outer_separator ) exteriors = [ parts [ 0 ]] interiors = parts [ 1 :] # Inside else : # Check if any polygon contains holes, when clipping inside if geometrylist . inner_outer_separator in geometrylist . x_coordinates : raise NotImplementedError ( \"Deleting inside a (Multi)Polygon with holes is not implemented.\" ) # Get exterior and interiors parts = split_by ( geometrylist , geometrylist . geometry_separator ) exteriors = parts [:] interiors = [] # Check if parts are closed for part in exteriors + interiors : if ( part . x_coordinates [ 0 ], part . y_coordinates [ 0 ]) != ( part . x_coordinates [ - 1 ], part . y_coordinates [ - 1 ], ): raise ValueError ( \"First and last coordinate of each GeometryList part should match.\" ) # Delete everything outside the (Multi)Polygon for exterior in exteriors : self . meshkernel . mesh2d_delete ( geometry_list = exterior , delete_option = deletemeshoption , invert_deletion = not inside , ) # Delete all holes. for interior in interiors : self . meshkernel . mesh2d_delete ( geometry_list = interior , delete_option = deletemeshoption , invert_deletion = inside , )","title":"clip()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.create_rectilinear","text":"Create a rectilinear mesh within a polygon. A rectangular grid is generated within the polygon bounds Parameters: Name Type Description Default extent tuple Bounding box of mesh (left, bottom, right, top) required dx float Horizontal distance required dy float Vertical distance required Exceptions: Type Description NotImplementedError MultiPolygons Source code in hydrolib/core/dflowfm/net/models.py def create_rectilinear ( self , extent : tuple , dx : float , dy : float ) -> None : \"\"\"Create a rectilinear mesh within a polygon. A rectangular grid is generated within the polygon bounds Args: extent (tuple): Bounding box of mesh (left, bottom, right, top) dx (float): Horizontal distance dy (float): Vertical distance Raises: NotImplementedError: MultiPolygons \"\"\" xmin , ymin , xmax , ymax = extent rows = int (( ymax - ymin ) / dy ) columns = int (( xmax - xmin ) / dx ) params = mk . MakeGridParameters ( num_columns = columns , num_rows = rows , origin_x = xmin , origin_y = ymin , block_size_x = dx , block_size_y = dy , ) mesh2d_input = self . meshkernel # mk.MeshKernel() mesh2d_input . curvilinear_compute_rectangular_grid ( params ) mesh2d_input . curvilinear_convert_to_mesh2d () # convert to ugrid/mesh2d","title":"create_rectilinear()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.create_triangular","text":"Create triangular grid within GeometryList object Parameters: Name Type Description Default geometry_list mk.GeometryList GeometryList represeting a polygon within which the mesh is generated. required Source code in hydrolib/core/dflowfm/net/models.py def create_triangular ( self , geometry_list : mk . GeometryList ) -> None : \"\"\"Create triangular grid within GeometryList object Args: geometry_list (mk.GeometryList): GeometryList represeting a polygon within which the mesh is generated. \"\"\" # Call meshkernel self . meshkernel . mesh2d_make_triangular_mesh_from_polygon ( geometry_list )","title":"create_triangular()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.get_mesh2d","text":"Get the mesh2d as represented in the MeshKernel Returns: Type Description (mk.Mesh2d) The mesh2d as represented in the MeshKernel Source code in hydrolib/core/dflowfm/net/models.py def get_mesh2d ( self ) -> mk . Mesh2d : \"\"\"Get the mesh2d as represented in the MeshKernel Returns: (mk.Mesh2d): The mesh2d as represented in the MeshKernel \"\"\" return self . meshkernel . mesh2d_get ()","title":"get_mesh2d()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.is_empty","text":"Determine whether this Mesh2d is empty. Returns: Type Description (bool) Whether this Mesh2d is empty. Source code in hydrolib/core/dflowfm/net/models.py def is_empty ( self ) -> bool : \"\"\"Determine whether this Mesh2d is empty. Returns: (bool): Whether this Mesh2d is empty. \"\"\" return self . mesh2d_node_x . size == 0","title":"is_empty()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.mesh2d_edge_nodes","text":"The node indices of the mesh edges. Returns: Type Description np.ndarray[int, int] A 2D integer array (nEdges, 2) containg the two node indices for each edge.","title":"mesh2d_edge_nodes"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.mesh2d_edge_x","text":"The x-coordinates of the mesh edges' middle points. Returns: Type Description ndarray[float] A 1D double array describing x-coordinates of the mesh edges' middle points.","title":"mesh2d_edge_x"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.mesh2d_edge_y","text":"The y-coordinates of the mesh edges' middle points. Returns: Type Description ndarray[float] A 1D double array describing y-coordinates of the mesh edges' middle points.","title":"mesh2d_edge_y"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.mesh2d_face_nodes","text":"The node indices of the mesh faces Returns: Type Description np.ndarray[int, int] A 2D integer array describing the nodes composing each mesh 2d face. A 2D integer array (nFaces, maxNodesPerFace) containg the node indices for each face.","title":"mesh2d_face_nodes"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.mesh2d_face_x","text":"The x-coordinates of the mesh faces' mass centers. Returns: Type Description ndarray[float] A 1D double array describing x-coordinates of the mesh faces' mass centers.","title":"mesh2d_face_x"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.mesh2d_face_y","text":"The y-coordinates of the mesh faces' mass centers. Returns: Type Description ndarray[float] A 1D double array describing y-coordinates of the mesh faces' mass centers.","title":"mesh2d_face_y"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.mesh2d_node_x","text":"The x-coordinates of the nodes in the mesh. Returns: Type Description ndarray[float] A 1D double array describing the x-coordinates of the nodes.","title":"mesh2d_node_x"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.mesh2d_node_y","text":"The y-coordinates of the nodes in the mesh. Returns: Type Description ndarray[float] A 1D double array describing the y-coordinates of the nodes.","title":"mesh2d_node_y"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.read_file","text":"Read the Mesh2d from the file at file_path. Parameters: Name Type Description Default file_path Path Path to the file to be read. required Source code in hydrolib/core/dflowfm/net/models.py def read_file ( self , file_path : Path ) -> None : \"\"\"Read the Mesh2d from the file at file_path. Args: file_path (Path): Path to the file to be read. \"\"\" reader = UgridReader ( file_path ) reader . read_mesh2d ( self )","title":"read_file()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Mesh2d.refine","text":"Refine the mesh within a polygon, by a number of steps (level) Parameters: Name Type Description Default polygon GeometryList Polygon in which to refine required level int Number of refinement steps required Source code in hydrolib/core/dflowfm/net/models.py def refine ( self , polygon : mk . GeometryList , level : int , min_edge_size = 10.0 ): \"\"\"Refine the mesh within a polygon, by a number of steps (level) Args: polygon (GeometryList): Polygon in which to refine level (int): Number of refinement steps \"\"\" # Check if parts are closed # if not (polygon.x_coordinates[0], polygon.y_coordinates[0]) == ( # polygon.x_coordinates[-1], # polygon.y_coordinates[-1], # ): # raise ValueError(\"First and last coordinate of each GeometryList part should match.\") parameters = mk . MeshRefinementParameters ( refine_intersected = True , use_mass_center_when_refining = False , min_edge_size = min_edge_size , # Does nothing? refinement_type = 1 , # No effect? connect_hanging_nodes = True , account_for_samples_outside_face = False , max_refinement_iterations = level , ) self . meshkernel . mesh2d_refine_based_on_polygon ( polygon , parameters )","title":"refine()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Network","text":"","title":"Network"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Network.from_file","text":"Read network from file. This classmethod checks what mesh components (mesh1d & network1d, mesh2d, link1d2d) are present, and loads them one by one. Parameters: Name Type Description Default file_path Path path to netcdf file with network data required Returns: Type Description Network The instance of the class itself that is returned Source code in hydrolib/core/dflowfm/net/models.py @classmethod def from_file ( cls , file_path : Path ) -> Network : \"\"\"Read network from file. This classmethod checks what mesh components (mesh1d & network1d, mesh2d, link1d2d) are present, and loads them one by one. Args: file_path (Path): path to netcdf file with network data Returns: Network: The instance of the class itself that is returned \"\"\" network = cls () ds = nc . Dataset ( file_path ) # type: ignore[import] reader = UgridReader ( file_path ) reader . read_mesh1d_network1d ( network . _mesh1d ) reader . read_mesh2d ( network . _mesh2d ) reader . read_link1d2d ( network . _link1d2d ) ds . close () return network","title":"from_file()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Network.is_geographic","text":"Whether or not this network has a geographic projection. Returns: Type Description bool True if this network is geographic; otherwise, False.","title":"is_geographic"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Network.mesh2d_create_triangular_within_polygon","text":"Create triangular grid within GeometryList object. Calls _mesh2d.create_triangular directly, but is easier accessible for users. Parameters: Name Type Description Default polygon mk.GeometryList GeometryList representing a polygon within which the mesh is generated. required Source code in hydrolib/core/dflowfm/net/models.py def mesh2d_create_triangular_within_polygon ( self , polygon : mk . GeometryList ) -> None : \"\"\"Create triangular grid within GeometryList object. Calls _mesh2d.create_triangular directly, but is easier accessible for users. Args: polygon (mk.GeometryList): GeometryList representing a polygon within which the mesh is generated. \"\"\" self . _mesh2d . create_triangular ( geometry_list = polygon )","title":"mesh2d_create_triangular_within_polygon()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Network.plot","text":"Create a plot of the 1d2d links and edges within this network. Parameters: Name Type Description Default ax matplotlib.pyplot.Axes The axes where to plot the edges. Defaults to None. None Source code in hydrolib/core/dflowfm/net/models.py def plot ( self , ax = None ): \"\"\"Create a plot of the 1d2d links and edges within this network. Args: ax (matplotlib.pyplot.Axes, optional): The axes where to plot the edges. Defaults to None. \"\"\" import matplotlib.pyplot as plt if ax is None : _ , ax = plt . subplots () mesh2d_output = self . _mesh2d . get_mesh2d () mesh1d_output = self . _mesh1d . _get_mesh1d () links_output = self . _link1d2d . meshkernel . contacts_get () mesh2d_output . plot_edges ( ax = ax , color = \"r\" ) mesh1d_output . plot_edges ( ax = ax , color = \"g\" ) links_output . plot_edges ( ax = ax , mesh1d = mesh1d_output , mesh2d = mesh2d_output , color = \"k\" )","title":"plot()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.Network.to_file","text":"Write network to file Parameters: Name Type Description Default file Path File where _net.nc is written to. required Source code in hydrolib/core/dflowfm/net/models.py def to_file ( self , file : Path ) -> None : \"\"\"Write network to file Args: file (Path): File where _net.nc is written to. \"\"\" writer = UgridWriter () writer . write ( self , file )","title":"to_file()"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.NetworkModel","text":"Network model representation.","title":"NetworkModel"},{"location":"reference/net/#hydrolib.core.dflowfm.net.models.split_by","text":"Function to split mk.GeometryList by seperator. Parameters: Name Type Description Default gl mk.GeometryList The geometry list to split. required by float The value by which to split the gl. required Returns: Type Description list The split lists. Source code in hydrolib/core/dflowfm/net/models.py def split_by ( gl : mk . GeometryList , by : float ) -> list : \"\"\"Function to split mk.GeometryList by seperator. Args: gl (mk.GeometryList): The geometry list to split. by (float): The value by which to split the gl. Returns: list: The split lists. \"\"\" x , y = gl . x_coordinates . copy (), gl . y_coordinates . copy () idx = np . where ( x == by )[ 0 ] xparts = np . split ( x , idx ) yparts = np . split ( y , idx ) lists = [ mk . GeometryList ( xp [ min ( i , 1 ) :], yp [ min ( i , 1 ) :]) for i , ( xp , yp ) in enumerate ( zip ( xparts , yparts )) ] return lists","title":"split_by()"},{"location":"reference/observationcrosssection/","text":"Observation cross section files \u00b6 Observation cross section files come in two flavours: the official *_crs.ini format see below the legacy *.pli format see below Observation cross section .ini files \u00b6 The obscrosssection module provides the specific logic for accessing observation cross section .ini files. for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. An observation cross section .ini file is described by the classes below. Model \u00b6 ObservationCrossSection ( INIBasedModel ) pydantic-model \u00b6 The observation cross section that is included in the observation cross section file. All lowercased attributes match with the observation cross section output as described in [UM Sec.F2.4.1] (https://content.oss.deltares.nl/delft3dfm1d2d/D-Flow_FM_User_Manual_1D2D.pdf#subsubsection.F.2.4.1) validate_that_location_specification_is_correct ( values : Dict ) -> Dict classmethod \u00b6 Validates that the correct location specification is given. Source code in hydrolib/core/dflowfm/obscrosssection/models.py @root_validator ( allow_reuse = True ) def validate_that_location_specification_is_correct ( cls , values : Dict ) -> Dict : \"\"\"Validates that the correct location specification is given.\"\"\" return validate_location_specification ( values , config = LocationValidationConfiguration ( validate_node = False , minimum_num_coordinates = 2 ), ) ObservationCrossSectionGeneral ( INIGeneral ) pydantic-model \u00b6 The observation cross section file's [General] section with file meta data. ObservationCrossSectionModel ( INIModel ) pydantic-model \u00b6 The overall observation cross section model that contains the contents of one observation cross section file. Legacy observation cross section .pli files \u00b6 Legacy .pli files for observation points are supported via the generic polyfile module. A polyfile (hence also an observation cross section .pli file) is described by the classes below. Model \u00b6 models.py defines all classes and functions related to representing pol/pli(z) files. Description ( BaseModel ) pydantic-model \u00b6 Description of a single PolyObject. The Description will be prepended to a block. Each line will start with a '*'. Attributes: Name Type Description content str The content of this Description. Metadata ( BaseModel ) pydantic-model \u00b6 Metadata of a single PolyObject. Attributes: Name Type Description name str The name of the PolyObject n_rows int The number of rows (i.e. Point instances) of the PolyObject n_columns int The total number of values in a Point, including x, y, and z. Point ( BaseModel ) pydantic-model \u00b6 Point consisting of a x and y coordinate, an optional z coordinate and data. Attributes: Name Type Description x float The x-coordinate of this Point y float The y-coordinate of this Point z Optional[float] An optional z-coordinate of this Point. data Sequence[float] The additional data variables of this Point. PolyFile ( ParsableFileModel ) pydantic-model \u00b6 Poly-file (.pol/.pli/.pliz) representation. PolyObject ( BaseModel ) pydantic-model \u00b6 PolyObject describing a single block in a poly file. The metadata should be consistent with the points: - The number of points should be equal to number of rows defined in the metadata - The data of each point should be equal to the number of columns defined in the metadata. Attributes: Name Type Description description Optional[Description] An optional description of this PolyObject metadata Metadata The Metadata of this PolObject, describing the structure points List[Point] The points describing this PolyObject, structured according to the Metadata","title":"Observation cross section files"},{"location":"reference/observationcrosssection/#observation-cross-section-files","text":"Observation cross section files come in two flavours: the official *_crs.ini format see below the legacy *.pli format see below","title":"Observation cross section files"},{"location":"reference/observationcrosssection/#observation-cross-section-ini-files","text":"The obscrosssection module provides the specific logic for accessing observation cross section .ini files. for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. An observation cross section .ini file is described by the classes below.","title":"Observation cross section .ini files"},{"location":"reference/observationcrosssection/#model","text":"","title":"Model"},{"location":"reference/observationcrosssection/#hydrolib.core.dflowfm.obscrosssection.models.ObservationCrossSection","text":"The observation cross section that is included in the observation cross section file. All lowercased attributes match with the observation cross section output as described in [UM Sec.F2.4.1] (https://content.oss.deltares.nl/delft3dfm1d2d/D-Flow_FM_User_Manual_1D2D.pdf#subsubsection.F.2.4.1)","title":"ObservationCrossSection"},{"location":"reference/observationcrosssection/#hydrolib.core.dflowfm.obscrosssection.models.ObservationCrossSection.validate_that_location_specification_is_correct","text":"Validates that the correct location specification is given. Source code in hydrolib/core/dflowfm/obscrosssection/models.py @root_validator ( allow_reuse = True ) def validate_that_location_specification_is_correct ( cls , values : Dict ) -> Dict : \"\"\"Validates that the correct location specification is given.\"\"\" return validate_location_specification ( values , config = LocationValidationConfiguration ( validate_node = False , minimum_num_coordinates = 2 ), )","title":"validate_that_location_specification_is_correct()"},{"location":"reference/observationcrosssection/#hydrolib.core.dflowfm.obscrosssection.models.ObservationCrossSectionGeneral","text":"The observation cross section file's [General] section with file meta data.","title":"ObservationCrossSectionGeneral"},{"location":"reference/observationcrosssection/#hydrolib.core.dflowfm.obscrosssection.models.ObservationCrossSectionModel","text":"The overall observation cross section model that contains the contents of one observation cross section file.","title":"ObservationCrossSectionModel"},{"location":"reference/observationcrosssection/#legacy-observation-cross-section-pli-files","text":"Legacy .pli files for observation points are supported via the generic polyfile module. A polyfile (hence also an observation cross section .pli file) is described by the classes below.","title":"Legacy observation cross section .pli files"},{"location":"reference/observationcrosssection/#model_1","text":"models.py defines all classes and functions related to representing pol/pli(z) files.","title":"Model"},{"location":"reference/observationcrosssection/#hydrolib.core.dflowfm.polyfile.models.Description","text":"Description of a single PolyObject. The Description will be prepended to a block. Each line will start with a '*'. Attributes: Name Type Description content str The content of this Description.","title":"Description"},{"location":"reference/observationcrosssection/#hydrolib.core.dflowfm.polyfile.models.Metadata","text":"Metadata of a single PolyObject. Attributes: Name Type Description name str The name of the PolyObject n_rows int The number of rows (i.e. Point instances) of the PolyObject n_columns int The total number of values in a Point, including x, y, and z.","title":"Metadata"},{"location":"reference/observationcrosssection/#hydrolib.core.dflowfm.polyfile.models.Point","text":"Point consisting of a x and y coordinate, an optional z coordinate and data. Attributes: Name Type Description x float The x-coordinate of this Point y float The y-coordinate of this Point z Optional[float] An optional z-coordinate of this Point. data Sequence[float] The additional data variables of this Point.","title":"Point"},{"location":"reference/observationcrosssection/#hydrolib.core.dflowfm.polyfile.models.PolyFile","text":"Poly-file (.pol/.pli/.pliz) representation.","title":"PolyFile"},{"location":"reference/observationcrosssection/#hydrolib.core.dflowfm.polyfile.models.PolyObject","text":"PolyObject describing a single block in a poly file. The metadata should be consistent with the points: - The number of points should be equal to number of rows defined in the metadata - The data of each point should be equal to the number of columns defined in the metadata. Attributes: Name Type Description description Optional[Description] An optional description of this PolyObject metadata Metadata The Metadata of this PolObject, describing the structure points List[Point] The points describing this PolyObject, structured according to the Metadata","title":"PolyObject"},{"location":"reference/observationpoint/","text":"Observation point files \u00b6 Observation point files come in two flavours: the official *_obs.ini format see below the legacy *.xyn format see below Observation point .ini files \u00b6 The obs module provides the specific logic for accessing observation point .ini files for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. An observation point .ini file is described by the classes below. Model \u00b6 ObservationPoint ( INIBasedModel ) pydantic-model \u00b6 An observation point that is included in the observation point file. All lowercased attributes match with the observation point input as described in UM Sec.F.2.2.1 . validate_that_location_specification_is_correct ( values : Dict ) -> Dict classmethod \u00b6 Validates that the correct location specification is given. Source code in hydrolib/core/dflowfm/obs/models.py @root_validator ( allow_reuse = True ) def validate_that_location_specification_is_correct ( cls , values : Dict ) -> Dict : \"\"\"Validates that the correct location specification is given.\"\"\" return validate_location_specification ( values , config = LocationValidationConfiguration ( validate_node = False , validate_num_coordinates = False ), fields = LocationValidationFieldNames ( x_coordinates = \"x\" , y_coordinates = \"y\" ), ) ObservationPointGeneral ( INIGeneral ) pydantic-model \u00b6 The observation point file's [General] section with file meta data. ObservationPointModel ( INIModel ) pydantic-model \u00b6 The overall observation point model that contains the contents of one observation point file. This model is typically referenced under a FMModel .output.obsfile[..] . Attributes: Name Type Description general ObservationPointGeneral [General] block with file metadata. observationpoint List[ObservationPoint] List of [ObservationPoint] blocks for all observation points. Legacy observation point .xyn files \u00b6 The xyn module provides the specific logic for accessing legacy observation point files for a D-Flow FM model. An observation point .xyn file is described by the classes below. Model \u00b6 XYNModel ( ParsableFileModel ) pydantic-model \u00b6 Observation station (.xyn) file. dict ( self , * args , ** kwargs ) \u00b6 Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dflowfm/xyn/models.py def dict ( self , * args , ** kwargs ): # speed up serializing by not converting these lowest models to dict return dict ( points = self . points ) XYNPoint ( BaseModel ) pydantic-model \u00b6 Single XYN point, representing a named station location.","title":"Observation point files"},{"location":"reference/observationpoint/#observation-point-files","text":"Observation point files come in two flavours: the official *_obs.ini format see below the legacy *.xyn format see below","title":"Observation point files"},{"location":"reference/observationpoint/#observation-point-ini-files","text":"The obs module provides the specific logic for accessing observation point .ini files for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. An observation point .ini file is described by the classes below.","title":"Observation point .ini files"},{"location":"reference/observationpoint/#model","text":"","title":"Model"},{"location":"reference/observationpoint/#hydrolib.core.dflowfm.obs.models.ObservationPoint","text":"An observation point that is included in the observation point file. All lowercased attributes match with the observation point input as described in UM Sec.F.2.2.1 .","title":"ObservationPoint"},{"location":"reference/observationpoint/#hydrolib.core.dflowfm.obs.models.ObservationPoint.validate_that_location_specification_is_correct","text":"Validates that the correct location specification is given. Source code in hydrolib/core/dflowfm/obs/models.py @root_validator ( allow_reuse = True ) def validate_that_location_specification_is_correct ( cls , values : Dict ) -> Dict : \"\"\"Validates that the correct location specification is given.\"\"\" return validate_location_specification ( values , config = LocationValidationConfiguration ( validate_node = False , validate_num_coordinates = False ), fields = LocationValidationFieldNames ( x_coordinates = \"x\" , y_coordinates = \"y\" ), )","title":"validate_that_location_specification_is_correct()"},{"location":"reference/observationpoint/#hydrolib.core.dflowfm.obs.models.ObservationPointGeneral","text":"The observation point file's [General] section with file meta data.","title":"ObservationPointGeneral"},{"location":"reference/observationpoint/#hydrolib.core.dflowfm.obs.models.ObservationPointModel","text":"The overall observation point model that contains the contents of one observation point file. This model is typically referenced under a FMModel .output.obsfile[..] . Attributes: Name Type Description general ObservationPointGeneral [General] block with file metadata. observationpoint List[ObservationPoint] List of [ObservationPoint] blocks for all observation points.","title":"ObservationPointModel"},{"location":"reference/observationpoint/#legacy-observation-point-xyn-files","text":"The xyn module provides the specific logic for accessing legacy observation point files for a D-Flow FM model. An observation point .xyn file is described by the classes below.","title":"Legacy observation point .xyn files"},{"location":"reference/observationpoint/#model_1","text":"","title":"Model"},{"location":"reference/observationpoint/#hydrolib.core.dflowfm.xyn.models.XYNModel","text":"Observation station (.xyn) file.","title":"XYNModel"},{"location":"reference/observationpoint/#hydrolib.core.dflowfm.xyn.models.XYNModel.dict","text":"Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dflowfm/xyn/models.py def dict ( self , * args , ** kwargs ): # speed up serializing by not converting these lowest models to dict return dict ( points = self . points )","title":"dict()"},{"location":"reference/observationpoint/#hydrolib.core.dflowfm.xyn.models.XYNPoint","text":"Single XYN point, representing a named station location.","title":"XYNPoint"},{"location":"reference/onedfield/","text":"1D field INI files \u00b6 The 1D field INI files contain the spatial input data for 1D network initial conditions for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. The 1D field INI file is represented by the classes below. Model \u00b6 OneDFieldBranch ( INIBasedModel ) pydantic-model \u00b6 A [Branch] block for use inside a 1D field file. Each block can define value(s) on a particular branch. check_list_length_chainage ( values ) classmethod \u00b6 Validates that the length of the chainage field is as expected. Source code in hydrolib/core/dflowfm/onedfield/models.py @root_validator ( allow_reuse = True ) def check_list_length_chainage ( cls , values ): \"\"\"Validates that the length of the chainage field is as expected.\"\"\" return validate_correct_length ( values , \"chainage\" , length_name = \"numlocations\" , list_required_with_length = True , ) check_list_length_values ( values ) classmethod \u00b6 Validates that the length of the values field is as expected. Source code in hydrolib/core/dflowfm/onedfield/models.py @root_validator ( allow_reuse = True ) def check_list_length_values ( cls , values ): \"\"\"Validates that the length of the values field is as expected.\"\"\" return validate_correct_length ( values , \"values\" , length_name = \"numlocations\" , list_required_with_length = True , min_length = 1 , ) OneDFieldGeneral ( INIGeneral ) pydantic-model \u00b6 The 1D field file's [General] section with file meta data. OneDFieldGlobal ( INIBasedModel ) pydantic-model \u00b6 The [Global] block with a uniform value for use inside a 1D field file. OneDFieldModel ( INIModel ) pydantic-model \u00b6 The overall 1D field model that contains the contents of a 1D field file. This model is typically used when a FMModel .geometry.inifieldfile[..].initial[..].datafiletype==DataFileType.onedfield . Attributes: Name Type Description general OneDFieldGeneral [General] block with file metadata. global_ Optional[OneDFieldGlobal] Optional [Global] block with uniform value. branch List[OneDFieldBranch] Definitions of [Branch] field values.","title":"1D field INI files"},{"location":"reference/onedfield/#1d-field-ini-files","text":"The 1D field INI files contain the spatial input data for 1D network initial conditions for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. The 1D field INI file is represented by the classes below.","title":"1D field INI files"},{"location":"reference/onedfield/#model","text":"","title":"Model"},{"location":"reference/onedfield/#hydrolib.core.dflowfm.onedfield.models.OneDFieldBranch","text":"A [Branch] block for use inside a 1D field file. Each block can define value(s) on a particular branch.","title":"OneDFieldBranch"},{"location":"reference/onedfield/#hydrolib.core.dflowfm.onedfield.models.OneDFieldBranch.check_list_length_chainage","text":"Validates that the length of the chainage field is as expected. Source code in hydrolib/core/dflowfm/onedfield/models.py @root_validator ( allow_reuse = True ) def check_list_length_chainage ( cls , values ): \"\"\"Validates that the length of the chainage field is as expected.\"\"\" return validate_correct_length ( values , \"chainage\" , length_name = \"numlocations\" , list_required_with_length = True , )","title":"check_list_length_chainage()"},{"location":"reference/onedfield/#hydrolib.core.dflowfm.onedfield.models.OneDFieldBranch.check_list_length_values","text":"Validates that the length of the values field is as expected. Source code in hydrolib/core/dflowfm/onedfield/models.py @root_validator ( allow_reuse = True ) def check_list_length_values ( cls , values ): \"\"\"Validates that the length of the values field is as expected.\"\"\" return validate_correct_length ( values , \"values\" , length_name = \"numlocations\" , list_required_with_length = True , min_length = 1 , )","title":"check_list_length_values()"},{"location":"reference/onedfield/#hydrolib.core.dflowfm.onedfield.models.OneDFieldGeneral","text":"The 1D field file's [General] section with file meta data.","title":"OneDFieldGeneral"},{"location":"reference/onedfield/#hydrolib.core.dflowfm.onedfield.models.OneDFieldGlobal","text":"The [Global] block with a uniform value for use inside a 1D field file.","title":"OneDFieldGlobal"},{"location":"reference/onedfield/#hydrolib.core.dflowfm.onedfield.models.OneDFieldModel","text":"The overall 1D field model that contains the contents of a 1D field file. This model is typically used when a FMModel .geometry.inifieldfile[..].initial[..].datafiletype==DataFileType.onedfield . Attributes: Name Type Description general OneDFieldGeneral [General] block with file metadata. global_ Optional[OneDFieldGlobal] Optional [Global] block with uniform value. branch List[OneDFieldBranch] Definitions of [Branch] field values.","title":"OneDFieldModel"},{"location":"reference/polyfile/","text":"Polyline/polygon files \u00b6 Polyline .pli(z) and polygon .pol files are basic spatial input files for a D-Flow FM model to select particular locations, and are used in various other input files. They are represented by the classes below. Model \u00b6 models.py defines all classes and functions related to representing pol/pli(z) files. Description ( BaseModel ) pydantic-model \u00b6 Description of a single PolyObject. The Description will be prepended to a block. Each line will start with a '*'. Attributes: Name Type Description content str The content of this Description. Metadata ( BaseModel ) pydantic-model \u00b6 Metadata of a single PolyObject. Attributes: Name Type Description name str The name of the PolyObject n_rows int The number of rows (i.e. Point instances) of the PolyObject n_columns int The total number of values in a Point, including x, y, and z. Point ( BaseModel ) pydantic-model \u00b6 Point consisting of a x and y coordinate, an optional z coordinate and data. Attributes: Name Type Description x float The x-coordinate of this Point y float The y-coordinate of this Point z Optional[float] An optional z-coordinate of this Point. data Sequence[float] The additional data variables of this Point. PolyFile ( ParsableFileModel ) pydantic-model \u00b6 Poly-file (.pol/.pli/.pliz) representation. PolyObject ( BaseModel ) pydantic-model \u00b6 PolyObject describing a single block in a poly file. The metadata should be consistent with the points: - The number of points should be equal to number of rows defined in the metadata - The data of each point should be equal to the number of columns defined in the metadata. Attributes: Name Type Description description Optional[Description] An optional description of this PolyObject metadata Metadata The Metadata of this PolObject, describing the structure points List[Point] The points describing this PolyObject, structured according to the Metadata Parser \u00b6 parser.py defines all classes and functions related to parsing pol/pli(z) files. Block ( BaseModel ) pydantic-model \u00b6 Block is a temporary object which will be converted into a PolyObject. The fields are supposed to be set during the lifetime of this object. When all fields are set, finalize can be called. Attributes: Name Type Description start_line int The starting line of this current block. name Optional[str] The name of this block. Defaults to None. dimensions Optional[Tuple[int, int]] The dimensions (n_rows, n_columns) of this Block. Defaults to None. points Optional[List[Point]] The points of this block. Defaults to None. ws_warnings List[ParseMsg] The whitespace warnings associated with this block. Defaults to an empty list. empty_lines List[int] The line numbers of the empty lines. Defaults to an empty list. finalize ( self ) -> Optional [ Tuple [ hydrolib . core . dflowfm . polyfile . models . PolyObject , List [ hydrolib . core . dflowfm . polyfile . parser . ParseMsg ]]] \u00b6 Finalise this Block and return the constructed PolyObject and warnings If the metadata or the points are None, then None is returned. Returns: Type Description Optional[Tuple[PolyObject, List[ParseMsg]]] The constructed PolyObject and warnings encountered while parsing it. Source code in hydrolib/core/dflowfm/polyfile/parser.py def finalize ( self ) -> Optional [ Tuple [ PolyObject , List [ ParseMsg ]]]: \"\"\"Finalise this Block and return the constructed PolyObject and warnings If the metadata or the points are None, then None is returned. Returns: Optional[Tuple[PolyObject, List[ParseMsg]]]: The constructed PolyObject and warnings encountered while parsing it. \"\"\" metadata = self . _get_metadata () if metadata is None or self . points is None : return None obj = PolyObject ( description = self . _get_description (), metadata = metadata , points = self . points ) return obj , self . ws_warnings + self . _get_empty_line_warnings () ErrorBuilder \u00b6 ErrorBuilder provides the functionality to the Parser to keep track of errors. __init__ ( self ) -> None special \u00b6 Create a new ErorrorBuilder Source code in hydrolib/core/dflowfm/polyfile/parser.py def __init__ ( self ) -> None : \"\"\"Create a new ErorrorBuilder\"\"\" self . _current_block : Optional [ InvalidBlock ] = None end_invalid_block ( self , line : int ) -> None \u00b6 Store the end line of the current block If no invalid block currently exists, nothing will be done. Parameters: Name Type Description Default line int the final line of this invalid block required Source code in hydrolib/core/dflowfm/polyfile/parser.py def end_invalid_block ( self , line : int ) -> None : \"\"\"Store the end line of the current block If no invalid block currently exists, nothing will be done. Args: line (int): the final line of this invalid block \"\"\" if self . _current_block is not None : self . _current_block . end_line = line finalize_previous_error ( self ) -> Optional [ hydrolib . core . dflowfm . polyfile . parser . ParseMsg ] \u00b6 Finalize the current invalid block if it exists If no current invalid block exists, None will be returned, and nothing will change. If a current block exists, it will be converted into a ParseMsg and returned. The current invalid block will be reset. Returns: Type Description Optional[ParseMsg] The corresponding ParseMsg if an InvalidBlock exists. Source code in hydrolib/core/dflowfm/polyfile/parser.py def finalize_previous_error ( self ) -> Optional [ ParseMsg ]: \"\"\"Finalize the current invalid block if it exists If no current invalid block exists, None will be returned, and nothing will change. If a current block exists, it will be converted into a ParseMsg and returned. The current invalid block will be reset. Returns: Optional[ParseMsg]: The corresponding ParseMsg if an InvalidBlock exists. \"\"\" if self . _current_block is not None : msg = self . _current_block . to_msg () self . _current_block = None return msg else : return None start_invalid_block ( self , block_start : int , invalid_line : int , reason : str ) -> None \u00b6 Start a new invalid block if none exists at the moment If we are already in an invalid block, or the previous one was never finalised, we will not log the reason, and assume it is one long invalid block. Parameters: Name Type Description Default block_start int The start of the invalid block. required invalid_line int The actual offending line number. required reason str The reason why this block is invalid. required Source code in hydrolib/core/dflowfm/polyfile/parser.py def start_invalid_block ( self , block_start : int , invalid_line : int , reason : str ) -> None : \"\"\"Start a new invalid block if none exists at the moment If we are already in an invalid block, or the previous one was never finalised, we will not log the reason, and assume it is one long invalid block. Args: block_start (int): The start of the invalid block. invalid_line (int): The actual offending line number. reason (str): The reason why this block is invalid. \"\"\" if self . _current_block is None : self . _current_block = InvalidBlock ( start_line = block_start , invalid_line = invalid_line , reason = reason ) InvalidBlock ( BaseModel ) pydantic-model \u00b6 InvalidBlock is a temporary object which will be converted into a ParseMsg. Attributes: Name Type Description start_line int The start line of this InvalidBlock end_line Optional[int] The end line of this InvalidBlock if it is set. Defaults to None. invalid_line int The line which is causing this block to be invalid. reason str A human-readable string detailing the reason of the ParseMsg. to_msg ( self ) -> ParseMsg \u00b6 Convert this InvalidBlock to the corresponding ParseMsg Returns: Type Description ParseMsg The ParseMsg corresponding with this InvalidBlock Source code in hydrolib/core/dflowfm/polyfile/parser.py def to_msg ( self ) -> ParseMsg : \"\"\"Convert this InvalidBlock to the corresponding ParseMsg Returns: ParseMsg: The ParseMsg corresponding with this InvalidBlock \"\"\" return ParseMsg ( line_start = self . start_line , line_end = self . end_line , reason = f \" { self . reason } at line { self . invalid_line } .\" , ) ParseMsg ( BaseModel ) pydantic-model \u00b6 ParseMsg defines a single message indicating a significant parse event. Attributes: Name Type Description line_start int The start line of the block to which this ParseMsg refers. line_end int The end line of the block to which this ParseMsg refers. column Optional[Tuple[int, int]] An optional begin and end column to which this ParseMsg refers. reason str A human-readable string detailing the reason of the ParseMsg. format_parsemsg_to_string ( self , file_path : Optional [ pathlib . Path ] = None ) -> str \u00b6 Format string describing this ParseMsg Parameters: Name Type Description Default file_path Optional[Path] The file path mentioned in the message if specified. Defaults to None. None Source code in hydrolib/core/dflowfm/polyfile/parser.py def format_parsemsg_to_string ( self , file_path : Optional [ Path ] = None ) -> str : \"\"\"Format string describing this ParseMsg Args: file_path (Optional[Path], optional): The file path mentioned in the message if specified. Defaults to None. \"\"\" if self . line_start != self . line_end : block_suffix = f \" \\n Invalid block { self . line_start } : { self . line_end } \" else : block_suffix = f \" \\n Invalid line { self . line_start } \" col_suffix = ( f \" \\n Columns { self . column [ 0 ] } : { self . column [ 1 ] } \" if self . column is not None else \"\" ) file_suffix = f \" \\n File: { file_path } \" if file_path is not None else \"\" message = f \" { self . reason }{ block_suffix }{ col_suffix }{ file_suffix } \" return message Parser \u00b6 Parser provides the functionality to parse a polyfile line by line. The Parser parses blocks describing PolyObject instances by relying on a rudimentary state machine. The states are encoded with the StateType. New lines are fed through the feed_line method. After each line the internal state will be updated. When a complete block is read, it will be converted into a PolyObject and stored internally. When finalise is called, the constructed objects, as well as any warnings and errors describing invalid blocks, will be returned. Each state defines a feed_line method, stored in the _feed_line dict, which consumes a line and potentially transitions the state into the next. Each state further defines a finalise method, stored in the _finalise dict, which is called upon finalising the parser. Invalid states are encoded with INVALID_STATE. In this state the Parser attempts to find a new block, and thus looks for a new description or name. Unexpected whitespace before comments, names, and dimensions, as well as empty lines will generate a warning, and will be ignored by the parser. __init__ ( self , file_path : Path , has_z_value : bool = False ) -> None special \u00b6 Create a new Parser Parameters: Name Type Description Default file_path Path Name of the file being parsed, only used for providing proper warnings. required has_z_value bool Whether to interpret the third column as z-coordinates. Defaults to False. False Source code in hydrolib/core/dflowfm/polyfile/parser.py def __init__ ( self , file_path : Path , has_z_value : bool = False ) -> None : \"\"\"Create a new Parser Args: file_path (Path): Name of the file being parsed, only used for providing proper warnings. has_z_value (bool, optional): Whether to interpret the third column as z-coordinates. Defaults to False. \"\"\" self . _has_z_value = has_z_value self . _file_path = file_path self . _line = 0 self . _new_block () self . _error_builder = ErrorBuilder () self . _poly_objects : List [ PolyObject ] = [] self . _current_point : int = 0 self . _feed_line : Dict [ StateType , Callable [[ str ], None ]] = { StateType . NEW_BLOCK : self . _parse_name_or_new_description , StateType . PARSED_DESCRIPTION : self . _parse_name_or_next_description , StateType . PARSED_NAME : self . _parse_dimensions , StateType . PARSING_POINTS : self . _parse_next_point , StateType . INVALID_STATE : self . _parse_name_or_new_description , } self . _finalise : Dict [ StateType , Callable [[], None ]] = { StateType . NEW_BLOCK : self . _noop , StateType . PARSED_DESCRIPTION : self . _add_current_block_as_incomplete_error , StateType . PARSED_NAME : self . _add_current_block_as_incomplete_error , StateType . PARSING_POINTS : self . _add_current_block_as_incomplete_error , StateType . INVALID_STATE : self . _noop , } feed_line ( self , line : str ) -> None \u00b6 Parse the next line with this Parser. Parameters: Name Type Description Default line str The line to parse required Source code in hydrolib/core/dflowfm/polyfile/parser.py def feed_line ( self , line : str ) -> None : \"\"\"Parse the next line with this Parser. Args: line (str): The line to parse \"\"\" if not Parser . _is_empty_line ( line ): self . _feed_line [ self . _state ]( line ) else : self . _handle_empty_line () self . _increment_line () finalize ( self ) -> Sequence [ hydrolib . core . dflowfm . polyfile . models . PolyObject ] \u00b6 Finalize parsing and return the constructed PolyObject. Exceptions: Type Description ValueError When the plifile is invalid. Returns: Type Description PolyObject A PolyObject containing the constructed PolyObject instances. Source code in hydrolib/core/dflowfm/polyfile/parser.py def finalize ( self ) -> Sequence [ PolyObject ]: \"\"\"Finalize parsing and return the constructed PolyObject. Raises: ValueError: When the plifile is invalid. Returns: PolyObject: A PolyObject containing the constructed PolyObject instances. \"\"\" self . _error_builder . end_invalid_block ( self . _line ) last_error_msg = self . _error_builder . finalize_previous_error () if last_error_msg is not None : self . _notify_as_error ( last_error_msg ) self . _finalise [ self . _state ]() return self . _poly_objects StateType ( IntEnum ) \u00b6 The types of state of a Parser. read_polyfile ( filepath : Path , has_z_values : Optional [ bool ] = None ) -> Dict \u00b6 Read the specified file and return the corresponding data. The file is expected to follow the .pli(z) / .pol convention. A .pli(z) or .pol file is defined as consisting of a number of blocks of lines adhering to the following format: Optional description record consisting of one or more lines starting with '*'. These will be ignored. Name consisting of a non-blank character string Two integers, Nr and Nc, representing the numbers of rows and columns respectively Nr number of data points, consisting of Nc floats separated by whitespace For example: ... * * Polyline L008 * L008 4 2 131595.0 549685.0 131750.0 549865.0 131595.0 550025.0 131415.0 550175.0 ... Note that the points can be arbitrarily indented, and the comments are optional. if no has_z_value has been defined, it will be based on the file path extensions of the filepath: - .pliz will default to True - .pli and .pol will default to False Empty lines and unexpected whitespace will be flagged as warnings, and ignored. If invalid syntax is detected within a block, an error will be created. This block will be ignored for the purpose of creating PolyObject instances. Once an error is encountered, any following lines will be marked as part of the invalid block, until a new valid block is found. Note that this means that sequential invalid blocks will be reported as a single invalid block. Such invalid blocks will be reported as warnings. Parameters: Name Type Description Default filepath Path Path to the pli(z)/pol convention structured file. required has_z_values Optional[bool] Whether to create points containing a z-value. Defaults to None. None Exceptions: Type Description ValueError When the plifile is invalid. Returns: Type Description Dict The dictionary describing the data of a PolyObject. Source code in hydrolib/core/dflowfm/polyfile/parser.py def read_polyfile ( filepath : Path , has_z_values : Optional [ bool ] = None ) -> Dict : \"\"\"Read the specified file and return the corresponding data. The file is expected to follow the .pli(z) / .pol convention. A .pli(z) or .pol file is defined as consisting of a number of blocks of lines adhering to the following format: - Optional description record consisting of one or more lines starting with '*'. These will be ignored. - Name consisting of a non-blank character string - Two integers, Nr and Nc, representing the numbers of rows and columns respectively - Nr number of data points, consisting of Nc floats separated by whitespace For example: ``` ... * * Polyline L008 * L008 4 2 131595.0 549685.0 131750.0 549865.0 131595.0 550025.0 131415.0 550175.0 ... ``` Note that the points can be arbitrarily indented, and the comments are optional. if no has_z_value has been defined, it will be based on the file path extensions of the filepath: - .pliz will default to True - .pli and .pol will default to False Empty lines and unexpected whitespace will be flagged as warnings, and ignored. If invalid syntax is detected within a block, an error will be created. This block will be ignored for the purpose of creating PolyObject instances. Once an error is encountered, any following lines will be marked as part of the invalid block, until a new valid block is found. Note that this means that sequential invalid blocks will be reported as a single invalid block. Such invalid blocks will be reported as warnings. Args: filepath: Path to the pli(z)/pol convention structured file. has_z_values: Whether to create points containing a z-value. Defaults to None. Raises: ValueError: When the plifile is invalid. Returns: Dict: The dictionary describing the data of a PolyObject. \"\"\" if has_z_values is None : has_z_values = _determine_has_z_value ( filepath ) parser = Parser ( filepath , has_z_value = has_z_values ) with filepath . open ( \"r\" , encoding = \"utf8\" ) as f : for line in f : parser . feed_line ( line ) objs = parser . finalize () return { \"has_z_values\" : has_z_values , \"objects\" : objs } Serializer \u00b6 Serializer \u00b6 Serializer provides several static serialize methods for the models. serialize_description ( description : Optional [ hydrolib . core . dflowfm . polyfile . models . Description ]) -> Iterable [ str ] staticmethod \u00b6 Serialize the Description to a string which can be used within a polyfile. Returns: Type Description str The serialised equivalent of this Description Source code in hydrolib/core/dflowfm/polyfile/serializer.py @staticmethod def serialize_description ( description : Optional [ Description ]) -> Iterable [ str ]: \"\"\"Serialize the Description to a string which can be used within a polyfile. Returns: str: The serialised equivalent of this Description \"\"\" if description is None : return [] if description . content == \"\" : return [ \"*\" , ] return ( f \"* { v . rstrip () } \" for v in ( description . content + \" \\n \" ) . splitlines ()) serialize_metadata ( metadata : Metadata ) -> Iterable [ str ] staticmethod \u00b6 Serialize this Metadata to a string which can be used within a polyfile. The number of rows and number of columns are separated by four spaces. Returns: Type Description str The serialised equivalent of this Metadata Source code in hydrolib/core/dflowfm/polyfile/serializer.py @staticmethod def serialize_metadata ( metadata : Metadata ) -> Iterable [ str ]: \"\"\"Serialize this Metadata to a string which can be used within a polyfile. The number of rows and number of columns are separated by four spaces. Returns: str: The serialised equivalent of this Metadata \"\"\" return [ metadata . name , f \" { metadata . n_rows } { metadata . n_columns } \" ] serialize_point ( point : Point , config : SerializerConfig ) -> str staticmethod \u00b6 Serialize this Point to a string which can be used within a polyfile. the point data is indented with 4 spaces, and the individual values are separated by 4 spaces as well. Parameters: Name Type Description Default point Point The point to serialize. required config SerializerConfig The serialization configuration. required Returns: Type Description str The serialised equivalent of this Point Source code in hydrolib/core/dflowfm/polyfile/serializer.py @staticmethod def serialize_point ( point : Point , config : SerializerConfig ) -> str : \"\"\"Serialize this Point to a string which can be used within a polyfile. the point data is indented with 4 spaces, and the individual values are separated by 4 spaces as well. Args: point (Point): The point to serialize. config (SerializerConfig): The serialization configuration. Returns: str: The serialised equivalent of this Point \"\"\" space = 4 * \" \" float_format = lambda v : f \" { v :{ config . float_format }} \" return space + space . join ( float_format ( v ) for v in Serializer . _get_point_values ( point ) ) serialize_poly_object ( obj : PolyObject , config : SerializerConfig ) -> Iterable [ str ] staticmethod \u00b6 Serialize this PolyObject to a string which can be used within a polyfile. Parameters: Name Type Description Default obj PolyObject The poly object to serializer. required config SerializerConfig The serialization configuration. required Returns: Type Description str The serialised equivalent of this PolyObject Source code in hydrolib/core/dflowfm/polyfile/serializer.py @staticmethod def serialize_poly_object ( obj : PolyObject , config : SerializerConfig ) -> Iterable [ str ]: \"\"\"Serialize this PolyObject to a string which can be used within a polyfile. Args: obj (PolyObject): The poly object to serializer. config (SerializerConfig): The serialization configuration. Returns: str: The serialised equivalent of this PolyObject \"\"\" description = Serializer . serialize_description ( obj . description ) metadata = Serializer . serialize_metadata ( obj . metadata ) points = [ Serializer . serialize_point ( obj , config ) for obj in obj . points ] return chain ( description , metadata , points ) write_polyfile ( path : Path , data : Sequence [ hydrolib . core . dflowfm . polyfile . models . PolyObject ], config : SerializerConfig ) -> None \u00b6 Write the data to a new file at path Parameters: Name Type Description Default path Path The path to write the data to required data Sequence[PolyObject] The poly objects to write required config SerializerConfig The serialization configuration. required Source code in hydrolib/core/dflowfm/polyfile/serializer.py def write_polyfile ( path : Path , data : Sequence [ PolyObject ], config : SerializerConfig ) -> None : \"\"\"Write the data to a new file at path Args: path (Path): The path to write the data to data (Sequence[PolyObject]): The poly objects to write config (SerializerConfig): The serialization configuration. \"\"\" serialized_poly_objects = [ Serializer . serialize_poly_object ( poly_object , config ) for poly_object in data ] serialized_data = chain . from_iterable ( serialized_poly_objects ) path . parent . mkdir ( parents = True , exist_ok = True ) with path . open ( \"w\" , encoding = \"utf8\" ) as f : for line in serialized_data : f . write ( line ) f . write ( \" \\n \" )","title":"Polyline/polygon files"},{"location":"reference/polyfile/#polylinepolygon-files","text":"Polyline .pli(z) and polygon .pol files are basic spatial input files for a D-Flow FM model to select particular locations, and are used in various other input files. They are represented by the classes below.","title":"Polyline/polygon files"},{"location":"reference/polyfile/#model","text":"models.py defines all classes and functions related to representing pol/pli(z) files.","title":"Model"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.models.Description","text":"Description of a single PolyObject. The Description will be prepended to a block. Each line will start with a '*'. Attributes: Name Type Description content str The content of this Description.","title":"Description"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.models.Metadata","text":"Metadata of a single PolyObject. Attributes: Name Type Description name str The name of the PolyObject n_rows int The number of rows (i.e. Point instances) of the PolyObject n_columns int The total number of values in a Point, including x, y, and z.","title":"Metadata"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.models.Point","text":"Point consisting of a x and y coordinate, an optional z coordinate and data. Attributes: Name Type Description x float The x-coordinate of this Point y float The y-coordinate of this Point z Optional[float] An optional z-coordinate of this Point. data Sequence[float] The additional data variables of this Point.","title":"Point"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.models.PolyFile","text":"Poly-file (.pol/.pli/.pliz) representation.","title":"PolyFile"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.models.PolyObject","text":"PolyObject describing a single block in a poly file. The metadata should be consistent with the points: - The number of points should be equal to number of rows defined in the metadata - The data of each point should be equal to the number of columns defined in the metadata. Attributes: Name Type Description description Optional[Description] An optional description of this PolyObject metadata Metadata The Metadata of this PolObject, describing the structure points List[Point] The points describing this PolyObject, structured according to the Metadata","title":"PolyObject"},{"location":"reference/polyfile/#parser","text":"parser.py defines all classes and functions related to parsing pol/pli(z) files.","title":"Parser"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.Block","text":"Block is a temporary object which will be converted into a PolyObject. The fields are supposed to be set during the lifetime of this object. When all fields are set, finalize can be called. Attributes: Name Type Description start_line int The starting line of this current block. name Optional[str] The name of this block. Defaults to None. dimensions Optional[Tuple[int, int]] The dimensions (n_rows, n_columns) of this Block. Defaults to None. points Optional[List[Point]] The points of this block. Defaults to None. ws_warnings List[ParseMsg] The whitespace warnings associated with this block. Defaults to an empty list. empty_lines List[int] The line numbers of the empty lines. Defaults to an empty list.","title":"Block"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.Block.finalize","text":"Finalise this Block and return the constructed PolyObject and warnings If the metadata or the points are None, then None is returned. Returns: Type Description Optional[Tuple[PolyObject, List[ParseMsg]]] The constructed PolyObject and warnings encountered while parsing it. Source code in hydrolib/core/dflowfm/polyfile/parser.py def finalize ( self ) -> Optional [ Tuple [ PolyObject , List [ ParseMsg ]]]: \"\"\"Finalise this Block and return the constructed PolyObject and warnings If the metadata or the points are None, then None is returned. Returns: Optional[Tuple[PolyObject, List[ParseMsg]]]: The constructed PolyObject and warnings encountered while parsing it. \"\"\" metadata = self . _get_metadata () if metadata is None or self . points is None : return None obj = PolyObject ( description = self . _get_description (), metadata = metadata , points = self . points ) return obj , self . ws_warnings + self . _get_empty_line_warnings ()","title":"finalize()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.ErrorBuilder","text":"ErrorBuilder provides the functionality to the Parser to keep track of errors.","title":"ErrorBuilder"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.ErrorBuilder.__init__","text":"Create a new ErorrorBuilder Source code in hydrolib/core/dflowfm/polyfile/parser.py def __init__ ( self ) -> None : \"\"\"Create a new ErorrorBuilder\"\"\" self . _current_block : Optional [ InvalidBlock ] = None","title":"__init__()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.ErrorBuilder.end_invalid_block","text":"Store the end line of the current block If no invalid block currently exists, nothing will be done. Parameters: Name Type Description Default line int the final line of this invalid block required Source code in hydrolib/core/dflowfm/polyfile/parser.py def end_invalid_block ( self , line : int ) -> None : \"\"\"Store the end line of the current block If no invalid block currently exists, nothing will be done. Args: line (int): the final line of this invalid block \"\"\" if self . _current_block is not None : self . _current_block . end_line = line","title":"end_invalid_block()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.ErrorBuilder.finalize_previous_error","text":"Finalize the current invalid block if it exists If no current invalid block exists, None will be returned, and nothing will change. If a current block exists, it will be converted into a ParseMsg and returned. The current invalid block will be reset. Returns: Type Description Optional[ParseMsg] The corresponding ParseMsg if an InvalidBlock exists. Source code in hydrolib/core/dflowfm/polyfile/parser.py def finalize_previous_error ( self ) -> Optional [ ParseMsg ]: \"\"\"Finalize the current invalid block if it exists If no current invalid block exists, None will be returned, and nothing will change. If a current block exists, it will be converted into a ParseMsg and returned. The current invalid block will be reset. Returns: Optional[ParseMsg]: The corresponding ParseMsg if an InvalidBlock exists. \"\"\" if self . _current_block is not None : msg = self . _current_block . to_msg () self . _current_block = None return msg else : return None","title":"finalize_previous_error()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.ErrorBuilder.start_invalid_block","text":"Start a new invalid block if none exists at the moment If we are already in an invalid block, or the previous one was never finalised, we will not log the reason, and assume it is one long invalid block. Parameters: Name Type Description Default block_start int The start of the invalid block. required invalid_line int The actual offending line number. required reason str The reason why this block is invalid. required Source code in hydrolib/core/dflowfm/polyfile/parser.py def start_invalid_block ( self , block_start : int , invalid_line : int , reason : str ) -> None : \"\"\"Start a new invalid block if none exists at the moment If we are already in an invalid block, or the previous one was never finalised, we will not log the reason, and assume it is one long invalid block. Args: block_start (int): The start of the invalid block. invalid_line (int): The actual offending line number. reason (str): The reason why this block is invalid. \"\"\" if self . _current_block is None : self . _current_block = InvalidBlock ( start_line = block_start , invalid_line = invalid_line , reason = reason )","title":"start_invalid_block()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.InvalidBlock","text":"InvalidBlock is a temporary object which will be converted into a ParseMsg. Attributes: Name Type Description start_line int The start line of this InvalidBlock end_line Optional[int] The end line of this InvalidBlock if it is set. Defaults to None. invalid_line int The line which is causing this block to be invalid. reason str A human-readable string detailing the reason of the ParseMsg.","title":"InvalidBlock"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.InvalidBlock.to_msg","text":"Convert this InvalidBlock to the corresponding ParseMsg Returns: Type Description ParseMsg The ParseMsg corresponding with this InvalidBlock Source code in hydrolib/core/dflowfm/polyfile/parser.py def to_msg ( self ) -> ParseMsg : \"\"\"Convert this InvalidBlock to the corresponding ParseMsg Returns: ParseMsg: The ParseMsg corresponding with this InvalidBlock \"\"\" return ParseMsg ( line_start = self . start_line , line_end = self . end_line , reason = f \" { self . reason } at line { self . invalid_line } .\" , )","title":"to_msg()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.ParseMsg","text":"ParseMsg defines a single message indicating a significant parse event. Attributes: Name Type Description line_start int The start line of the block to which this ParseMsg refers. line_end int The end line of the block to which this ParseMsg refers. column Optional[Tuple[int, int]] An optional begin and end column to which this ParseMsg refers. reason str A human-readable string detailing the reason of the ParseMsg.","title":"ParseMsg"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.ParseMsg.format_parsemsg_to_string","text":"Format string describing this ParseMsg Parameters: Name Type Description Default file_path Optional[Path] The file path mentioned in the message if specified. Defaults to None. None Source code in hydrolib/core/dflowfm/polyfile/parser.py def format_parsemsg_to_string ( self , file_path : Optional [ Path ] = None ) -> str : \"\"\"Format string describing this ParseMsg Args: file_path (Optional[Path], optional): The file path mentioned in the message if specified. Defaults to None. \"\"\" if self . line_start != self . line_end : block_suffix = f \" \\n Invalid block { self . line_start } : { self . line_end } \" else : block_suffix = f \" \\n Invalid line { self . line_start } \" col_suffix = ( f \" \\n Columns { self . column [ 0 ] } : { self . column [ 1 ] } \" if self . column is not None else \"\" ) file_suffix = f \" \\n File: { file_path } \" if file_path is not None else \"\" message = f \" { self . reason }{ block_suffix }{ col_suffix }{ file_suffix } \" return message","title":"format_parsemsg_to_string()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.Parser","text":"Parser provides the functionality to parse a polyfile line by line. The Parser parses blocks describing PolyObject instances by relying on a rudimentary state machine. The states are encoded with the StateType. New lines are fed through the feed_line method. After each line the internal state will be updated. When a complete block is read, it will be converted into a PolyObject and stored internally. When finalise is called, the constructed objects, as well as any warnings and errors describing invalid blocks, will be returned. Each state defines a feed_line method, stored in the _feed_line dict, which consumes a line and potentially transitions the state into the next. Each state further defines a finalise method, stored in the _finalise dict, which is called upon finalising the parser. Invalid states are encoded with INVALID_STATE. In this state the Parser attempts to find a new block, and thus looks for a new description or name. Unexpected whitespace before comments, names, and dimensions, as well as empty lines will generate a warning, and will be ignored by the parser.","title":"Parser"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.Parser.__init__","text":"Create a new Parser Parameters: Name Type Description Default file_path Path Name of the file being parsed, only used for providing proper warnings. required has_z_value bool Whether to interpret the third column as z-coordinates. Defaults to False. False Source code in hydrolib/core/dflowfm/polyfile/parser.py def __init__ ( self , file_path : Path , has_z_value : bool = False ) -> None : \"\"\"Create a new Parser Args: file_path (Path): Name of the file being parsed, only used for providing proper warnings. has_z_value (bool, optional): Whether to interpret the third column as z-coordinates. Defaults to False. \"\"\" self . _has_z_value = has_z_value self . _file_path = file_path self . _line = 0 self . _new_block () self . _error_builder = ErrorBuilder () self . _poly_objects : List [ PolyObject ] = [] self . _current_point : int = 0 self . _feed_line : Dict [ StateType , Callable [[ str ], None ]] = { StateType . NEW_BLOCK : self . _parse_name_or_new_description , StateType . PARSED_DESCRIPTION : self . _parse_name_or_next_description , StateType . PARSED_NAME : self . _parse_dimensions , StateType . PARSING_POINTS : self . _parse_next_point , StateType . INVALID_STATE : self . _parse_name_or_new_description , } self . _finalise : Dict [ StateType , Callable [[], None ]] = { StateType . NEW_BLOCK : self . _noop , StateType . PARSED_DESCRIPTION : self . _add_current_block_as_incomplete_error , StateType . PARSED_NAME : self . _add_current_block_as_incomplete_error , StateType . PARSING_POINTS : self . _add_current_block_as_incomplete_error , StateType . INVALID_STATE : self . _noop , }","title":"__init__()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.Parser.feed_line","text":"Parse the next line with this Parser. Parameters: Name Type Description Default line str The line to parse required Source code in hydrolib/core/dflowfm/polyfile/parser.py def feed_line ( self , line : str ) -> None : \"\"\"Parse the next line with this Parser. Args: line (str): The line to parse \"\"\" if not Parser . _is_empty_line ( line ): self . _feed_line [ self . _state ]( line ) else : self . _handle_empty_line () self . _increment_line ()","title":"feed_line()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.Parser.finalize","text":"Finalize parsing and return the constructed PolyObject. Exceptions: Type Description ValueError When the plifile is invalid. Returns: Type Description PolyObject A PolyObject containing the constructed PolyObject instances. Source code in hydrolib/core/dflowfm/polyfile/parser.py def finalize ( self ) -> Sequence [ PolyObject ]: \"\"\"Finalize parsing and return the constructed PolyObject. Raises: ValueError: When the plifile is invalid. Returns: PolyObject: A PolyObject containing the constructed PolyObject instances. \"\"\" self . _error_builder . end_invalid_block ( self . _line ) last_error_msg = self . _error_builder . finalize_previous_error () if last_error_msg is not None : self . _notify_as_error ( last_error_msg ) self . _finalise [ self . _state ]() return self . _poly_objects","title":"finalize()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.StateType","text":"The types of state of a Parser.","title":"StateType"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.parser.read_polyfile","text":"Read the specified file and return the corresponding data. The file is expected to follow the .pli(z) / .pol convention. A .pli(z) or .pol file is defined as consisting of a number of blocks of lines adhering to the following format: Optional description record consisting of one or more lines starting with '*'. These will be ignored. Name consisting of a non-blank character string Two integers, Nr and Nc, representing the numbers of rows and columns respectively Nr number of data points, consisting of Nc floats separated by whitespace For example: ... * * Polyline L008 * L008 4 2 131595.0 549685.0 131750.0 549865.0 131595.0 550025.0 131415.0 550175.0 ... Note that the points can be arbitrarily indented, and the comments are optional. if no has_z_value has been defined, it will be based on the file path extensions of the filepath: - .pliz will default to True - .pli and .pol will default to False Empty lines and unexpected whitespace will be flagged as warnings, and ignored. If invalid syntax is detected within a block, an error will be created. This block will be ignored for the purpose of creating PolyObject instances. Once an error is encountered, any following lines will be marked as part of the invalid block, until a new valid block is found. Note that this means that sequential invalid blocks will be reported as a single invalid block. Such invalid blocks will be reported as warnings. Parameters: Name Type Description Default filepath Path Path to the pli(z)/pol convention structured file. required has_z_values Optional[bool] Whether to create points containing a z-value. Defaults to None. None Exceptions: Type Description ValueError When the plifile is invalid. Returns: Type Description Dict The dictionary describing the data of a PolyObject. Source code in hydrolib/core/dflowfm/polyfile/parser.py def read_polyfile ( filepath : Path , has_z_values : Optional [ bool ] = None ) -> Dict : \"\"\"Read the specified file and return the corresponding data. The file is expected to follow the .pli(z) / .pol convention. A .pli(z) or .pol file is defined as consisting of a number of blocks of lines adhering to the following format: - Optional description record consisting of one or more lines starting with '*'. These will be ignored. - Name consisting of a non-blank character string - Two integers, Nr and Nc, representing the numbers of rows and columns respectively - Nr number of data points, consisting of Nc floats separated by whitespace For example: ``` ... * * Polyline L008 * L008 4 2 131595.0 549685.0 131750.0 549865.0 131595.0 550025.0 131415.0 550175.0 ... ``` Note that the points can be arbitrarily indented, and the comments are optional. if no has_z_value has been defined, it will be based on the file path extensions of the filepath: - .pliz will default to True - .pli and .pol will default to False Empty lines and unexpected whitespace will be flagged as warnings, and ignored. If invalid syntax is detected within a block, an error will be created. This block will be ignored for the purpose of creating PolyObject instances. Once an error is encountered, any following lines will be marked as part of the invalid block, until a new valid block is found. Note that this means that sequential invalid blocks will be reported as a single invalid block. Such invalid blocks will be reported as warnings. Args: filepath: Path to the pli(z)/pol convention structured file. has_z_values: Whether to create points containing a z-value. Defaults to None. Raises: ValueError: When the plifile is invalid. Returns: Dict: The dictionary describing the data of a PolyObject. \"\"\" if has_z_values is None : has_z_values = _determine_has_z_value ( filepath ) parser = Parser ( filepath , has_z_value = has_z_values ) with filepath . open ( \"r\" , encoding = \"utf8\" ) as f : for line in f : parser . feed_line ( line ) objs = parser . finalize () return { \"has_z_values\" : has_z_values , \"objects\" : objs }","title":"read_polyfile()"},{"location":"reference/polyfile/#serializer","text":"","title":"Serializer"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.serializer.Serializer","text":"Serializer provides several static serialize methods for the models.","title":"Serializer"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.serializer.Serializer.serialize_description","text":"Serialize the Description to a string which can be used within a polyfile. Returns: Type Description str The serialised equivalent of this Description Source code in hydrolib/core/dflowfm/polyfile/serializer.py @staticmethod def serialize_description ( description : Optional [ Description ]) -> Iterable [ str ]: \"\"\"Serialize the Description to a string which can be used within a polyfile. Returns: str: The serialised equivalent of this Description \"\"\" if description is None : return [] if description . content == \"\" : return [ \"*\" , ] return ( f \"* { v . rstrip () } \" for v in ( description . content + \" \\n \" ) . splitlines ())","title":"serialize_description()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.serializer.Serializer.serialize_metadata","text":"Serialize this Metadata to a string which can be used within a polyfile. The number of rows and number of columns are separated by four spaces. Returns: Type Description str The serialised equivalent of this Metadata Source code in hydrolib/core/dflowfm/polyfile/serializer.py @staticmethod def serialize_metadata ( metadata : Metadata ) -> Iterable [ str ]: \"\"\"Serialize this Metadata to a string which can be used within a polyfile. The number of rows and number of columns are separated by four spaces. Returns: str: The serialised equivalent of this Metadata \"\"\" return [ metadata . name , f \" { metadata . n_rows } { metadata . n_columns } \" ]","title":"serialize_metadata()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.serializer.Serializer.serialize_point","text":"Serialize this Point to a string which can be used within a polyfile. the point data is indented with 4 spaces, and the individual values are separated by 4 spaces as well. Parameters: Name Type Description Default point Point The point to serialize. required config SerializerConfig The serialization configuration. required Returns: Type Description str The serialised equivalent of this Point Source code in hydrolib/core/dflowfm/polyfile/serializer.py @staticmethod def serialize_point ( point : Point , config : SerializerConfig ) -> str : \"\"\"Serialize this Point to a string which can be used within a polyfile. the point data is indented with 4 spaces, and the individual values are separated by 4 spaces as well. Args: point (Point): The point to serialize. config (SerializerConfig): The serialization configuration. Returns: str: The serialised equivalent of this Point \"\"\" space = 4 * \" \" float_format = lambda v : f \" { v :{ config . float_format }} \" return space + space . join ( float_format ( v ) for v in Serializer . _get_point_values ( point ) )","title":"serialize_point()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.serializer.Serializer.serialize_poly_object","text":"Serialize this PolyObject to a string which can be used within a polyfile. Parameters: Name Type Description Default obj PolyObject The poly object to serializer. required config SerializerConfig The serialization configuration. required Returns: Type Description str The serialised equivalent of this PolyObject Source code in hydrolib/core/dflowfm/polyfile/serializer.py @staticmethod def serialize_poly_object ( obj : PolyObject , config : SerializerConfig ) -> Iterable [ str ]: \"\"\"Serialize this PolyObject to a string which can be used within a polyfile. Args: obj (PolyObject): The poly object to serializer. config (SerializerConfig): The serialization configuration. Returns: str: The serialised equivalent of this PolyObject \"\"\" description = Serializer . serialize_description ( obj . description ) metadata = Serializer . serialize_metadata ( obj . metadata ) points = [ Serializer . serialize_point ( obj , config ) for obj in obj . points ] return chain ( description , metadata , points )","title":"serialize_poly_object()"},{"location":"reference/polyfile/#hydrolib.core.dflowfm.polyfile.serializer.write_polyfile","text":"Write the data to a new file at path Parameters: Name Type Description Default path Path The path to write the data to required data Sequence[PolyObject] The poly objects to write required config SerializerConfig The serialization configuration. required Source code in hydrolib/core/dflowfm/polyfile/serializer.py def write_polyfile ( path : Path , data : Sequence [ PolyObject ], config : SerializerConfig ) -> None : \"\"\"Write the data to a new file at path Args: path (Path): The path to write the data to data (Sequence[PolyObject]): The poly objects to write config (SerializerConfig): The serialization configuration. \"\"\" serialized_poly_objects = [ Serializer . serialize_poly_object ( poly_object , config ) for poly_object in data ] serialized_data = chain . from_iterable ( serialized_poly_objects ) path . parent . mkdir ( parents = True , exist_ok = True ) with path . open ( \"w\" , encoding = \"utf8\" ) as f : for line in serialized_data : f . write ( line ) f . write ( \" \\n \" )","title":"write_polyfile()"},{"location":"reference/storagenode/","text":"Storage node .ini files \u00b6 The storage node module provides the specific logic for accessing storage node files for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. A storage node .ini file is described by the classes below. Model \u00b6 Interpolation ( str , Enum ) \u00b6 Enum class containing the valid values for the interpolation type as used for a storage area table in StorageNode. NodeType ( str , Enum ) \u00b6 Enum class containing the valid values for the node type as used in StorageNode. StorageNode ( INIBasedModel ) pydantic-model \u00b6 A storage node that is included in the storage node file. All lowercased attributes match with the storage node input as described in UM Sec.C.17 . check_list_length_levels ( values ) classmethod \u00b6 Validates that the length of the levels field is as expected. Source code in hydrolib/core/dflowfm/storagenode/models.py @root_validator ( allow_reuse = True ) def check_list_length_levels ( cls , values ): \"\"\"Validates that the length of the levels field is as expected.\"\"\" return validate_correct_length ( values , \"levels\" , \"storagearea\" , length_name = \"numlevels\" , list_required_with_length = True , ) validate_that_required_fields_are_present_when_not_using_tables ( values : Dict ) -> Dict classmethod \u00b6 Validates that the specified fields are present. Source code in hydrolib/core/dflowfm/storagenode/models.py @root_validator ( allow_reuse = True ) def validate_that_required_fields_are_present_when_not_using_tables ( cls , values : Dict ) -> Dict : \"\"\"Validates that the specified fields are present.\"\"\" return validate_required_fields ( values , \"bedlevel\" , \"area\" , \"streetlevel\" , conditional_field_name = \"usetable\" , conditional_value = False , ) validate_that_required_fields_are_present_when_using_tables ( values : Dict ) -> Dict classmethod \u00b6 Validates that the specified fields are present when the usetable field is also present. Source code in hydrolib/core/dflowfm/storagenode/models.py @root_validator ( allow_reuse = True ) def validate_that_required_fields_are_present_when_using_tables ( cls , values : Dict ) -> Dict : \"\"\"Validates that the specified fields are present when the usetable field is also present.\"\"\" return validate_required_fields ( values , \"numlevels\" , \"levels\" , \"storagearea\" , conditional_field_name = \"usetable\" , conditional_value = True , ) StorageNodeGeneral ( INIGeneral ) pydantic-model \u00b6 The storage node file's [General] section with file meta data. StorageNodeModel ( INIModel ) pydantic-model \u00b6 The overall storage node model that contains the contents of one storage node file. This model is typically referenced under a FMModel .geometry.storagenodefile[..] . Attributes: Name Type Description general StorageNodeGeneral [General] block with file metadata. storagenode List[StorageNode] List of [StorageNode] blocks for all storage nodes. StorageType ( str , Enum ) \u00b6 Enum class containing the valid values for the storage type as used in StorageNode.","title":"Storage node .ini files"},{"location":"reference/storagenode/#storage-node-ini-files","text":"The storage node module provides the specific logic for accessing storage node files for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. A storage node .ini file is described by the classes below.","title":"Storage node .ini files"},{"location":"reference/storagenode/#model","text":"","title":"Model"},{"location":"reference/storagenode/#hydrolib.core.dflowfm.storagenode.models.Interpolation","text":"Enum class containing the valid values for the interpolation type as used for a storage area table in StorageNode.","title":"Interpolation"},{"location":"reference/storagenode/#hydrolib.core.dflowfm.storagenode.models.NodeType","text":"Enum class containing the valid values for the node type as used in StorageNode.","title":"NodeType"},{"location":"reference/storagenode/#hydrolib.core.dflowfm.storagenode.models.StorageNode","text":"A storage node that is included in the storage node file. All lowercased attributes match with the storage node input as described in UM Sec.C.17 .","title":"StorageNode"},{"location":"reference/storagenode/#hydrolib.core.dflowfm.storagenode.models.StorageNode.check_list_length_levels","text":"Validates that the length of the levels field is as expected. Source code in hydrolib/core/dflowfm/storagenode/models.py @root_validator ( allow_reuse = True ) def check_list_length_levels ( cls , values ): \"\"\"Validates that the length of the levels field is as expected.\"\"\" return validate_correct_length ( values , \"levels\" , \"storagearea\" , length_name = \"numlevels\" , list_required_with_length = True , )","title":"check_list_length_levels()"},{"location":"reference/storagenode/#hydrolib.core.dflowfm.storagenode.models.StorageNode.validate_that_required_fields_are_present_when_not_using_tables","text":"Validates that the specified fields are present. Source code in hydrolib/core/dflowfm/storagenode/models.py @root_validator ( allow_reuse = True ) def validate_that_required_fields_are_present_when_not_using_tables ( cls , values : Dict ) -> Dict : \"\"\"Validates that the specified fields are present.\"\"\" return validate_required_fields ( values , \"bedlevel\" , \"area\" , \"streetlevel\" , conditional_field_name = \"usetable\" , conditional_value = False , )","title":"validate_that_required_fields_are_present_when_not_using_tables()"},{"location":"reference/storagenode/#hydrolib.core.dflowfm.storagenode.models.StorageNode.validate_that_required_fields_are_present_when_using_tables","text":"Validates that the specified fields are present when the usetable field is also present. Source code in hydrolib/core/dflowfm/storagenode/models.py @root_validator ( allow_reuse = True ) def validate_that_required_fields_are_present_when_using_tables ( cls , values : Dict ) -> Dict : \"\"\"Validates that the specified fields are present when the usetable field is also present.\"\"\" return validate_required_fields ( values , \"numlevels\" , \"levels\" , \"storagearea\" , conditional_field_name = \"usetable\" , conditional_value = True , )","title":"validate_that_required_fields_are_present_when_using_tables()"},{"location":"reference/storagenode/#hydrolib.core.dflowfm.storagenode.models.StorageNodeGeneral","text":"The storage node file's [General] section with file meta data.","title":"StorageNodeGeneral"},{"location":"reference/storagenode/#hydrolib.core.dflowfm.storagenode.models.StorageNodeModel","text":"The overall storage node model that contains the contents of one storage node file. This model is typically referenced under a FMModel .geometry.storagenodefile[..] . Attributes: Name Type Description general StorageNodeGeneral [General] block with file metadata. storagenode List[StorageNode] List of [StorageNode] blocks for all storage nodes.","title":"StorageNodeModel"},{"location":"reference/storagenode/#hydrolib.core.dflowfm.storagenode.models.StorageType","text":"Enum class containing the valid values for the storage type as used in StorageNode.","title":"StorageType"},{"location":"reference/structure/","text":"Structure .ini files \u00b6 Structure .ini files contain the definition of hydraulic structures for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. A structures.ini file is described by the classes below. Models \u00b6 structure namespace for storing the contents of an FMModel 's structure file. Bridge ( Structure ) pydantic-model \u00b6 Hydraulic structure with type=bridge , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the bridge input as described in UM Sec.C.12.5 . Compound ( Structure ) pydantic-model \u00b6 Hydraulic structure with type=compound , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the compound input as described in UM Sec.C.12.11 . Culvert ( Structure ) pydantic-model \u00b6 Hydraulic structure with type=culvert , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the culvert input as described in UM Sec.C.12.3 . check_list_lengths ( values ) classmethod \u00b6 Validates that the length of the relopening and losscoeff fields are as expected. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def check_list_lengths ( cls , values ): \"\"\"Validates that the length of the relopening and losscoeff fields are as expected.\"\"\" return validate_correct_length ( values , \"relopening\" , \"losscoeff\" , length_name = \"numlosscoeff\" , list_required_with_length = True , ) validate_that_bendlosscoeff_field_is_present_for_invertedsyphons ( values : Dict ) -> Dict classmethod \u00b6 Validates that the bendlosscoeff value is present when dealing with inverted syphons. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def validate_that_bendlosscoeff_field_is_present_for_invertedsyphons ( cls , values : Dict ) -> Dict : \"\"\"Validates that the bendlosscoeff value is present when dealing with inverted syphons.\"\"\" return validate_required_fields ( values , \"bendlosscoeff\" , conditional_field_name = \"subtype\" , conditional_value = CulvertSubType . invertedSiphon , ) validate_that_bendlosscoeff_is_not_provided_for_culverts ( values : Dict ) -> Dict classmethod \u00b6 Validates that the bendlosscoeff field is not provided when the subtype is a culvert. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def validate_that_bendlosscoeff_is_not_provided_for_culverts ( cls , values : Dict ) -> Dict : \"\"\"Validates that the bendlosscoeff field is not provided when the subtype is a culvert.\"\"\" return validate_forbidden_fields ( values , \"bendlosscoeff\" , conditional_field_name = \"subtype\" , conditional_value = CulvertSubType . culvert , ) validate_that_valve_related_fields_are_present_for_culverts_with_valves ( values : Dict ) -> Dict classmethod \u00b6 Validates that valve-related fields are present when there is a valve present. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def validate_that_valve_related_fields_are_present_for_culverts_with_valves ( cls , values : Dict ) -> Dict : \"\"\"Validates that valve-related fields are present when there is a valve present.\"\"\" return validate_required_fields ( values , \"valveopeningheight\" , \"numlosscoeff\" , \"relopening\" , \"losscoeff\" , conditional_field_name = \"valveonoff\" , conditional_value = True , ) CulvertSubType ( str , Enum ) \u00b6 Enum class to store a Culvert 's subType. Dambreak ( Structure ) pydantic-model \u00b6 Hydraulic structure with type=dambreak , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the dambreak input as described in UM Sec.C.12.10 . check_location_dambreak ( values : dict ) -> dict classmethod \u00b6 Verifies whether the location for this structure contains valid values for numCoordinates, xCoordinates and yCoordinates or instead is using a polyline file. Verifies whether de water level location specifications are valid. Parameters: Name Type Description Default values dict Dictionary of validated values to create a Dambreak. required Exceptions: Type Description ValueError When the values dictionary does not contain valid coordinates or polyline file or when the water level location specifications are not valid. Returns: Type Description dict Dictionary of validated values. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator @classmethod def check_location_dambreak ( cls , values : dict ) -> dict : \"\"\" Verifies whether the location for this structure contains valid values for numCoordinates, xCoordinates and yCoordinates or instead is using a polyline file. Verifies whether de water level location specifications are valid. Args: values (dict): Dictionary of validated values to create a Dambreak. Raises: ValueError: When the values dictionary does not contain valid coordinates or polyline file or when the water level location specifications are not valid. Returns: dict: Dictionary of validated values. \"\"\" def _validate_waterlevel_location ( x_key : str , y_key : str , node_key : str ): x_is_given = values . get ( x_key . lower ()) is not None y_is_given = values . get ( y_key . lower ()) is not None node_is_given = values . get ( node_key . lower ()) is not None if ( x_is_given and y_is_given and not node_is_given ) or ( node_is_given and not x_is_given and not y_is_given ): return raise ValueError ( f \"Either ` { node_key } ` should be specified or ` { x_key } ` and ` { y_key } `.\" ) _validate_waterlevel_location ( \"waterLevelUpstreamLocationX\" , \"waterLevelUpstreamLocationY\" , \"waterLevelUpstreamNodeId\" , ) _validate_waterlevel_location ( \"waterLevelDownstreamLocationX\" , \"waterLevelDownstreamLocationY\" , \"waterLevelDownstreamNodeId\" , ) return values validate_algorithm ( value : str ) -> DambreakAlgorithm classmethod \u00b6 Validates the algorithm parameter for the dambreak structure. Parameters: Name Type Description Default value int algorithm value read from the user's input. required Exceptions: Type Description ValueError When the value given is not of type int. ValueError When the value given is not in the range [1,3] Returns: Type Description int Validated value. Source code in hydrolib/core/dflowfm/structure/models.py @validator ( \"algorithm\" , pre = True ) @classmethod def validate_algorithm ( cls , value : str ) -> DambreakAlgorithm : \"\"\" Validates the algorithm parameter for the dambreak structure. Args: value (int): algorithm value read from the user's input. Raises: ValueError: When the value given is not of type int. ValueError: When the value given is not in the range [1,3] Returns: int: Validated value. \"\"\" int_value = - 1 try : int_value = int ( value ) except Exception : raise ValueError ( \"Dambreak algorithm value should be of type int.\" ) if 0 < int_value <= 3 : return DambreakAlgorithm ( int_value ) raise ValueError ( \"Dambreak algorithm value should be 1, 2 or 3.\" ) validate_dambreak_levels_and_widths ( field_value : Union [ hydrolib . core . dflowfm . tim . models . TimModel , hydrolib . core . dflowfm . bc . models . ForcingModel ], values : dict ) -> Union [ hydrolib . core . dflowfm . tim . models . TimModel , hydrolib . core . dflowfm . bc . models . ForcingModel ] classmethod \u00b6 Validates whether a dambreak can be created with the given dambreakLevelsAndWidths property. This property should be given when the algorithm value is 3. Parameters: Name Type Description Default field_value Optional[Union[TimModel, ForcingModel]] Value given for dambreakLevelsAndWidths. required values dict Dictionary of values already validated (assuming algorithm is in it). required Exceptions: Type Description ValueError When algorithm value is not 3 and field_value has a value. Returns: Type Description Optional[Union[TimModel, ForcingModel]] The value given for dambreakLevelsAndwidths. Source code in hydrolib/core/dflowfm/structure/models.py @validator ( \"dambreaklevelsandwidths\" ) @classmethod def validate_dambreak_levels_and_widths ( cls , field_value : Optional [ Union [ TimModel , ForcingModel ]], values : dict ) -> Optional [ Union [ TimModel , ForcingModel ]]: \"\"\" Validates whether a dambreak can be created with the given dambreakLevelsAndWidths property. This property should be given when the algorithm value is 3. Args: field_value (Optional[Union[TimModel, ForcingModel]]): Value given for dambreakLevelsAndWidths. values (dict): Dictionary of values already validated (assuming algorithm is in it). Raises: ValueError: When algorithm value is not 3 and field_value has a value. Returns: Optional[Union[TimModel, ForcingModel]]: The value given for dambreakLevelsAndwidths. \"\"\" # Retrieve the algorithm value (if not found use 0). algorithm_value = values . get ( \"algorithm\" , 0 ) if field_value is not None and algorithm_value != 3 : # dambreakLevelsAndWidths can only be set when algorithm = 3 raise ValueError ( f \"Dambreak field dambreakLevelsAndWidths can only be set when algorithm = 3, current value: { algorithm_value } .\" ) return field_value DambreakAlgorithm ( int , Enum ) \u00b6 An enumeration. FlowDirection ( str , Enum ) \u00b6 Enum class containing the valid values for the allowedFlowDirection attribute in several subclasses of Structure. GateOpeningHorizontalDirection ( str , Enum ) \u00b6 Horizontal opening direction of gate door[s]. GeneralStructure ( Structure ) pydantic-model \u00b6 Hydraulic structure with type=generalStructure , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the orifice input as described in UM Sec.C.12.9 . Orientation ( str , Enum ) \u00b6 Enum class containing the valid values for the orientation attribute in several subclasses of Structure. Orifice ( Structure ) pydantic-model \u00b6 Hydraulic structure with type=orifice , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the orifice input as described in UM Sec.C.12.7 . Pump ( Structure ) pydantic-model \u00b6 Hydraulic structure with type=pump , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the pump input as described in UM Sec.C.12.6 . check_list_lengths_head_and_reductionfactor ( values ) classmethod \u00b6 Validates that the lengths of the head and reductionfactor fields are as expected. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def check_list_lengths_head_and_reductionfactor ( cls , values ): \"\"\"Validates that the lengths of the head and reductionfactor fields are as expected.\"\"\" return validate_correct_length ( values , \"head\" , \"reductionfactor\" , length_name = \"numreductionlevels\" , list_required_with_length = True , ) conditionally_check_list_lengths_deliveryside ( values : Dict ) -> Dict classmethod \u00b6 Validates the length of the delivery side fields, but only if there is a controlside value present in the values and the controlside is not equal to the suctionSide. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def conditionally_check_list_lengths_deliveryside ( cls , values : Dict ) -> Dict : \"\"\" Validates the length of the delivery side fields, but only if there is a controlside value present in the values and the controlside is not equal to the suctionSide. \"\"\" return validate_conditionally ( cls , values , Pump . _check_list_lengths_deliveryside , \"controlside\" , \"suctionSide\" , ne , ) conditionally_check_list_lengths_suctionside ( values : Dict ) -> Dict classmethod \u00b6 Validates the length of the suction side fields, but only if there is a controlside value present in the values and the controlside is not equal to the deliverySide. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def conditionally_check_list_lengths_suctionside ( cls , values : Dict ) -> Dict : \"\"\" Validates the length of the suction side fields, but only if there is a controlside value present in the values and the controlside is not equal to the deliverySide. \"\"\" return validate_conditionally ( cls , values , Pump . _check_list_lengths_suctionside , \"controlside\" , \"deliverySide\" , ne , ) Structure ( INIBasedModel ) pydantic-model \u00b6 check_location ( values : dict ) -> dict classmethod \u00b6 Validates the location of the structure based on the given parameters. For instance, if a branchid is given, then it is expected also the chainage, otherwise numcoordinates xcoordinates and ycoordinates shall be expected. Parameters: Name Type Description Default values dict Dictionary of values validated for the new structure. required Exceptions: Type Description ValueError When branchid or chainage values are not valid (empty strings). ValueError When the number of xcoordinates and ycoordinates do not match numcoordinates. Returns: Type Description dict Dictionary of values validated for the new structure. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator @classmethod def check_location ( cls , values : dict ) -> dict : \"\"\" Validates the location of the structure based on the given parameters. For instance, if a branchid is given, then it is expected also the chainage, otherwise numcoordinates xcoordinates and ycoordinates shall be expected. Args: values (dict): Dictionary of values validated for the new structure. Raises: ValueError: When branchid or chainage values are not valid (empty strings). ValueError: When the number of xcoordinates and ycoordinates do not match numcoordinates. Returns: dict: Dictionary of values validated for the new structure. \"\"\" filtered_values = { k : v for k , v in values . items () if v is not None } structype = filtered_values . get ( \"type\" , \"\" ) . lower () if structype == \"compound\" or issubclass ( cls , ( Compound )): # Compound structure does not require a location specification. return values # Backwards compatibility for old-style polylinefile input field (instead of num/x/yCoordinates): polyline_compatible_structures = dict ( pump = \"Pump\" , dambreak = \"Dambreak\" , gate = \"Gate\" , weir = \"Weir\" , generalstructure = \"GeneralStructure\" , ) polylinefile_in_model = ( structype in polyline_compatible_structures . keys () and filtered_values . get ( \"polylinefile\" ) is not None ) # No branchId+chainage for some structures: only_coordinates_structures = dict ( longculvert = \"LongCulvert\" , dambreak = \"Dambreak\" ) coordinates_in_model = Structure . validate_coordinates_in_model ( filtered_values ) # Error: do not allow both x/y and polyline file: assert not ( polylinefile_in_model and coordinates_in_model ), f \"`Specify location either by `num/x/yCoordinates` or `polylinefile`, but not both.\" # Error: require x/y or polyline file: if ( structype in polyline_compatible_structures . keys () and structype in only_coordinates_structures . keys () ): assert ( coordinates_in_model or polylinefile_in_model ), f \"Specify location either by setting `num/x/yCoordinates` or `polylinefile` fields for a { polyline_compatible_structures [ structype ] } structure.\" # Error: Some structures require coordinates_in_model, but not branchId and chainage. if ( not polylinefile_in_model and structype in only_coordinates_structures . keys () ): assert ( coordinates_in_model ), f \"Specify location by setting `num/x/yCoordinates` for a { only_coordinates_structures [ structype ] } structure.\" # Error: final check: at least one of x/y, branchId+chainage or polyline file must be given branch_and_chainage_in_model = Structure . validate_branch_and_chainage_in_model ( filtered_values ) assert ( branch_and_chainage_in_model or coordinates_in_model or polylinefile_in_model ), \"Specify location either by setting `branchId` and `chainage` or `num/x/yCoordinates` or `polylinefile` fields.\" return values validate ( v ) classmethod \u00b6 Try to initialize subclass based on the type field. This field is compared to each type field of the derived models of Structure . The derived model with an equal structure type will be initialized. Exceptions: Type Description ValueError When the given type is not a known structure type. Source code in hydrolib/core/dflowfm/structure/models.py @classmethod def validate ( cls , v ): \"\"\"Try to initialize subclass based on the `type` field. This field is compared to each `type` field of the derived models of `Structure`. The derived model with an equal structure type will be initialized. Raises: ValueError: When the given type is not a known structure type. \"\"\" # should be replaced by discriminated unions once merged # https://github.com/samuelcolvin/pydantic/pull/2336 if isinstance ( v , dict ): for c in cls . __subclasses__ (): if ( c . __fields__ . get ( \"type\" ) . default . lower () == v . get ( \"type\" , \"\" ) . lower () ): v = c ( ** v ) break else : raise ValueError ( f \"Type of { cls . __name__ } with id= { v . get ( 'id' , '' ) } and type= { v . get ( 'type' , '' ) } is not recognized.\" ) return super () . validate ( v ) validate_branch_and_chainage_in_model ( values : dict ) -> bool staticmethod \u00b6 Static method to validate whether the given branchid and chainage values match the expectation of a new structure. Parameters: Name Type Description Default values dict Dictionary of values to be used to generate a structure. required Exceptions: Type Description ValueError When the value for branchid or chainage are not valid. Returns: Type Description bool Result of valid branchid / chainage in dictionary. Source code in hydrolib/core/dflowfm/structure/models.py @staticmethod def validate_branch_and_chainage_in_model ( values : dict ) -> bool : \"\"\" Static method to validate whether the given branchid and chainage values match the expectation of a new structure. Args: values (dict): Dictionary of values to be used to generate a structure. Raises: ValueError: When the value for branchid or chainage are not valid. Returns: bool: Result of valid branchid / chainage in dictionary. \"\"\" branchid = values . get ( \"branchid\" , None ) if branchid is None : return False chainage = values . get ( \"chainage\" , None ) if str_is_empty_or_none ( branchid ) or chainage is None : raise ValueError ( \"A valid value for branchId and chainage is required when branchId key is specified.\" ) return True validate_coordinates_in_model ( values : dict ) -> bool staticmethod \u00b6 Static method to validate whether the given values match the expectations of a structure to define its coordinates. Parameters: Name Type Description Default values dict Dictionary of values to be used to generate a structure. required Exceptions: Type Description ValueError When the given coordinates is less than 2. ValueError When the given coordinates do not match in expected size. Returns: Type Description bool Result of valid coordinates in dictionary. Source code in hydrolib/core/dflowfm/structure/models.py @staticmethod def validate_coordinates_in_model ( values : dict ) -> bool : \"\"\" Static method to validate whether the given values match the expectations of a structure to define its coordinates. Args: values (dict): Dictionary of values to be used to generate a structure. Raises: ValueError: When the given coordinates is less than 2. ValueError: When the given coordinates do not match in expected size. Returns: bool: Result of valid coordinates in dictionary. \"\"\" searched_keys = [ \"numcoordinates\" , \"xcoordinates\" , \"ycoordinates\" ] if any ( values . get ( k , None ) is None for k in searched_keys ): return False n_coords = values [ \"numcoordinates\" ] if n_coords < 2 : raise ValueError ( f \"Expected at least 2 coordinates, but only { n_coords } declared.\" ) def get_coord_len ( coord : str ) -> int : if values [ coord ] is None : return 0 return len ( values [ coord ]) len_x_coords = get_coord_len ( \"xcoordinates\" ) len_y_coords = get_coord_len ( \"ycoordinates\" ) if n_coords == len_x_coords == len_y_coords : return True raise ValueError ( f \"Expected { n_coords } coordinates, given { len_x_coords } for xCoordinates and { len_y_coords } for yCoordinates.\" ) StructureGeneral ( INIGeneral ) pydantic-model \u00b6 [General] section with structure file metadata. StructureModel ( INIModel ) pydantic-model \u00b6 The overall structure model that contains the contents of one structure file. This model is typically referenced under a FMModel .geometry.structurefile[..] . Attributes: Name Type Description general StructureGeneral [General] block with file metadata. branch List[Structure] List of [Structure] blocks for all hydraulic structures. UniversalWeir ( Structure ) pydantic-model \u00b6 Hydraulic structure with type=universalWeir , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the universal weir input as described in UM Sec.C.12.2 . Weir ( Structure ) pydantic-model \u00b6 Hydraulic structure with type=weir , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the weir input as described in UM Sec.C.12.1 .","title":"Structure .ini files"},{"location":"reference/structure/#structure-ini-files","text":"Structure .ini files contain the definition of hydraulic structures for a D-Flow FM model. Generic parsing and serializing functionality comes from the generic hydrolib.core.dflowfm.ini modules. A structures.ini file is described by the classes below.","title":"Structure .ini files"},{"location":"reference/structure/#models","text":"structure namespace for storing the contents of an FMModel 's structure file.","title":"Models"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Bridge","text":"Hydraulic structure with type=bridge , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the bridge input as described in UM Sec.C.12.5 .","title":"Bridge"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Compound","text":"Hydraulic structure with type=compound , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the compound input as described in UM Sec.C.12.11 .","title":"Compound"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Culvert","text":"Hydraulic structure with type=culvert , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the culvert input as described in UM Sec.C.12.3 .","title":"Culvert"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Culvert.check_list_lengths","text":"Validates that the length of the relopening and losscoeff fields are as expected. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def check_list_lengths ( cls , values ): \"\"\"Validates that the length of the relopening and losscoeff fields are as expected.\"\"\" return validate_correct_length ( values , \"relopening\" , \"losscoeff\" , length_name = \"numlosscoeff\" , list_required_with_length = True , )","title":"check_list_lengths()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Culvert.validate_that_bendlosscoeff_field_is_present_for_invertedsyphons","text":"Validates that the bendlosscoeff value is present when dealing with inverted syphons. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def validate_that_bendlosscoeff_field_is_present_for_invertedsyphons ( cls , values : Dict ) -> Dict : \"\"\"Validates that the bendlosscoeff value is present when dealing with inverted syphons.\"\"\" return validate_required_fields ( values , \"bendlosscoeff\" , conditional_field_name = \"subtype\" , conditional_value = CulvertSubType . invertedSiphon , )","title":"validate_that_bendlosscoeff_field_is_present_for_invertedsyphons()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Culvert.validate_that_bendlosscoeff_is_not_provided_for_culverts","text":"Validates that the bendlosscoeff field is not provided when the subtype is a culvert. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def validate_that_bendlosscoeff_is_not_provided_for_culverts ( cls , values : Dict ) -> Dict : \"\"\"Validates that the bendlosscoeff field is not provided when the subtype is a culvert.\"\"\" return validate_forbidden_fields ( values , \"bendlosscoeff\" , conditional_field_name = \"subtype\" , conditional_value = CulvertSubType . culvert , )","title":"validate_that_bendlosscoeff_is_not_provided_for_culverts()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Culvert.validate_that_valve_related_fields_are_present_for_culverts_with_valves","text":"Validates that valve-related fields are present when there is a valve present. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def validate_that_valve_related_fields_are_present_for_culverts_with_valves ( cls , values : Dict ) -> Dict : \"\"\"Validates that valve-related fields are present when there is a valve present.\"\"\" return validate_required_fields ( values , \"valveopeningheight\" , \"numlosscoeff\" , \"relopening\" , \"losscoeff\" , conditional_field_name = \"valveonoff\" , conditional_value = True , )","title":"validate_that_valve_related_fields_are_present_for_culverts_with_valves()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.CulvertSubType","text":"Enum class to store a Culvert 's subType.","title":"CulvertSubType"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Dambreak","text":"Hydraulic structure with type=dambreak , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the dambreak input as described in UM Sec.C.12.10 .","title":"Dambreak"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Dambreak.check_location_dambreak","text":"Verifies whether the location for this structure contains valid values for numCoordinates, xCoordinates and yCoordinates or instead is using a polyline file. Verifies whether de water level location specifications are valid. Parameters: Name Type Description Default values dict Dictionary of validated values to create a Dambreak. required Exceptions: Type Description ValueError When the values dictionary does not contain valid coordinates or polyline file or when the water level location specifications are not valid. Returns: Type Description dict Dictionary of validated values. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator @classmethod def check_location_dambreak ( cls , values : dict ) -> dict : \"\"\" Verifies whether the location for this structure contains valid values for numCoordinates, xCoordinates and yCoordinates or instead is using a polyline file. Verifies whether de water level location specifications are valid. Args: values (dict): Dictionary of validated values to create a Dambreak. Raises: ValueError: When the values dictionary does not contain valid coordinates or polyline file or when the water level location specifications are not valid. Returns: dict: Dictionary of validated values. \"\"\" def _validate_waterlevel_location ( x_key : str , y_key : str , node_key : str ): x_is_given = values . get ( x_key . lower ()) is not None y_is_given = values . get ( y_key . lower ()) is not None node_is_given = values . get ( node_key . lower ()) is not None if ( x_is_given and y_is_given and not node_is_given ) or ( node_is_given and not x_is_given and not y_is_given ): return raise ValueError ( f \"Either ` { node_key } ` should be specified or ` { x_key } ` and ` { y_key } `.\" ) _validate_waterlevel_location ( \"waterLevelUpstreamLocationX\" , \"waterLevelUpstreamLocationY\" , \"waterLevelUpstreamNodeId\" , ) _validate_waterlevel_location ( \"waterLevelDownstreamLocationX\" , \"waterLevelDownstreamLocationY\" , \"waterLevelDownstreamNodeId\" , ) return values","title":"check_location_dambreak()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Dambreak.validate_algorithm","text":"Validates the algorithm parameter for the dambreak structure. Parameters: Name Type Description Default value int algorithm value read from the user's input. required Exceptions: Type Description ValueError When the value given is not of type int. ValueError When the value given is not in the range [1,3] Returns: Type Description int Validated value. Source code in hydrolib/core/dflowfm/structure/models.py @validator ( \"algorithm\" , pre = True ) @classmethod def validate_algorithm ( cls , value : str ) -> DambreakAlgorithm : \"\"\" Validates the algorithm parameter for the dambreak structure. Args: value (int): algorithm value read from the user's input. Raises: ValueError: When the value given is not of type int. ValueError: When the value given is not in the range [1,3] Returns: int: Validated value. \"\"\" int_value = - 1 try : int_value = int ( value ) except Exception : raise ValueError ( \"Dambreak algorithm value should be of type int.\" ) if 0 < int_value <= 3 : return DambreakAlgorithm ( int_value ) raise ValueError ( \"Dambreak algorithm value should be 1, 2 or 3.\" )","title":"validate_algorithm()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Dambreak.validate_dambreak_levels_and_widths","text":"Validates whether a dambreak can be created with the given dambreakLevelsAndWidths property. This property should be given when the algorithm value is 3. Parameters: Name Type Description Default field_value Optional[Union[TimModel, ForcingModel]] Value given for dambreakLevelsAndWidths. required values dict Dictionary of values already validated (assuming algorithm is in it). required Exceptions: Type Description ValueError When algorithm value is not 3 and field_value has a value. Returns: Type Description Optional[Union[TimModel, ForcingModel]] The value given for dambreakLevelsAndwidths. Source code in hydrolib/core/dflowfm/structure/models.py @validator ( \"dambreaklevelsandwidths\" ) @classmethod def validate_dambreak_levels_and_widths ( cls , field_value : Optional [ Union [ TimModel , ForcingModel ]], values : dict ) -> Optional [ Union [ TimModel , ForcingModel ]]: \"\"\" Validates whether a dambreak can be created with the given dambreakLevelsAndWidths property. This property should be given when the algorithm value is 3. Args: field_value (Optional[Union[TimModel, ForcingModel]]): Value given for dambreakLevelsAndWidths. values (dict): Dictionary of values already validated (assuming algorithm is in it). Raises: ValueError: When algorithm value is not 3 and field_value has a value. Returns: Optional[Union[TimModel, ForcingModel]]: The value given for dambreakLevelsAndwidths. \"\"\" # Retrieve the algorithm value (if not found use 0). algorithm_value = values . get ( \"algorithm\" , 0 ) if field_value is not None and algorithm_value != 3 : # dambreakLevelsAndWidths can only be set when algorithm = 3 raise ValueError ( f \"Dambreak field dambreakLevelsAndWidths can only be set when algorithm = 3, current value: { algorithm_value } .\" ) return field_value","title":"validate_dambreak_levels_and_widths()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.DambreakAlgorithm","text":"An enumeration.","title":"DambreakAlgorithm"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.FlowDirection","text":"Enum class containing the valid values for the allowedFlowDirection attribute in several subclasses of Structure.","title":"FlowDirection"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.GateOpeningHorizontalDirection","text":"Horizontal opening direction of gate door[s].","title":"GateOpeningHorizontalDirection"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.GeneralStructure","text":"Hydraulic structure with type=generalStructure , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the orifice input as described in UM Sec.C.12.9 .","title":"GeneralStructure"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Orientation","text":"Enum class containing the valid values for the orientation attribute in several subclasses of Structure.","title":"Orientation"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Orifice","text":"Hydraulic structure with type=orifice , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the orifice input as described in UM Sec.C.12.7 .","title":"Orifice"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Pump","text":"Hydraulic structure with type=pump , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the pump input as described in UM Sec.C.12.6 .","title":"Pump"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Pump.check_list_lengths_head_and_reductionfactor","text":"Validates that the lengths of the head and reductionfactor fields are as expected. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def check_list_lengths_head_and_reductionfactor ( cls , values ): \"\"\"Validates that the lengths of the head and reductionfactor fields are as expected.\"\"\" return validate_correct_length ( values , \"head\" , \"reductionfactor\" , length_name = \"numreductionlevels\" , list_required_with_length = True , )","title":"check_list_lengths_head_and_reductionfactor()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Pump.conditionally_check_list_lengths_deliveryside","text":"Validates the length of the delivery side fields, but only if there is a controlside value present in the values and the controlside is not equal to the suctionSide. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def conditionally_check_list_lengths_deliveryside ( cls , values : Dict ) -> Dict : \"\"\" Validates the length of the delivery side fields, but only if there is a controlside value present in the values and the controlside is not equal to the suctionSide. \"\"\" return validate_conditionally ( cls , values , Pump . _check_list_lengths_deliveryside , \"controlside\" , \"suctionSide\" , ne , )","title":"conditionally_check_list_lengths_deliveryside()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Pump.conditionally_check_list_lengths_suctionside","text":"Validates the length of the suction side fields, but only if there is a controlside value present in the values and the controlside is not equal to the deliverySide. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator ( allow_reuse = True ) def conditionally_check_list_lengths_suctionside ( cls , values : Dict ) -> Dict : \"\"\" Validates the length of the suction side fields, but only if there is a controlside value present in the values and the controlside is not equal to the deliverySide. \"\"\" return validate_conditionally ( cls , values , Pump . _check_list_lengths_suctionside , \"controlside\" , \"deliverySide\" , ne , )","title":"conditionally_check_list_lengths_suctionside()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Structure","text":"","title":"Structure"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Structure.check_location","text":"Validates the location of the structure based on the given parameters. For instance, if a branchid is given, then it is expected also the chainage, otherwise numcoordinates xcoordinates and ycoordinates shall be expected. Parameters: Name Type Description Default values dict Dictionary of values validated for the new structure. required Exceptions: Type Description ValueError When branchid or chainage values are not valid (empty strings). ValueError When the number of xcoordinates and ycoordinates do not match numcoordinates. Returns: Type Description dict Dictionary of values validated for the new structure. Source code in hydrolib/core/dflowfm/structure/models.py @root_validator @classmethod def check_location ( cls , values : dict ) -> dict : \"\"\" Validates the location of the structure based on the given parameters. For instance, if a branchid is given, then it is expected also the chainage, otherwise numcoordinates xcoordinates and ycoordinates shall be expected. Args: values (dict): Dictionary of values validated for the new structure. Raises: ValueError: When branchid or chainage values are not valid (empty strings). ValueError: When the number of xcoordinates and ycoordinates do not match numcoordinates. Returns: dict: Dictionary of values validated for the new structure. \"\"\" filtered_values = { k : v for k , v in values . items () if v is not None } structype = filtered_values . get ( \"type\" , \"\" ) . lower () if structype == \"compound\" or issubclass ( cls , ( Compound )): # Compound structure does not require a location specification. return values # Backwards compatibility for old-style polylinefile input field (instead of num/x/yCoordinates): polyline_compatible_structures = dict ( pump = \"Pump\" , dambreak = \"Dambreak\" , gate = \"Gate\" , weir = \"Weir\" , generalstructure = \"GeneralStructure\" , ) polylinefile_in_model = ( structype in polyline_compatible_structures . keys () and filtered_values . get ( \"polylinefile\" ) is not None ) # No branchId+chainage for some structures: only_coordinates_structures = dict ( longculvert = \"LongCulvert\" , dambreak = \"Dambreak\" ) coordinates_in_model = Structure . validate_coordinates_in_model ( filtered_values ) # Error: do not allow both x/y and polyline file: assert not ( polylinefile_in_model and coordinates_in_model ), f \"`Specify location either by `num/x/yCoordinates` or `polylinefile`, but not both.\" # Error: require x/y or polyline file: if ( structype in polyline_compatible_structures . keys () and structype in only_coordinates_structures . keys () ): assert ( coordinates_in_model or polylinefile_in_model ), f \"Specify location either by setting `num/x/yCoordinates` or `polylinefile` fields for a { polyline_compatible_structures [ structype ] } structure.\" # Error: Some structures require coordinates_in_model, but not branchId and chainage. if ( not polylinefile_in_model and structype in only_coordinates_structures . keys () ): assert ( coordinates_in_model ), f \"Specify location by setting `num/x/yCoordinates` for a { only_coordinates_structures [ structype ] } structure.\" # Error: final check: at least one of x/y, branchId+chainage or polyline file must be given branch_and_chainage_in_model = Structure . validate_branch_and_chainage_in_model ( filtered_values ) assert ( branch_and_chainage_in_model or coordinates_in_model or polylinefile_in_model ), \"Specify location either by setting `branchId` and `chainage` or `num/x/yCoordinates` or `polylinefile` fields.\" return values","title":"check_location()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Structure.validate","text":"Try to initialize subclass based on the type field. This field is compared to each type field of the derived models of Structure . The derived model with an equal structure type will be initialized. Exceptions: Type Description ValueError When the given type is not a known structure type. Source code in hydrolib/core/dflowfm/structure/models.py @classmethod def validate ( cls , v ): \"\"\"Try to initialize subclass based on the `type` field. This field is compared to each `type` field of the derived models of `Structure`. The derived model with an equal structure type will be initialized. Raises: ValueError: When the given type is not a known structure type. \"\"\" # should be replaced by discriminated unions once merged # https://github.com/samuelcolvin/pydantic/pull/2336 if isinstance ( v , dict ): for c in cls . __subclasses__ (): if ( c . __fields__ . get ( \"type\" ) . default . lower () == v . get ( \"type\" , \"\" ) . lower () ): v = c ( ** v ) break else : raise ValueError ( f \"Type of { cls . __name__ } with id= { v . get ( 'id' , '' ) } and type= { v . get ( 'type' , '' ) } is not recognized.\" ) return super () . validate ( v )","title":"validate()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Structure.validate_branch_and_chainage_in_model","text":"Static method to validate whether the given branchid and chainage values match the expectation of a new structure. Parameters: Name Type Description Default values dict Dictionary of values to be used to generate a structure. required Exceptions: Type Description ValueError When the value for branchid or chainage are not valid. Returns: Type Description bool Result of valid branchid / chainage in dictionary. Source code in hydrolib/core/dflowfm/structure/models.py @staticmethod def validate_branch_and_chainage_in_model ( values : dict ) -> bool : \"\"\" Static method to validate whether the given branchid and chainage values match the expectation of a new structure. Args: values (dict): Dictionary of values to be used to generate a structure. Raises: ValueError: When the value for branchid or chainage are not valid. Returns: bool: Result of valid branchid / chainage in dictionary. \"\"\" branchid = values . get ( \"branchid\" , None ) if branchid is None : return False chainage = values . get ( \"chainage\" , None ) if str_is_empty_or_none ( branchid ) or chainage is None : raise ValueError ( \"A valid value for branchId and chainage is required when branchId key is specified.\" ) return True","title":"validate_branch_and_chainage_in_model()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Structure.validate_coordinates_in_model","text":"Static method to validate whether the given values match the expectations of a structure to define its coordinates. Parameters: Name Type Description Default values dict Dictionary of values to be used to generate a structure. required Exceptions: Type Description ValueError When the given coordinates is less than 2. ValueError When the given coordinates do not match in expected size. Returns: Type Description bool Result of valid coordinates in dictionary. Source code in hydrolib/core/dflowfm/structure/models.py @staticmethod def validate_coordinates_in_model ( values : dict ) -> bool : \"\"\" Static method to validate whether the given values match the expectations of a structure to define its coordinates. Args: values (dict): Dictionary of values to be used to generate a structure. Raises: ValueError: When the given coordinates is less than 2. ValueError: When the given coordinates do not match in expected size. Returns: bool: Result of valid coordinates in dictionary. \"\"\" searched_keys = [ \"numcoordinates\" , \"xcoordinates\" , \"ycoordinates\" ] if any ( values . get ( k , None ) is None for k in searched_keys ): return False n_coords = values [ \"numcoordinates\" ] if n_coords < 2 : raise ValueError ( f \"Expected at least 2 coordinates, but only { n_coords } declared.\" ) def get_coord_len ( coord : str ) -> int : if values [ coord ] is None : return 0 return len ( values [ coord ]) len_x_coords = get_coord_len ( \"xcoordinates\" ) len_y_coords = get_coord_len ( \"ycoordinates\" ) if n_coords == len_x_coords == len_y_coords : return True raise ValueError ( f \"Expected { n_coords } coordinates, given { len_x_coords } for xCoordinates and { len_y_coords } for yCoordinates.\" )","title":"validate_coordinates_in_model()"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.StructureGeneral","text":"[General] section with structure file metadata.","title":"StructureGeneral"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.StructureModel","text":"The overall structure model that contains the contents of one structure file. This model is typically referenced under a FMModel .geometry.structurefile[..] . Attributes: Name Type Description general StructureGeneral [General] block with file metadata. branch List[Structure] List of [Structure] blocks for all hydraulic structures.","title":"StructureModel"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.UniversalWeir","text":"Hydraulic structure with type=universalWeir , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the universal weir input as described in UM Sec.C.12.2 .","title":"UniversalWeir"},{"location":"reference/structure/#hydrolib.core.dflowfm.structure.models.Weir","text":"Hydraulic structure with type=weir , to be included in a structure file. Typically inside the structure list of a FMModel .geometry.structurefile[0].structure[..] All lowercased attributes match with the weir input as described in UM Sec.C.12.1 .","title":"Weir"},{"location":"reference/tim/","text":"Timeseries .tim files \u00b6 .tim files contain time series data of a D-Flow FM model. The support of .tim files for boundary time series will be discontinued. Instead, these will be replaced by the *.bc file . They are represented by the classes below. Model \u00b6 TimModel ( ParsableFileModel ) pydantic-model \u00b6 Class representing a tim (*.tim) file. TimRecord ( BaseModel ) pydantic-model \u00b6 Single tim record, representing a time and a list of data. Parser \u00b6 TimParser \u00b6 A parser for .tim files. Full line comments at the start of the file are supported. Comment lines start with either a * or a # . No other comments are supported. parse ( filepath : Path ) -> Dict [ str , List [ Any ]] staticmethod \u00b6 Parse a .tim file into a dictionary with comments and time series data. Parameters: Name Type Description Default filepath Path Path to the .tim file to be parsed. required Returns: Type Description Dict[str, List[Any]] A dictionary with keys \"comments\" and \"timeseries\". - \"comments\" represents comments found at the start of the file. - \"timeseries\" is a list of dictionaries with the key as \"time\" and values as \"data\". - \"time\" is a time as a string. - \"data\" is data as a list of strings. Exceptions: Type Description ValueError If the file contains a comment that is not at the start of the file. ValueError If the data of the timeseries is empty. Source code in hydrolib/core/dflowfm/tim/parser.py @staticmethod def parse ( filepath : Path ) -> Dict [ str , List [ Any ]]: \"\"\"Parse a .tim file into a dictionary with comments and time series data. Args: filepath (Path): Path to the .tim file to be parsed. Returns: Dict[str, List[Any]]: A dictionary with keys \"comments\" and \"timeseries\". - \"comments\" represents comments found at the start of the file. - \"timeseries\" is a list of dictionaries with the key as \"time\" and values as \"data\". - \"time\" is a time as a string. - \"data\" is data as a list of strings. Raises: ValueError: If the file contains a comment that is not at the start of the file. ValueError: If the data of the timeseries is empty. \"\"\" comments : List [ str ] = [] timeseries : List [ TimData ] = [] with filepath . open ( encoding = \"utf8\" ) as file : lines = file . readlines () comments , start_timeseries_index = TimParser . _read_header_comments ( lines ) timeseries = TimParser . _read_time_series_data ( lines , start_timeseries_index ) return { \"comments\" : comments , \"timeseries\" : timeseries } Serializer \u00b6 TimSerializer \u00b6 serialize ( path : Path , data : Dict [ str , List [ Any ]], config : TimSerializerConfig , save_settings : ModelSaveSettings ) -> None staticmethod \u00b6 Serialize timeseries data to a file in .tim format. Parameters: Name Type Description Default path Path The path to the destination .tim file. required data Dict[str, List[Any]] A dictionary with keys \"comments\" and \"timeseries\". required config TimSerializerConfig The serialization configuration settings. required save_settings ModelSaveSettings The save settings to be used. required Source code in hydrolib/core/dflowfm/tim/serializer.py @staticmethod def serialize ( path : Path , data : Dict [ str , List [ Any ]], config : TimSerializerConfig , save_settings : ModelSaveSettings , ) -> None : \"\"\" Serialize timeseries data to a file in .tim format. Args: path (Path): The path to the destination .tim file. data (Dict[str, List[Any]]): A dictionary with keys \"comments\" and \"timeseries\". - \"comments\" represents comments found at the start of the file. - \"timeseries\" is a list of dictionaries with the key as \"time\" and values as \"data\". - \"time\" is a time as a string. - \"data\" is data as a list of strings. config (TimSerializerConfig): The serialization configuration settings. save_settings (ModelSaveSettings): The save settings to be used. \"\"\" path . parent . mkdir ( parents = True , exist_ok = True ) commentlines = TimSerializer . _serialize_comment_lines ( data ) timeserieslines = TimSerializer . _serialize_timeseries_lines ( data , config ) file_content = TimSerializer . _serialize_file_content ( timeserieslines , commentlines ) with path . open ( \"w\" , encoding = \"utf8\" ) as file : file . write ( file_content ) TimSerializerConfig ( SerializerConfig ) pydantic-model \u00b6 Configuration settings for the TimSerializer.","title":"Timeseries .tim files"},{"location":"reference/tim/#timeseries-tim-files","text":".tim files contain time series data of a D-Flow FM model. The support of .tim files for boundary time series will be discontinued. Instead, these will be replaced by the *.bc file . They are represented by the classes below.","title":"Timeseries .tim files"},{"location":"reference/tim/#model","text":"","title":"Model"},{"location":"reference/tim/#hydrolib.core.dflowfm.tim.models.TimModel","text":"Class representing a tim (*.tim) file.","title":"TimModel"},{"location":"reference/tim/#hydrolib.core.dflowfm.tim.models.TimRecord","text":"Single tim record, representing a time and a list of data.","title":"TimRecord"},{"location":"reference/tim/#parser","text":"","title":"Parser"},{"location":"reference/tim/#hydrolib.core.dflowfm.tim.parser.TimParser","text":"A parser for .tim files. Full line comments at the start of the file are supported. Comment lines start with either a * or a # . No other comments are supported.","title":"TimParser"},{"location":"reference/tim/#hydrolib.core.dflowfm.tim.parser.TimParser.parse","text":"Parse a .tim file into a dictionary with comments and time series data. Parameters: Name Type Description Default filepath Path Path to the .tim file to be parsed. required Returns: Type Description Dict[str, List[Any]] A dictionary with keys \"comments\" and \"timeseries\". - \"comments\" represents comments found at the start of the file. - \"timeseries\" is a list of dictionaries with the key as \"time\" and values as \"data\". - \"time\" is a time as a string. - \"data\" is data as a list of strings. Exceptions: Type Description ValueError If the file contains a comment that is not at the start of the file. ValueError If the data of the timeseries is empty. Source code in hydrolib/core/dflowfm/tim/parser.py @staticmethod def parse ( filepath : Path ) -> Dict [ str , List [ Any ]]: \"\"\"Parse a .tim file into a dictionary with comments and time series data. Args: filepath (Path): Path to the .tim file to be parsed. Returns: Dict[str, List[Any]]: A dictionary with keys \"comments\" and \"timeseries\". - \"comments\" represents comments found at the start of the file. - \"timeseries\" is a list of dictionaries with the key as \"time\" and values as \"data\". - \"time\" is a time as a string. - \"data\" is data as a list of strings. Raises: ValueError: If the file contains a comment that is not at the start of the file. ValueError: If the data of the timeseries is empty. \"\"\" comments : List [ str ] = [] timeseries : List [ TimData ] = [] with filepath . open ( encoding = \"utf8\" ) as file : lines = file . readlines () comments , start_timeseries_index = TimParser . _read_header_comments ( lines ) timeseries = TimParser . _read_time_series_data ( lines , start_timeseries_index ) return { \"comments\" : comments , \"timeseries\" : timeseries }","title":"parse()"},{"location":"reference/tim/#serializer","text":"","title":"Serializer"},{"location":"reference/tim/#hydrolib.core.dflowfm.tim.serializer.TimSerializer","text":"","title":"TimSerializer"},{"location":"reference/tim/#hydrolib.core.dflowfm.tim.serializer.TimSerializer.serialize","text":"Serialize timeseries data to a file in .tim format. Parameters: Name Type Description Default path Path The path to the destination .tim file. required data Dict[str, List[Any]] A dictionary with keys \"comments\" and \"timeseries\". required config TimSerializerConfig The serialization configuration settings. required save_settings ModelSaveSettings The save settings to be used. required Source code in hydrolib/core/dflowfm/tim/serializer.py @staticmethod def serialize ( path : Path , data : Dict [ str , List [ Any ]], config : TimSerializerConfig , save_settings : ModelSaveSettings , ) -> None : \"\"\" Serialize timeseries data to a file in .tim format. Args: path (Path): The path to the destination .tim file. data (Dict[str, List[Any]]): A dictionary with keys \"comments\" and \"timeseries\". - \"comments\" represents comments found at the start of the file. - \"timeseries\" is a list of dictionaries with the key as \"time\" and values as \"data\". - \"time\" is a time as a string. - \"data\" is data as a list of strings. config (TimSerializerConfig): The serialization configuration settings. save_settings (ModelSaveSettings): The save settings to be used. \"\"\" path . parent . mkdir ( parents = True , exist_ok = True ) commentlines = TimSerializer . _serialize_comment_lines ( data ) timeserieslines = TimSerializer . _serialize_timeseries_lines ( data , config ) file_content = TimSerializer . _serialize_file_content ( timeserieslines , commentlines ) with path . open ( \"w\" , encoding = \"utf8\" ) as file : file . write ( file_content )","title":"serialize()"},{"location":"reference/tim/#hydrolib.core.dflowfm.tim.serializer.TimSerializerConfig","text":"Configuration settings for the TimSerializer.","title":"TimSerializerConfig"},{"location":"reference/xyz/","text":"Sample files \u00b6 Sample .xyz files contain spatial input point data for a D-Flow FM model, and are used in various other input files. A sample data file is described by the classes below. Model \u00b6 XYZModel ( ParsableFileModel ) pydantic-model \u00b6 Sample or forcing file. Attributes: Name Type Description points List[hydrolib.core.dflowfm.xyz.models.XYZPoint] List of XYZPoint dict ( self , * args , ** kwargs ) \u00b6 Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dflowfm/xyz/models.py def dict ( self , * args , ** kwargs ): # speed up serializing by not converting these lowest models to dict return dict ( points = self . points ) XYZPoint ( BaseModel ) pydantic-model \u00b6 Single sample or forcing point. Attributes: Name Type Description x float x or \u03bb coordinate y float y or \u03c6 coordinate z float sample value or group number (forcing) comment Optional[str] keyword for grouping (forcing) comment : str pydantic-field \u00b6 comment or group name Parser \u00b6 XYZParser \u00b6 A parser for .xyz files which are like this: number number number number number number # comment Note that the whitespace can vary and the comment left out. parse ( filepath : Path ) -> Dict staticmethod \u00b6 Parse an .xyz file into a Dict with the list of points read. Parameters: Name Type Description Default filepath Path .xyz file to be read. required Returns: Type Description Dict dictionary with \"points\" value set to a list of points each of which is a dict itself, with keys 'x', 'y', 'z' and 'c' for an optional comment. Exceptions: Type Description ValueError if a line in the file contains no values that could be parsed. Source code in hydrolib/core/dflowfm/xyz/parser.py @staticmethod def parse ( filepath : Path ) -> Dict : \"\"\"Parse an .xyz file into a Dict with the list of points read. Args: filepath (Path): .xyz file to be read. Returns: Dict: dictionary with \"points\" value set to a list of points each of which is a dict itself, with keys 'x', 'y', 'z' and 'c' for an optional comment. Raises: ValueError: if a line in the file contains no values that could be parsed. \"\"\" data : Dict = dict ( points = []) with filepath . open ( encoding = \"utf8\" ) as f : for linenr , line in enumerate ( f . readlines ()): line = line . strip () if line . startswith ( \"*\" ) or len ( line ) == 0 : continue try : x , y , z , * c = re . split ( xyzpattern , line , maxsplit = 3 ) except ValueError : raise ValueError ( f \"Error parsing XYZ file ' { filepath } ', line { linenr + 1 } .\" ) c = c [ 0 ] if len ( c ) > 0 else \"\" c = c . strip ( \"#\" ) . strip () if len ( c ) == 0 : c = None data [ \"points\" ] . append ( dict ( x = x , y = y , z = z , comment = c )) return data Serializer \u00b6 XYZSerializer \u00b6 serialize ( path : Path , data : Dict , config : SerializerConfig , save_settings : ModelSaveSettings ) -> None staticmethod \u00b6 Serializes the XYZ data to the file at the specified path. Attributes: Name Type Description path Path The path to the destination file. data Dict The data to be serialized. config SerializerConfig The serialization configuration. save_settings ModelSaveSettings The model save settings. Source code in hydrolib/core/dflowfm/xyz/serializer.py @staticmethod def serialize ( path : Path , data : Dict , config : SerializerConfig , save_settings : ModelSaveSettings , ) -> None : \"\"\" Serializes the XYZ data to the file at the specified path. Attributes: path (Path): The path to the destination file. data (Dict): The data to be serialized. config (SerializerConfig): The serialization configuration. save_settings (ModelSaveSettings): The model save settings. \"\"\" path . parent . mkdir ( parents = True , exist_ok = True ) space = 1 * \" \" format_float = lambda x : f \" { x :{ config . float_format }} \" with path . open ( \"w\" , encoding = \"utf8\" ) as f : for point in data [ \"points\" ]: geometry : str = space . join ( [ format_float ( p ) for p in XYZSerializer . _get_point_values ( point )] ) if point . comment : f . write ( f \" { geometry } # { point . comment } \\n \" ) else : f . write ( f \" { geometry } \\n \" )","title":"Sample files"},{"location":"reference/xyz/#sample-files","text":"Sample .xyz files contain spatial input point data for a D-Flow FM model, and are used in various other input files. A sample data file is described by the classes below.","title":"Sample files"},{"location":"reference/xyz/#model","text":"","title":"Model"},{"location":"reference/xyz/#hydrolib.core.dflowfm.xyz.models.XYZModel","text":"Sample or forcing file. Attributes: Name Type Description points List[hydrolib.core.dflowfm.xyz.models.XYZPoint] List of XYZPoint","title":"XYZModel"},{"location":"reference/xyz/#hydrolib.core.dflowfm.xyz.models.XYZModel.dict","text":"Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/dflowfm/xyz/models.py def dict ( self , * args , ** kwargs ): # speed up serializing by not converting these lowest models to dict return dict ( points = self . points )","title":"dict()"},{"location":"reference/xyz/#hydrolib.core.dflowfm.xyz.models.XYZPoint","text":"Single sample or forcing point. Attributes: Name Type Description x float x or \u03bb coordinate y float y or \u03c6 coordinate z float sample value or group number (forcing) comment Optional[str] keyword for grouping (forcing)","title":"XYZPoint"},{"location":"reference/xyz/#hydrolib.core.dflowfm.xyz.models.XYZPoint.comment","text":"comment or group name","title":"comment"},{"location":"reference/xyz/#parser","text":"","title":"Parser"},{"location":"reference/xyz/#hydrolib.core.dflowfm.xyz.parser.XYZParser","text":"A parser for .xyz files which are like this: number number number number number number # comment Note that the whitespace can vary and the comment left out.","title":"XYZParser"},{"location":"reference/xyz/#hydrolib.core.dflowfm.xyz.parser.XYZParser.parse","text":"Parse an .xyz file into a Dict with the list of points read. Parameters: Name Type Description Default filepath Path .xyz file to be read. required Returns: Type Description Dict dictionary with \"points\" value set to a list of points each of which is a dict itself, with keys 'x', 'y', 'z' and 'c' for an optional comment. Exceptions: Type Description ValueError if a line in the file contains no values that could be parsed. Source code in hydrolib/core/dflowfm/xyz/parser.py @staticmethod def parse ( filepath : Path ) -> Dict : \"\"\"Parse an .xyz file into a Dict with the list of points read. Args: filepath (Path): .xyz file to be read. Returns: Dict: dictionary with \"points\" value set to a list of points each of which is a dict itself, with keys 'x', 'y', 'z' and 'c' for an optional comment. Raises: ValueError: if a line in the file contains no values that could be parsed. \"\"\" data : Dict = dict ( points = []) with filepath . open ( encoding = \"utf8\" ) as f : for linenr , line in enumerate ( f . readlines ()): line = line . strip () if line . startswith ( \"*\" ) or len ( line ) == 0 : continue try : x , y , z , * c = re . split ( xyzpattern , line , maxsplit = 3 ) except ValueError : raise ValueError ( f \"Error parsing XYZ file ' { filepath } ', line { linenr + 1 } .\" ) c = c [ 0 ] if len ( c ) > 0 else \"\" c = c . strip ( \"#\" ) . strip () if len ( c ) == 0 : c = None data [ \"points\" ] . append ( dict ( x = x , y = y , z = z , comment = c )) return data","title":"parse()"},{"location":"reference/xyz/#serializer","text":"","title":"Serializer"},{"location":"reference/xyz/#hydrolib.core.dflowfm.xyz.serializer.XYZSerializer","text":"","title":"XYZSerializer"},{"location":"reference/xyz/#hydrolib.core.dflowfm.xyz.serializer.XYZSerializer.serialize","text":"Serializes the XYZ data to the file at the specified path. Attributes: Name Type Description path Path The path to the destination file. data Dict The data to be serialized. config SerializerConfig The serialization configuration. save_settings ModelSaveSettings The model save settings. Source code in hydrolib/core/dflowfm/xyz/serializer.py @staticmethod def serialize ( path : Path , data : Dict , config : SerializerConfig , save_settings : ModelSaveSettings , ) -> None : \"\"\" Serializes the XYZ data to the file at the specified path. Attributes: path (Path): The path to the destination file. data (Dict): The data to be serialized. config (SerializerConfig): The serialization configuration. save_settings (ModelSaveSettings): The model save settings. \"\"\" path . parent . mkdir ( parents = True , exist_ok = True ) space = 1 * \" \" format_float = lambda x : f \" { x :{ config . float_format }} \" with path . open ( \"w\" , encoding = \"utf8\" ) as f : for point in data [ \"points\" ]: geometry : str = space . join ( [ format_float ( p ) for p in XYZSerializer . _get_point_values ( point )] ) if point . comment : f . write ( f \" { geometry } # { point . comment } \\n \" ) else : f . write ( f \" { geometry } \\n \" )","title":"serialize()"},{"location":"reference/rr/meteo/","text":"The Rainfall Runoff meteo layer \u00b6 The meteo layer currently contains only support for the BUI file. The \"bui\" file contains the precipitation input data for Rainfall Runoff . It is represented by the classes below. Model \u00b6 BuiModel ( ParsableFileModel ) pydantic-model \u00b6 Model that represents the file structure of a .bui file. get_station_events ( self , station : str ) -> Dict [ datetime . datetime , List [ float ]] \u00b6 Returns all the events (start time and precipitations) related to a given station. Parameters: Name Type Description Default station str Name of the station to retrieve. required Exceptions: Type Description ValueError If the station name does not exist in the BuiModel. Returns: Type Description Dict[datetime, List[float]] Dictionary with the start time and its precipitations. Source code in hydrolib/core/rr/meteo/models.py def get_station_events ( self , station : str ) -> Dict [ datetime , List [ float ]]: \"\"\" Returns all the events (start time and precipitations) related to a given station. Args: station (str): Name of the station to retrieve. Raises: ValueError: If the station name does not exist in the BuiModel. Returns: Dict[datetime, List[float]]: Dictionary with the start time and its precipitations. \"\"\" if station not in self . name_of_stations : raise ValueError ( \"Station {} not found BuiModel.\" . format ( station )) station_idx = self . name_of_stations . index ( station ) station_events = {} for event in self . precipitation_events : start_time , precipitations = event . get_station_precipitations ( station_idx ) station_events [ start_time ] = precipitations return station_events BuiPrecipitationEvent ( BaseModel ) pydantic-model \u00b6 get_station_precipitations ( self , station_idx : int ) -> Tuple [ datetime . datetime , List [ float ]] \u00b6 Returns all the precipitations related to the given station index (column). Parameters: Name Type Description Default station_idx int Index of the column which values need to be retrieved. required Exceptions: Type Description ValueError If the station index does not exist. Returns: Type Description Tuple[datetime, List[float]] Tuple with the start time and its precipitations. Source code in hydrolib/core/rr/meteo/models.py def get_station_precipitations ( self , station_idx : int ) -> Tuple [ datetime , List [ float ]]: \"\"\" Returns all the precipitations related to the given station index (column). Args: station_idx (int): Index of the column which values need to be retrieved. Raises: ValueError: If the station index does not exist. Returns: Tuple[datetime, List[float]]: Tuple with the start time and its precipitations. \"\"\" number_of_stations = len ( self . precipitation_per_timestep [ 0 ]) if station_idx >= number_of_stations : raise ValueError ( \"Station index not found, number of stations: {} \" . format ( number_of_stations ) ) return ( self . start_time , [ ts_precipitations [ station_idx ] for ts_precipitations in self . precipitation_per_timestep ], ) Parser \u00b6 BuiEventListParser \u00b6 A parser for .bui events which are like this: StartTime (YYYY mm dd HH MM SS) TimeSeriesLength (dd HH MM SS) PrecipitationPerTimestep StartTime (YYYY mm dd HH MM SS) TimeSeriesLength (dd HH MM SS) PrecipitationPerTimestep Example given: 2021 12 20 0 0 0 1 0 4 20 4.2 4.2 4.2 2021 12 21 0 0 0 1 0 4 20 2.4 2.4 2.4 parse ( raw_text : str , n_events : int , timestep : int ) -> List [ Dict ] staticmethod \u00b6 Parses a given raw text containing 0 to many text blocks representing a precipitation event. Parameters: Name Type Description Default raw_text str Text blocks representing precipitation events. required n_events int Number of events contained in the text block. required timestep int Number of seconds conforming a timestep. required Returns: Type Description List[Dict] List containing all the events represented as dictionaries. Source code in hydrolib/core/rr/meteo/parser.py @staticmethod def parse ( raw_text : str , n_events : int , timestep : int ) -> List [ Dict ]: \"\"\" Parses a given raw text containing 0 to many text blocks representing a precipitation event. Args: raw_text (str): Text blocks representing precipitation events. n_events (int): Number of events contained in the text block. timestep (int): Number of seconds conforming a timestep. Returns: List[Dict]: List containing all the events represented as dictionaries. \"\"\" def get_event_timestep_length ( raw_line : str ) -> int : timereference = BuiEventParser . parse_event_time_reference ( raw_line ) ts_length : timedelta = timereference [ \"timeseries_length\" ] return ts_length . total_seconds () def get_multiple_events ( raw_lines : List [ str ]) -> Iterator [ BuiEventParser ]: n_line = 0 while n_line < len ( raw_lines ): ts_seconds = get_event_timestep_length ( raw_lines [ n_line ]) event_lines = int ( ts_seconds / timestep ) + 1 yield BuiEventParser . parse ( \" \\n \" . join ( raw_lines [ n_line :][: event_lines ])) n_line += event_lines event_list = [] if n_events == 1 : event_list . append ( BuiEventParser . parse ( raw_text )) elif n_events > 1 : raw_lines = raw_text . splitlines ( keepends = False ) event_list = list ( get_multiple_events ( raw_lines )) return event_list BuiEventParser \u00b6 A parser for the precipitation event section within a .bui file. It resembles something like this: StartTime (YYYY mm dd HH MM SS) TimeSeriesLength (dd HH MM SS) PrecipitationPerTimestep Example given: 2021 12 20 0 0 0 1 0 4 20 4.2 2.4 4.2 2.4 4.2 2.4 (it should match the timeseries length based on the seconds per timstep.) Each column of the last three lines represents a station. parse ( raw_text : str ) -> Dict staticmethod \u00b6 Given text representing a single BuiPrecipitationEvent parses it into a dictionary. Parameters: Name Type Description Default raw_text str Text containing a single precipitation event. required Returns: Type Description Dict Mapped contents of the text. Source code in hydrolib/core/rr/meteo/parser.py @staticmethod def parse ( raw_text : str ) -> Dict : \"\"\" Given text representing a single BuiPrecipitationEvent parses it into a dictionary. Args: raw_text (str): Text containing a single precipitation event. Returns: Dict: Mapped contents of the text. \"\"\" def get_precipitations_per_ts ( line : str ) -> List [ str ]: return [ prec for prec in line . split ()] event_lines = raw_text . splitlines ( keepends = False ) time_reference = BuiEventParser . parse_event_time_reference ( event_lines [ 0 ]) return dict ( start_time = time_reference [ \"start_time\" ], timeseries_length = time_reference [ \"timeseries_length\" ], precipitation_per_timestep = list ( map ( get_precipitations_per_ts , event_lines [ 1 :]) ), ) parse_event_time_reference ( raw_text : str ) -> Dict staticmethod \u00b6 Parses a single event time reference line containing both the start time and the timeseries length into a dictionary. Parameters: Name Type Description Default raw_text str Line representing both start time and timeseries length. required Returns: Type Description Dict Resulting dictionary with keys start_time and timeseries_length. Source code in hydrolib/core/rr/meteo/parser.py @staticmethod def parse_event_time_reference ( raw_text : str ) -> Dict : \"\"\" Parses a single event time reference line containing both the start time and the timeseries length into a dictionary. Args: raw_text (str): Line representing both start time and timeseries length. Returns: Dict: Resulting dictionary with keys start_time and timeseries_length. \"\"\" def get_start_time ( line : str ) -> datetime : return datetime . strptime ( line , \"%Y %m %d %H %M %S\" ) def get_timeseries_length ( line : str ) -> timedelta : time_fields = line . split () return timedelta ( days = int ( time_fields [ 0 ]), hours = int ( time_fields [ 1 ]), minutes = int ( time_fields [ 2 ]), seconds = int ( time_fields [ 3 ]), ) timeref = raw_text . split () return dict ( start_time = get_start_time ( \" \" . join ( timeref [: 6 ])), timeseries_length = get_timeseries_length ( \" \" . join ( timeref [ 6 :])), ) BuiParser \u00b6 A parser for .bui files which are like this: * comments Dataset type to use (always 1). * comments Number of stations. * comments Name of stations * comments Number of events Number of seconds per timestep. * comments First datetime reference. Precipitation per timestep per station. parse ( filepath : Path ) -> Dict staticmethod \u00b6 Parses a given file, in case valid, into a dictionary which can later be mapped to the BuiModel. Parameters: Name Type Description Default filepath Path Path to file containing the data to parse. required Returns: Type Description Dict Parsed values. Source code in hydrolib/core/rr/meteo/parser.py @staticmethod def parse ( filepath : Path ) -> Dict : \"\"\" Parses a given file, in case valid, into a dictionary which can later be mapped to the BuiModel. Args: filepath (Path): Path to file containing the data to parse. Returns: Dict: Parsed values. \"\"\" def get_station_ids ( lines : List [ str ]) -> List [ str ]: return [ s_id . strip ( \"' \\\" \" ) for s_id in lines ] def parse_events_and_timestep ( line : str ) -> Tuple [ int , int ]: n_events_timestep = line . split () return ( int ( n_events_timestep [ 0 ]), int ( n_events_timestep [ 1 ])) bui_lines = [ line for line in filepath . read_text ( encoding = \"utf8\" ) . splitlines () if not line . startswith ( \"*\" ) ] number_of_stations = int ( bui_lines [ 1 ]) last_station_line = 1 + number_of_stations n_events , timestep = parse_events_and_timestep ( bui_lines [ last_station_line + 1 ]) return dict ( default_dataset = bui_lines [ 0 ], number_of_stations = bui_lines [ 1 ], name_of_stations = get_station_ids ( bui_lines [ 2 : last_station_line + 1 ]), number_of_events = n_events , seconds_per_timestep = timestep , precipitation_events = BuiEventListParser . parse ( \" \\n \" . join ( bui_lines [ last_station_line + 2 :]), n_events , timestep ), ) Serializer \u00b6 BuiEventSerializer \u00b6 Serializer class to transform a bui event into a text block. get_timedelta_fields ( duration : timedelta ) -> Dict staticmethod \u00b6 Gets a dictionary containing the time delta in days, hours, minutes and seconds. This means that the seconds field does not contain the accumulative value of days hours and minutes. Parameters: Name Type Description Default duration timedelta Timedelta to convert. required Returns: Type Description Dict Dictionary containing all fields. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def get_timedelta_fields ( duration : timedelta ) -> Dict : \"\"\" Gets a dictionary containing the time delta in days, hours, minutes and seconds. This means that the seconds field does not contain the accumulative value of days hours and minutes. Args: duration (timedelta): Timedelta to convert. Returns: Dict: Dictionary containing all fields. \"\"\" total_hours = int ( duration . seconds / ( 60 * 60 )) total_minutes = int (( duration . seconds / 60 ) - ( total_hours * 60 )) total_seconds = int ( duration . seconds - (( total_hours * 60 + total_minutes ) * 60 ) ) return dict ( d_seconds = total_seconds , d_minutes = total_minutes , d_hours = total_hours , d_days = duration . days , ) serialize ( event_data : Dict , config : SerializerConfig ) -> str staticmethod \u00b6 Serializes a dictionary representing an event into a text block. Parameters: Name Type Description Default event_data Dict Dictionary representing precipitation event. required config SerializerConfig The serialization configuration. required Returns: Type Description str Formatted string. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize ( event_data : Dict , config : SerializerConfig ) -> str : \"\"\" Serializes a dictionary representing an event into a text block. Args: event_data (Dict): Dictionary representing precipitation event. config (SerializerConfig): The serialization configuration. Returns: str: Formatted string. \"\"\" event_data [ \"start_time\" ] = BuiEventSerializer . serialize_start_time ( event_data [ \"start_time\" ] ) ts_duration = event_data [ \"timeseries_length\" ] event_data = { ** event_data , ** BuiEventSerializer . get_timedelta_fields ( ts_duration ), } event_data [ \"timeseries_length\" ] = BuiEventSerializer . serialize_timeseries_length ( event_data [ \"timeseries_length\" ] ) event_data [ \"precipitation_per_timestep\" ] = BuiEventSerializer . serialize_precipitation_per_timestep ( event_data [ \"precipitation_per_timestep\" ], config ) if \"event_idx\" not in event_data . keys (): event_data [ \"event_idx\" ] = 1 return BuiEventSerializer . bui_event_template . format ( ** event_data ) serialize_precipitation_per_timestep ( data_to_serialize : List [ List [ float ]], config : SerializerConfig ) -> str staticmethod \u00b6 Serialized the data containing all the precipitations per timestep (and station) into a single string ready to be mapped. Parameters: Name Type Description Default data_to_serialize List[List[str]] Data to be mapped. required config SerializerConfig The serialization configuration. required Returns: Type Description str Serialized string in .bui format. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_precipitation_per_timestep ( data_to_serialize : List [ List [ float ]], config : SerializerConfig ) -> str : \"\"\" Serialized the data containing all the precipitations per timestep (and station) into a single string ready to be mapped. Args: data_to_serialize (List[List[str]]): Data to be mapped. config (SerializerConfig): The serialization configuration. Returns: str: Serialized string in .bui format. \"\"\" float_format = lambda v : f \" { v :{ config . float_format }} \" serialized_data = str . join ( \" \\n \" , [ str . join ( \" \" , map ( float_format , listed_data )) for listed_data in data_to_serialize ], ) return serialized_data serialize_start_time ( data_to_serialize : datetime ) -> str staticmethod \u00b6 Serializes a datetime into the expected .bui format. Parameters: Name Type Description Default data_to_serialize datetime Datetime representing reference time. required Returns: Type Description str Converted datetime into string. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_start_time ( data_to_serialize : datetime ) -> str : \"\"\" Serializes a datetime into the expected .bui format. Args: data_to_serialize (datetime): Datetime representing reference time. Returns: str: Converted datetime into string. \"\"\" # Not using the following format because we only want one digit instead of # double (day 1 -> 1, instead of 01). # data_to_serialize.strftime(\"%Y %m %d %H %M %S\") dt = data_to_serialize return f \" { dt . year } { dt . month } { dt . day } { dt . hour } { dt . minute } { dt . second } \" serialize_timeseries_length ( data_to_serialize : timedelta ) -> str staticmethod \u00b6 Serializes a given timedelta into the .bui format. Parameters: Name Type Description Default data_to_serialize timedelta Reference timespan to serialize. required Returns: Type Description str Converted timedelta in string. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_timeseries_length ( data_to_serialize : timedelta ) -> str : \"\"\" Serializes a given timedelta into the .bui format. Args: data_to_serialize (timedelta): Reference timespan to serialize. Returns: str: Converted timedelta in string. \"\"\" fields_dict = BuiEventSerializer . get_timedelta_fields ( data_to_serialize ) total_hours = fields_dict [ \"d_hours\" ] total_minutes = fields_dict [ \"d_minutes\" ] total_seconds = fields_dict [ \"d_seconds\" ] return f \" { data_to_serialize . days } { total_hours } { total_minutes } { total_seconds } \" BuiSerializer \u00b6 Serializer class to transform an object into a .bui file text format. serialize ( bui_data : Dict , config : SerializerConfig ) -> str staticmethod \u00b6 Formats the bui_template with the content of the given data. NOTE: It requires that caller injects file_path into bui_data prior to this call. Otherwise it will crash. Parameters: Name Type Description Default bui_data Dict Data to serialize. required config SerializerConfig The serialization configuration. required Returns: Type Description str The serialized data. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize ( bui_data : Dict , config : SerializerConfig ) -> str : \"\"\" Formats the bui_template with the content of the given data. NOTE: It requires that caller injects file_path into bui_data prior to this call. Otherwise it will crash. Args: bui_data (Dict): Data to serialize. config (SerializerConfig): The serialization configuration. Returns: str: The serialized data. \"\"\" bui_data [ \"datetime_now\" ] = datetime . now () . strftime ( \" %d -%m-%y %H:%M:%S\" ) bui_data [ \"name_of_stations\" ] = BuiSerializer . serialize_stations_ids ( bui_data [ \"name_of_stations\" ] ) bui_data [ \"precipitation_events\" ] = BuiSerializer . serialize_event_list ( bui_data [ \"precipitation_events\" ], config ) return BuiSerializer . bui_template . format ( ** bui_data ) serialize_event_list ( data_to_serialize : List [ Dict ], config : SerializerConfig ) -> str staticmethod \u00b6 Serializes a event list dictionary into a single text block. Parameters: Name Type Description Default data_to_serialize Dict Dictionary containing list of events. required config SerializerConfig The serialization configuration. required Returns: Type Description str Text block representing all precipitation events. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_event_list ( data_to_serialize : List [ Dict ], config : SerializerConfig ) -> str : \"\"\" Serializes a event list dictionary into a single text block. Args: data_to_serialize (Dict): Dictionary containing list of events. config (SerializerConfig): The serialization configuration. Returns: str: Text block representing all precipitation events. \"\"\" serialized_list = [] for n_event , event in enumerate ( data_to_serialize ): event [ \"event_idx\" ] = n_event + 1 serialized_list . append ( BuiEventSerializer . serialize ( event , config )) return \" \\n \" . join ( serialized_list ) serialize_stations_ids ( data_to_serialize : List [ str ]) -> str staticmethod \u00b6 Serializes the stations ids into a single string as expected in a .bui file. Parameters: Name Type Description Default data_to_serialize List[str] List of station ids. required Returns: Type Description str Serialized string. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_stations_ids ( data_to_serialize : List [ str ]) -> str : \"\"\" Serializes the stations ids into a single string as expected in a .bui file. Args: data_to_serialize (List[str]): List of station ids. Returns: str: Serialized string. \"\"\" return \" \\n \" . join ( f \"' { station_id } '\" for station_id in data_to_serialize ) write_bui_file ( path : Path , data : Dict , config : SerializerConfig , save_settings : ModelSaveSettings ) -> None \u00b6 Writes a .bui file in the given path based on the data given in a dictionary. Parameters: Name Type Description Default path Path Path where to output the text. required data Dict Data to serialize into the file. required config SerializerConfig The serialization configuration. required save_settings ModelSaveSettings The model save settings. required Source code in hydrolib/core/rr/meteo/serializer.py def write_bui_file ( path : Path , data : Dict , config : SerializerConfig , save_settings : ModelSaveSettings ) -> None : \"\"\" Writes a .bui file in the given path based on the data given in a dictionary. Args: path (Path): Path where to output the text. data (Dict): Data to serialize into the file. config (SerializerConfig): The serialization configuration. save_settings (ModelSaveSettings): The model save settings. \"\"\" data [ \"filepath\" ] = path # This is redundant as already exists in the data. serialized_bui_data = BuiSerializer . serialize ( data , config ) path . parent . mkdir ( parents = True , exist_ok = True ) path . write_text ( serialized_bui_data , encoding = \"utf8\" )","title":"The Rainfall Runoff meteo layer"},{"location":"reference/rr/meteo/#the-rainfall-runoff-meteo-layer","text":"The meteo layer currently contains only support for the BUI file. The \"bui\" file contains the precipitation input data for Rainfall Runoff . It is represented by the classes below.","title":"The Rainfall Runoff meteo layer"},{"location":"reference/rr/meteo/#model","text":"","title":"Model"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.models.BuiModel","text":"Model that represents the file structure of a .bui file.","title":"BuiModel"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.models.BuiModel.get_station_events","text":"Returns all the events (start time and precipitations) related to a given station. Parameters: Name Type Description Default station str Name of the station to retrieve. required Exceptions: Type Description ValueError If the station name does not exist in the BuiModel. Returns: Type Description Dict[datetime, List[float]] Dictionary with the start time and its precipitations. Source code in hydrolib/core/rr/meteo/models.py def get_station_events ( self , station : str ) -> Dict [ datetime , List [ float ]]: \"\"\" Returns all the events (start time and precipitations) related to a given station. Args: station (str): Name of the station to retrieve. Raises: ValueError: If the station name does not exist in the BuiModel. Returns: Dict[datetime, List[float]]: Dictionary with the start time and its precipitations. \"\"\" if station not in self . name_of_stations : raise ValueError ( \"Station {} not found BuiModel.\" . format ( station )) station_idx = self . name_of_stations . index ( station ) station_events = {} for event in self . precipitation_events : start_time , precipitations = event . get_station_precipitations ( station_idx ) station_events [ start_time ] = precipitations return station_events","title":"get_station_events()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.models.BuiPrecipitationEvent","text":"","title":"BuiPrecipitationEvent"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.models.BuiPrecipitationEvent.get_station_precipitations","text":"Returns all the precipitations related to the given station index (column). Parameters: Name Type Description Default station_idx int Index of the column which values need to be retrieved. required Exceptions: Type Description ValueError If the station index does not exist. Returns: Type Description Tuple[datetime, List[float]] Tuple with the start time and its precipitations. Source code in hydrolib/core/rr/meteo/models.py def get_station_precipitations ( self , station_idx : int ) -> Tuple [ datetime , List [ float ]]: \"\"\" Returns all the precipitations related to the given station index (column). Args: station_idx (int): Index of the column which values need to be retrieved. Raises: ValueError: If the station index does not exist. Returns: Tuple[datetime, List[float]]: Tuple with the start time and its precipitations. \"\"\" number_of_stations = len ( self . precipitation_per_timestep [ 0 ]) if station_idx >= number_of_stations : raise ValueError ( \"Station index not found, number of stations: {} \" . format ( number_of_stations ) ) return ( self . start_time , [ ts_precipitations [ station_idx ] for ts_precipitations in self . precipitation_per_timestep ], )","title":"get_station_precipitations()"},{"location":"reference/rr/meteo/#parser","text":"","title":"Parser"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.parser.BuiEventListParser","text":"A parser for .bui events which are like this: StartTime (YYYY mm dd HH MM SS) TimeSeriesLength (dd HH MM SS) PrecipitationPerTimestep StartTime (YYYY mm dd HH MM SS) TimeSeriesLength (dd HH MM SS) PrecipitationPerTimestep Example given: 2021 12 20 0 0 0 1 0 4 20 4.2 4.2 4.2 2021 12 21 0 0 0 1 0 4 20 2.4 2.4 2.4","title":"BuiEventListParser"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.parser.BuiEventListParser.parse","text":"Parses a given raw text containing 0 to many text blocks representing a precipitation event. Parameters: Name Type Description Default raw_text str Text blocks representing precipitation events. required n_events int Number of events contained in the text block. required timestep int Number of seconds conforming a timestep. required Returns: Type Description List[Dict] List containing all the events represented as dictionaries. Source code in hydrolib/core/rr/meteo/parser.py @staticmethod def parse ( raw_text : str , n_events : int , timestep : int ) -> List [ Dict ]: \"\"\" Parses a given raw text containing 0 to many text blocks representing a precipitation event. Args: raw_text (str): Text blocks representing precipitation events. n_events (int): Number of events contained in the text block. timestep (int): Number of seconds conforming a timestep. Returns: List[Dict]: List containing all the events represented as dictionaries. \"\"\" def get_event_timestep_length ( raw_line : str ) -> int : timereference = BuiEventParser . parse_event_time_reference ( raw_line ) ts_length : timedelta = timereference [ \"timeseries_length\" ] return ts_length . total_seconds () def get_multiple_events ( raw_lines : List [ str ]) -> Iterator [ BuiEventParser ]: n_line = 0 while n_line < len ( raw_lines ): ts_seconds = get_event_timestep_length ( raw_lines [ n_line ]) event_lines = int ( ts_seconds / timestep ) + 1 yield BuiEventParser . parse ( \" \\n \" . join ( raw_lines [ n_line :][: event_lines ])) n_line += event_lines event_list = [] if n_events == 1 : event_list . append ( BuiEventParser . parse ( raw_text )) elif n_events > 1 : raw_lines = raw_text . splitlines ( keepends = False ) event_list = list ( get_multiple_events ( raw_lines )) return event_list","title":"parse()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.parser.BuiEventParser","text":"A parser for the precipitation event section within a .bui file. It resembles something like this: StartTime (YYYY mm dd HH MM SS) TimeSeriesLength (dd HH MM SS) PrecipitationPerTimestep Example given: 2021 12 20 0 0 0 1 0 4 20 4.2 2.4 4.2 2.4 4.2 2.4 (it should match the timeseries length based on the seconds per timstep.) Each column of the last three lines represents a station.","title":"BuiEventParser"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.parser.BuiEventParser.parse","text":"Given text representing a single BuiPrecipitationEvent parses it into a dictionary. Parameters: Name Type Description Default raw_text str Text containing a single precipitation event. required Returns: Type Description Dict Mapped contents of the text. Source code in hydrolib/core/rr/meteo/parser.py @staticmethod def parse ( raw_text : str ) -> Dict : \"\"\" Given text representing a single BuiPrecipitationEvent parses it into a dictionary. Args: raw_text (str): Text containing a single precipitation event. Returns: Dict: Mapped contents of the text. \"\"\" def get_precipitations_per_ts ( line : str ) -> List [ str ]: return [ prec for prec in line . split ()] event_lines = raw_text . splitlines ( keepends = False ) time_reference = BuiEventParser . parse_event_time_reference ( event_lines [ 0 ]) return dict ( start_time = time_reference [ \"start_time\" ], timeseries_length = time_reference [ \"timeseries_length\" ], precipitation_per_timestep = list ( map ( get_precipitations_per_ts , event_lines [ 1 :]) ), )","title":"parse()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.parser.BuiEventParser.parse_event_time_reference","text":"Parses a single event time reference line containing both the start time and the timeseries length into a dictionary. Parameters: Name Type Description Default raw_text str Line representing both start time and timeseries length. required Returns: Type Description Dict Resulting dictionary with keys start_time and timeseries_length. Source code in hydrolib/core/rr/meteo/parser.py @staticmethod def parse_event_time_reference ( raw_text : str ) -> Dict : \"\"\" Parses a single event time reference line containing both the start time and the timeseries length into a dictionary. Args: raw_text (str): Line representing both start time and timeseries length. Returns: Dict: Resulting dictionary with keys start_time and timeseries_length. \"\"\" def get_start_time ( line : str ) -> datetime : return datetime . strptime ( line , \"%Y %m %d %H %M %S\" ) def get_timeseries_length ( line : str ) -> timedelta : time_fields = line . split () return timedelta ( days = int ( time_fields [ 0 ]), hours = int ( time_fields [ 1 ]), minutes = int ( time_fields [ 2 ]), seconds = int ( time_fields [ 3 ]), ) timeref = raw_text . split () return dict ( start_time = get_start_time ( \" \" . join ( timeref [: 6 ])), timeseries_length = get_timeseries_length ( \" \" . join ( timeref [ 6 :])), )","title":"parse_event_time_reference()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.parser.BuiParser","text":"A parser for .bui files which are like this: * comments Dataset type to use (always 1). * comments Number of stations. * comments Name of stations * comments Number of events Number of seconds per timestep. * comments First datetime reference. Precipitation per timestep per station.","title":"BuiParser"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.parser.BuiParser.parse","text":"Parses a given file, in case valid, into a dictionary which can later be mapped to the BuiModel. Parameters: Name Type Description Default filepath Path Path to file containing the data to parse. required Returns: Type Description Dict Parsed values. Source code in hydrolib/core/rr/meteo/parser.py @staticmethod def parse ( filepath : Path ) -> Dict : \"\"\" Parses a given file, in case valid, into a dictionary which can later be mapped to the BuiModel. Args: filepath (Path): Path to file containing the data to parse. Returns: Dict: Parsed values. \"\"\" def get_station_ids ( lines : List [ str ]) -> List [ str ]: return [ s_id . strip ( \"' \\\" \" ) for s_id in lines ] def parse_events_and_timestep ( line : str ) -> Tuple [ int , int ]: n_events_timestep = line . split () return ( int ( n_events_timestep [ 0 ]), int ( n_events_timestep [ 1 ])) bui_lines = [ line for line in filepath . read_text ( encoding = \"utf8\" ) . splitlines () if not line . startswith ( \"*\" ) ] number_of_stations = int ( bui_lines [ 1 ]) last_station_line = 1 + number_of_stations n_events , timestep = parse_events_and_timestep ( bui_lines [ last_station_line + 1 ]) return dict ( default_dataset = bui_lines [ 0 ], number_of_stations = bui_lines [ 1 ], name_of_stations = get_station_ids ( bui_lines [ 2 : last_station_line + 1 ]), number_of_events = n_events , seconds_per_timestep = timestep , precipitation_events = BuiEventListParser . parse ( \" \\n \" . join ( bui_lines [ last_station_line + 2 :]), n_events , timestep ), )","title":"parse()"},{"location":"reference/rr/meteo/#serializer","text":"","title":"Serializer"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiEventSerializer","text":"Serializer class to transform a bui event into a text block.","title":"BuiEventSerializer"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiEventSerializer.get_timedelta_fields","text":"Gets a dictionary containing the time delta in days, hours, minutes and seconds. This means that the seconds field does not contain the accumulative value of days hours and minutes. Parameters: Name Type Description Default duration timedelta Timedelta to convert. required Returns: Type Description Dict Dictionary containing all fields. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def get_timedelta_fields ( duration : timedelta ) -> Dict : \"\"\" Gets a dictionary containing the time delta in days, hours, minutes and seconds. This means that the seconds field does not contain the accumulative value of days hours and minutes. Args: duration (timedelta): Timedelta to convert. Returns: Dict: Dictionary containing all fields. \"\"\" total_hours = int ( duration . seconds / ( 60 * 60 )) total_minutes = int (( duration . seconds / 60 ) - ( total_hours * 60 )) total_seconds = int ( duration . seconds - (( total_hours * 60 + total_minutes ) * 60 ) ) return dict ( d_seconds = total_seconds , d_minutes = total_minutes , d_hours = total_hours , d_days = duration . days , )","title":"get_timedelta_fields()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiEventSerializer.serialize","text":"Serializes a dictionary representing an event into a text block. Parameters: Name Type Description Default event_data Dict Dictionary representing precipitation event. required config SerializerConfig The serialization configuration. required Returns: Type Description str Formatted string. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize ( event_data : Dict , config : SerializerConfig ) -> str : \"\"\" Serializes a dictionary representing an event into a text block. Args: event_data (Dict): Dictionary representing precipitation event. config (SerializerConfig): The serialization configuration. Returns: str: Formatted string. \"\"\" event_data [ \"start_time\" ] = BuiEventSerializer . serialize_start_time ( event_data [ \"start_time\" ] ) ts_duration = event_data [ \"timeseries_length\" ] event_data = { ** event_data , ** BuiEventSerializer . get_timedelta_fields ( ts_duration ), } event_data [ \"timeseries_length\" ] = BuiEventSerializer . serialize_timeseries_length ( event_data [ \"timeseries_length\" ] ) event_data [ \"precipitation_per_timestep\" ] = BuiEventSerializer . serialize_precipitation_per_timestep ( event_data [ \"precipitation_per_timestep\" ], config ) if \"event_idx\" not in event_data . keys (): event_data [ \"event_idx\" ] = 1 return BuiEventSerializer . bui_event_template . format ( ** event_data )","title":"serialize()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiEventSerializer.serialize_precipitation_per_timestep","text":"Serialized the data containing all the precipitations per timestep (and station) into a single string ready to be mapped. Parameters: Name Type Description Default data_to_serialize List[List[str]] Data to be mapped. required config SerializerConfig The serialization configuration. required Returns: Type Description str Serialized string in .bui format. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_precipitation_per_timestep ( data_to_serialize : List [ List [ float ]], config : SerializerConfig ) -> str : \"\"\" Serialized the data containing all the precipitations per timestep (and station) into a single string ready to be mapped. Args: data_to_serialize (List[List[str]]): Data to be mapped. config (SerializerConfig): The serialization configuration. Returns: str: Serialized string in .bui format. \"\"\" float_format = lambda v : f \" { v :{ config . float_format }} \" serialized_data = str . join ( \" \\n \" , [ str . join ( \" \" , map ( float_format , listed_data )) for listed_data in data_to_serialize ], ) return serialized_data","title":"serialize_precipitation_per_timestep()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiEventSerializer.serialize_start_time","text":"Serializes a datetime into the expected .bui format. Parameters: Name Type Description Default data_to_serialize datetime Datetime representing reference time. required Returns: Type Description str Converted datetime into string. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_start_time ( data_to_serialize : datetime ) -> str : \"\"\" Serializes a datetime into the expected .bui format. Args: data_to_serialize (datetime): Datetime representing reference time. Returns: str: Converted datetime into string. \"\"\" # Not using the following format because we only want one digit instead of # double (day 1 -> 1, instead of 01). # data_to_serialize.strftime(\"%Y %m %d %H %M %S\") dt = data_to_serialize return f \" { dt . year } { dt . month } { dt . day } { dt . hour } { dt . minute } { dt . second } \"","title":"serialize_start_time()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiEventSerializer.serialize_timeseries_length","text":"Serializes a given timedelta into the .bui format. Parameters: Name Type Description Default data_to_serialize timedelta Reference timespan to serialize. required Returns: Type Description str Converted timedelta in string. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_timeseries_length ( data_to_serialize : timedelta ) -> str : \"\"\" Serializes a given timedelta into the .bui format. Args: data_to_serialize (timedelta): Reference timespan to serialize. Returns: str: Converted timedelta in string. \"\"\" fields_dict = BuiEventSerializer . get_timedelta_fields ( data_to_serialize ) total_hours = fields_dict [ \"d_hours\" ] total_minutes = fields_dict [ \"d_minutes\" ] total_seconds = fields_dict [ \"d_seconds\" ] return f \" { data_to_serialize . days } { total_hours } { total_minutes } { total_seconds } \"","title":"serialize_timeseries_length()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiSerializer","text":"Serializer class to transform an object into a .bui file text format.","title":"BuiSerializer"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiSerializer.serialize","text":"Formats the bui_template with the content of the given data. NOTE: It requires that caller injects file_path into bui_data prior to this call. Otherwise it will crash. Parameters: Name Type Description Default bui_data Dict Data to serialize. required config SerializerConfig The serialization configuration. required Returns: Type Description str The serialized data. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize ( bui_data : Dict , config : SerializerConfig ) -> str : \"\"\" Formats the bui_template with the content of the given data. NOTE: It requires that caller injects file_path into bui_data prior to this call. Otherwise it will crash. Args: bui_data (Dict): Data to serialize. config (SerializerConfig): The serialization configuration. Returns: str: The serialized data. \"\"\" bui_data [ \"datetime_now\" ] = datetime . now () . strftime ( \" %d -%m-%y %H:%M:%S\" ) bui_data [ \"name_of_stations\" ] = BuiSerializer . serialize_stations_ids ( bui_data [ \"name_of_stations\" ] ) bui_data [ \"precipitation_events\" ] = BuiSerializer . serialize_event_list ( bui_data [ \"precipitation_events\" ], config ) return BuiSerializer . bui_template . format ( ** bui_data )","title":"serialize()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiSerializer.serialize_event_list","text":"Serializes a event list dictionary into a single text block. Parameters: Name Type Description Default data_to_serialize Dict Dictionary containing list of events. required config SerializerConfig The serialization configuration. required Returns: Type Description str Text block representing all precipitation events. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_event_list ( data_to_serialize : List [ Dict ], config : SerializerConfig ) -> str : \"\"\" Serializes a event list dictionary into a single text block. Args: data_to_serialize (Dict): Dictionary containing list of events. config (SerializerConfig): The serialization configuration. Returns: str: Text block representing all precipitation events. \"\"\" serialized_list = [] for n_event , event in enumerate ( data_to_serialize ): event [ \"event_idx\" ] = n_event + 1 serialized_list . append ( BuiEventSerializer . serialize ( event , config )) return \" \\n \" . join ( serialized_list )","title":"serialize_event_list()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.BuiSerializer.serialize_stations_ids","text":"Serializes the stations ids into a single string as expected in a .bui file. Parameters: Name Type Description Default data_to_serialize List[str] List of station ids. required Returns: Type Description str Serialized string. Source code in hydrolib/core/rr/meteo/serializer.py @staticmethod def serialize_stations_ids ( data_to_serialize : List [ str ]) -> str : \"\"\" Serializes the stations ids into a single string as expected in a .bui file. Args: data_to_serialize (List[str]): List of station ids. Returns: str: Serialized string. \"\"\" return \" \\n \" . join ( f \"' { station_id } '\" for station_id in data_to_serialize )","title":"serialize_stations_ids()"},{"location":"reference/rr/meteo/#hydrolib.core.rr.meteo.serializer.write_bui_file","text":"Writes a .bui file in the given path based on the data given in a dictionary. Parameters: Name Type Description Default path Path Path where to output the text. required data Dict Data to serialize into the file. required config SerializerConfig The serialization configuration. required save_settings ModelSaveSettings The model save settings. required Source code in hydrolib/core/rr/meteo/serializer.py def write_bui_file ( path : Path , data : Dict , config : SerializerConfig , save_settings : ModelSaveSettings ) -> None : \"\"\" Writes a .bui file in the given path based on the data given in a dictionary. Args: path (Path): Path where to output the text. data (Dict): Data to serialize into the file. config (SerializerConfig): The serialization configuration. save_settings (ModelSaveSettings): The model save settings. \"\"\" data [ \"filepath\" ] = path # This is redundant as already exists in the data. serialized_bui_data = BuiSerializer . serialize ( data , config ) path . parent . mkdir ( parents = True , exist_ok = True ) path . write_text ( serialized_bui_data , encoding = \"utf8\" )","title":"write_bui_file()"},{"location":"reference/rr/rr/","text":"RainfallRunoff file models \u00b6 The rr module provides the various file models for files that are input to the Rainfall Runoff kernel. Support is still basic, but growing. The input 'layers' listed below correspond with the input description in the SOBEK UM . Main input (sobek_3b.fnm) \u00b6 models.py defines the RainfallRunoffModel and supporting structures. ImmutableDiskOnlyFileModel ( DiskOnlyFileModel ) pydantic-model \u00b6 ImmutableDiskOnlyFileModel modifies the DiskOnlyFileModel to provide faux immutablitity. This behaviour is required for the mappix properties, which should always have the same name and path and should not be modified by users. RainfallRunoffModel ( ParsableFileModel ) pydantic-model \u00b6 The RainfallRunoffModel contains all paths and sub-models related to the Rainfall Runoff model. General layer \u00b6 rainfall file \u00b6 BuiModel ( ParsableFileModel ) pydantic-model \u00b6 Model that represents the file structure of a .bui file. get_station_events ( self , station : str ) -> Dict [ datetime . datetime , List [ float ]] \u00b6 Returns all the events (start time and precipitations) related to a given station. Parameters: Name Type Description Default station str Name of the station to retrieve. required Exceptions: Type Description ValueError If the station name does not exist in the BuiModel. Returns: Type Description Dict[datetime, List[float]] Dictionary with the start time and its precipitations. Source code in hydrolib/core/rr/meteo/models.py def get_station_events ( self , station : str ) -> Dict [ datetime , List [ float ]]: \"\"\" Returns all the events (start time and precipitations) related to a given station. Args: station (str): Name of the station to retrieve. Raises: ValueError: If the station name does not exist in the BuiModel. Returns: Dict[datetime, List[float]]: Dictionary with the start time and its precipitations. \"\"\" if station not in self . name_of_stations : raise ValueError ( \"Station {} not found BuiModel.\" . format ( station )) station_idx = self . name_of_stations . index ( station ) station_events = {} for event in self . precipitation_events : start_time , precipitations = event . get_station_precipitations ( station_idx ) station_events [ start_time ] = precipitations return station_events BuiPrecipitationEvent ( BaseModel ) pydantic-model \u00b6 get_station_precipitations ( self , station_idx : int ) -> Tuple [ datetime . datetime , List [ float ]] \u00b6 Returns all the precipitations related to the given station index (column). Parameters: Name Type Description Default station_idx int Index of the column which values need to be retrieved. required Exceptions: Type Description ValueError If the station index does not exist. Returns: Type Description Tuple[datetime, List[float]] Tuple with the start time and its precipitations. Source code in hydrolib/core/rr/meteo/models.py def get_station_precipitations ( self , station_idx : int ) -> Tuple [ datetime , List [ float ]]: \"\"\" Returns all the precipitations related to the given station index (column). Args: station_idx (int): Index of the column which values need to be retrieved. Raises: ValueError: If the station index does not exist. Returns: Tuple[datetime, List[float]]: Tuple with the start time and its precipitations. \"\"\" number_of_stations = len ( self . precipitation_per_timestep [ 0 ]) if station_idx >= number_of_stations : raise ValueError ( \"Station index not found, number of stations: {} \" . format ( number_of_stations ) ) return ( self . start_time , [ ts_precipitations [ station_idx ] for ts_precipitations in self . precipitation_per_timestep ], ) Topology layer (\"Topography\" in SOBEK UM) \u00b6 Link ( BaseModel ) pydantic-model \u00b6 Represents a link from the topology link file. dict ( self , * args , ** kwargs ) \u00b6 Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/rr/topology/models.py def dict ( self , * args , ** kwargs ): kwargs [ \"by_alias\" ] = True return super () . dict ( * args , ** kwargs ) LinkFile ( ParsableFileModel ) pydantic-model \u00b6 Represents the file with the RR link topology data. Node ( BaseModel ) pydantic-model \u00b6 Represents a node from the topology node file. dict ( self , * args , ** kwargs ) \u00b6 Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/rr/topology/models.py def dict ( self , * args , ** kwargs ): kwargs [ \"by_alias\" ] = True return super () . dict ( * args , ** kwargs ) NodeFile ( ParsableFileModel ) pydantic-model \u00b6 Represents the file with the RR node topology data. nodetypes_netter_to_rr \u00b6 Dictionary with nt mapped against the expected mt . Some model types mt do not have a related netter type; in that case the dict key is a dummy value of - . (Other input layers foreseen in future releases) \u00b6","title":"RainfallRunoff file models"},{"location":"reference/rr/rr/#rainfallrunoff-file-models","text":"The rr module provides the various file models for files that are input to the Rainfall Runoff kernel. Support is still basic, but growing. The input 'layers' listed below correspond with the input description in the SOBEK UM .","title":"RainfallRunoff file models"},{"location":"reference/rr/rr/#main-input-sobek_3bfnm","text":"models.py defines the RainfallRunoffModel and supporting structures.","title":"Main input (sobek_3b.fnm)"},{"location":"reference/rr/rr/#hydrolib.core.rr.models.ImmutableDiskOnlyFileModel","text":"ImmutableDiskOnlyFileModel modifies the DiskOnlyFileModel to provide faux immutablitity. This behaviour is required for the mappix properties, which should always have the same name and path and should not be modified by users.","title":"ImmutableDiskOnlyFileModel"},{"location":"reference/rr/rr/#hydrolib.core.rr.models.RainfallRunoffModel","text":"The RainfallRunoffModel contains all paths and sub-models related to the Rainfall Runoff model.","title":"RainfallRunoffModel"},{"location":"reference/rr/rr/#general-layer","text":"","title":"General layer"},{"location":"reference/rr/rr/#rainfall-file","text":"","title":"rainfall file"},{"location":"reference/rr/rr/#hydrolib.core.rr.meteo.models.BuiModel","text":"Model that represents the file structure of a .bui file.","title":"BuiModel"},{"location":"reference/rr/rr/#hydrolib.core.rr.meteo.models.BuiModel.get_station_events","text":"Returns all the events (start time and precipitations) related to a given station. Parameters: Name Type Description Default station str Name of the station to retrieve. required Exceptions: Type Description ValueError If the station name does not exist in the BuiModel. Returns: Type Description Dict[datetime, List[float]] Dictionary with the start time and its precipitations. Source code in hydrolib/core/rr/meteo/models.py def get_station_events ( self , station : str ) -> Dict [ datetime , List [ float ]]: \"\"\" Returns all the events (start time and precipitations) related to a given station. Args: station (str): Name of the station to retrieve. Raises: ValueError: If the station name does not exist in the BuiModel. Returns: Dict[datetime, List[float]]: Dictionary with the start time and its precipitations. \"\"\" if station not in self . name_of_stations : raise ValueError ( \"Station {} not found BuiModel.\" . format ( station )) station_idx = self . name_of_stations . index ( station ) station_events = {} for event in self . precipitation_events : start_time , precipitations = event . get_station_precipitations ( station_idx ) station_events [ start_time ] = precipitations return station_events","title":"get_station_events()"},{"location":"reference/rr/rr/#hydrolib.core.rr.meteo.models.BuiPrecipitationEvent","text":"","title":"BuiPrecipitationEvent"},{"location":"reference/rr/rr/#hydrolib.core.rr.meteo.models.BuiPrecipitationEvent.get_station_precipitations","text":"Returns all the precipitations related to the given station index (column). Parameters: Name Type Description Default station_idx int Index of the column which values need to be retrieved. required Exceptions: Type Description ValueError If the station index does not exist. Returns: Type Description Tuple[datetime, List[float]] Tuple with the start time and its precipitations. Source code in hydrolib/core/rr/meteo/models.py def get_station_precipitations ( self , station_idx : int ) -> Tuple [ datetime , List [ float ]]: \"\"\" Returns all the precipitations related to the given station index (column). Args: station_idx (int): Index of the column which values need to be retrieved. Raises: ValueError: If the station index does not exist. Returns: Tuple[datetime, List[float]]: Tuple with the start time and its precipitations. \"\"\" number_of_stations = len ( self . precipitation_per_timestep [ 0 ]) if station_idx >= number_of_stations : raise ValueError ( \"Station index not found, number of stations: {} \" . format ( number_of_stations ) ) return ( self . start_time , [ ts_precipitations [ station_idx ] for ts_precipitations in self . precipitation_per_timestep ], )","title":"get_station_precipitations()"},{"location":"reference/rr/rr/#topology-layer-topography-in-sobek-um","text":"","title":"Topology layer (\"Topography\" in SOBEK UM)"},{"location":"reference/rr/rr/#hydrolib.core.rr.topology.models.Link","text":"Represents a link from the topology link file.","title":"Link"},{"location":"reference/rr/rr/#hydrolib.core.rr.topology.models.Link.dict","text":"Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/rr/topology/models.py def dict ( self , * args , ** kwargs ): kwargs [ \"by_alias\" ] = True return super () . dict ( * args , ** kwargs )","title":"dict()"},{"location":"reference/rr/rr/#hydrolib.core.rr.topology.models.LinkFile","text":"Represents the file with the RR link topology data.","title":"LinkFile"},{"location":"reference/rr/rr/#hydrolib.core.rr.topology.models.Node","text":"Represents a node from the topology node file.","title":"Node"},{"location":"reference/rr/rr/#hydrolib.core.rr.topology.models.Node.dict","text":"Generate a dictionary representation of the model, optionally specifying which fields to include or exclude. Source code in hydrolib/core/rr/topology/models.py def dict ( self , * args , ** kwargs ): kwargs [ \"by_alias\" ] = True return super () . dict ( * args , ** kwargs )","title":"dict()"},{"location":"reference/rr/rr/#hydrolib.core.rr.topology.models.NodeFile","text":"Represents the file with the RR node topology data.","title":"NodeFile"},{"location":"reference/rr/rr/#hydrolib.core.rr.topology.models.nodetypes_netter_to_rr","text":"Dictionary with nt mapped against the expected mt . Some model types mt do not have a related netter type; in that case the dict key is a dummy value of - .","title":"nodetypes_netter_to_rr"},{"location":"reference/rr/rr/#other-input-layers-foreseen-in-future-releases","text":"","title":"(Other input layers foreseen in future releases)"},{"location":"topics/dhydro_support/","text":"List of D-HYDRO functionalities and support in HYDROLIB-core \u00b6 Below is a list of D-HYDRO functionalities, grouped by kernel, and the current status of support inside hydrolib-core. Symbology \u00b6 : All toplevel file contents can be read/written. : Partial support, see notes. : No support yet, but may come in future. : No support foreseen. Out of scope. * indicates a scheduled release that is not out yet. DIMR \u00b6 Functionality Read Write Supported since API ref Notes DIMR dimr_config.xml 0.2.0 DIMR Critical bugfix for #127 . FM component 0.1.1 FMComponent RR component 0.1.1 RRComponent RTC component parallel MPI models 0.1.1 Component coupler elements 0.1.1 Coupler FM \u00b6 Functionality Read Write Supported since API ref Notes FM MDU file 0.1.1 FMModel Network file _net.nc 0.1.1 Mesh2d Structure file 0.1.1 StructureModel * Weir 0.1.1 Weir * Universal weir 0.1.1 UniversalWeir * Culvert 0.1.1 Culvert * Long culvert * Bridge 0.1.5 Bridge * Pump 0.1.1 Pump * Orifice 0.1.1 Orifice * Gate * General structure 0.2.0 GeneralStructure * Dambreak 0.1.5 Dambreak * Compound structure 0.1.1 Compound External forcings file External forcings file (old) 0.5.0 ExtOldModel External forcings file (new) 0.1.1 ExtModel * Boundary 0.1.1 Boundary * Lateral 0.1.1 Lateral * Meteo 0.5.0 Meteo .bc file 0.1.1 ForcingModel * timeSeries 0.1.1 TimeSeries * harmonic (-Correction) 0.1.1 Harmonic * astronomic (-Correction) 0.1.1 Astronomic * t3D 0.3.1 T3D * QHTable 0.1.1 QHTable * constant 0.1.1 Constant * vector quantities 0.3.1 VectorQuantityUnitPairs .tim file 0.5.0 TimModel Cross section files Moved to io.crosssections in 0.2.0 Cross section definition file 0.1.1 CrossDefModel * Circle 0.1.5 CircleCrsDef * Rectangle 0.1.5 RectangleCrsDef * Tabulated river 0.1.5 ZWRiverCrsDef * ZW (tabulated) 0.1.5 ZWCrsDef * XYZ 0.1.5 XYZCrsDef * YZ 0.1.5 YZCrsDef Cross section location file 0.1.1 CrossLocModel 1D roughness file 0.2.0 FrictionModel Storage node file 0.2.0 StorageNodeModel Spatial data files Initial and parameter field file 0.2.0 IniFieldModel 1D field INI files 0.2.0 OneDFieldModel Sample file 0.1.1 XYZModel Output Observation station file (.xyn) 0.5.0 XYNModel Observation station file (.ini) 0.3.0 ObservationPointModel Observation crosssection file (.pli) 0.5.0 PolyFile Observation crosssection file (.ini) 0.3.1 ObservationCrossSectionModel History file _his.nc Map file (old) Map file (UGRID) _map.nc Fourier input file Fourier output file _fou.nc via map file reader Class map file via map file reader RR \u00b6 Functionality Read Write Supported since API ref Notes RR Main sobek_3b.fnm 0.1.5 RainfallRunoffModel Used to be in hydrolib.core.io.fnm.models before 0.3.0 Rainfall .bui file 0.1.5 BuiModel Used to be in hydrolib.core.io.bui.models before 0.3.0 Topology layer Node file 3b_node.tp 0.2.0 NodeFile Link file 3b_link.tp 0.2.0 LinkFile (Table source available on: https://github.com/Deltares/HYDROLIB-core/blob/main/docs/topics/dhydro_support_hydrolib-core.xlsx )","title":"List of D-HYDRO functionalities and support in HYDROLIB-core"},{"location":"topics/dhydro_support/#list-of-d-hydro-functionalities-and-support-in-hydrolib-core","text":"Below is a list of D-HYDRO functionalities, grouped by kernel, and the current status of support inside hydrolib-core.","title":"List of D-HYDRO functionalities and support in HYDROLIB-core"},{"location":"topics/dhydro_support/#symbology","text":": All toplevel file contents can be read/written. : Partial support, see notes. : No support yet, but may come in future. : No support foreseen. Out of scope. * indicates a scheduled release that is not out yet.","title":"Symbology"},{"location":"topics/dhydro_support/#dimr","text":"Functionality Read Write Supported since API ref Notes DIMR dimr_config.xml 0.2.0 DIMR Critical bugfix for #127 . FM component 0.1.1 FMComponent RR component 0.1.1 RRComponent RTC component parallel MPI models 0.1.1 Component coupler elements 0.1.1 Coupler","title":"DIMR"},{"location":"topics/dhydro_support/#fm","text":"Functionality Read Write Supported since API ref Notes FM MDU file 0.1.1 FMModel Network file _net.nc 0.1.1 Mesh2d Structure file 0.1.1 StructureModel * Weir 0.1.1 Weir * Universal weir 0.1.1 UniversalWeir * Culvert 0.1.1 Culvert * Long culvert * Bridge 0.1.5 Bridge * Pump 0.1.1 Pump * Orifice 0.1.1 Orifice * Gate * General structure 0.2.0 GeneralStructure * Dambreak 0.1.5 Dambreak * Compound structure 0.1.1 Compound External forcings file External forcings file (old) 0.5.0 ExtOldModel External forcings file (new) 0.1.1 ExtModel * Boundary 0.1.1 Boundary * Lateral 0.1.1 Lateral * Meteo 0.5.0 Meteo .bc file 0.1.1 ForcingModel * timeSeries 0.1.1 TimeSeries * harmonic (-Correction) 0.1.1 Harmonic * astronomic (-Correction) 0.1.1 Astronomic * t3D 0.3.1 T3D * QHTable 0.1.1 QHTable * constant 0.1.1 Constant * vector quantities 0.3.1 VectorQuantityUnitPairs .tim file 0.5.0 TimModel Cross section files Moved to io.crosssections in 0.2.0 Cross section definition file 0.1.1 CrossDefModel * Circle 0.1.5 CircleCrsDef * Rectangle 0.1.5 RectangleCrsDef * Tabulated river 0.1.5 ZWRiverCrsDef * ZW (tabulated) 0.1.5 ZWCrsDef * XYZ 0.1.5 XYZCrsDef * YZ 0.1.5 YZCrsDef Cross section location file 0.1.1 CrossLocModel 1D roughness file 0.2.0 FrictionModel Storage node file 0.2.0 StorageNodeModel Spatial data files Initial and parameter field file 0.2.0 IniFieldModel 1D field INI files 0.2.0 OneDFieldModel Sample file 0.1.1 XYZModel Output Observation station file (.xyn) 0.5.0 XYNModel Observation station file (.ini) 0.3.0 ObservationPointModel Observation crosssection file (.pli) 0.5.0 PolyFile Observation crosssection file (.ini) 0.3.1 ObservationCrossSectionModel History file _his.nc Map file (old) Map file (UGRID) _map.nc Fourier input file Fourier output file _fou.nc via map file reader Class map file via map file reader","title":"FM"},{"location":"topics/dhydro_support/#rr","text":"Functionality Read Write Supported since API ref Notes RR Main sobek_3b.fnm 0.1.5 RainfallRunoffModel Used to be in hydrolib.core.io.fnm.models before 0.3.0 Rainfall .bui file 0.1.5 BuiModel Used to be in hydrolib.core.io.bui.models before 0.3.0 Topology layer Node file 3b_node.tp 0.2.0 NodeFile Link file 3b_link.tp 0.2.0 LinkFile (Table source available on: https://github.com/Deltares/HYDROLIB-core/blob/main/docs/topics/dhydro_support_hydrolib-core.xlsx )","title":"RR"},{"location":"topics/loadsave/","text":"Loading and Saving within HYDROLIB-core \u00b6 This article describes the architectural choices of saving and loading, if you are looking for how to save, please refer to the tutorials. The motivation of HYDROLIB-core is to provide a python library to interact with the D-HYDRO suite files. These files generally form a sort of tree structure, with a single root model (generally a DIMR or an FM model), and different layers of child models which are referenced in their parent models. These child models can either be referenced relative to their parent models or with absolute file paths. This leads to potentially complex model structures, which need to be read and written correctly by HYDROLIB-core without any changes to either the contents or the structure. This article discusses the architectural choices made when designing the read and write capabalities, as well as the considerations that should be taken when implementing your own models. As such we will discuss the following topics: Motivation: HYDROLIB-core should not adjust files when reading and writing Structure of Models Loading Models: Resolving the tree structure with the FileLoadContext Saving Models: Traversing the model tree with the ModelTreeTraverser Extensions: Caveats to ensure your model plays nice with HYDROLIB-core Motivation: HYDROLIB-core should not adjust files when reading and writing \u00b6 When implementing the model read and write behaviour of HYDROLIB-core, the main design choice is to ensure models are read and written as is. Properties should not be adjusted nor dropped when reading or writing (unless there is a very clear reason to do so). This behaviour should extend to the way the tree structure of the models is handled. Therefor, file paths, stored in the filepath property, which are not explicitly set to be absolute are kept relative and resolved while reading or writing. This has the drawback that the file location of a child model is not explicitly defined without the root model it is part of. Within the current implementation, child models have no reference to their parent. This simplifies the bookkeeping when building models in memory, however it also means that it is not possible to resolve the absolute path of a child model without also providing the root model it is part of. This behaviour is further documented in the following sections. In order to alleviate this shortcoming, each file model internally keeps track of its resolved save location, which can be explicitly synchronized with the file path of the root model, if this is required. Loading Models: Resolving the tree structure with the FileLoadContext \u00b6 In order to load a model from disk, we need to call the appropriate constructor with a file path to an existing model file. The constructor will then ensure the model, and its child models are read. Multiple references to the same sub-model will reference the same sub-model after reading. Current Behaviour: Root models are read through the constructor while caching sub-models \u00b6 Currently, a model is loaded by calling the constructor with the filepath of the input file. HYDROLIB-core will then load the model as well as any children. Every child will only be read once, multiple references to the same child in the input files will result in references to the same child model in memory. When reading the model and its children, the file structure will be kept intact. Any models with absolute paths will still reference the same absolute paths, while models with relative paths will also have the same relative paths as within the original file. Architectural Choices: The tree structure is resolved with the FileLoadContext \u00b6 In order to properly resolve the model tree, we need to be able to keep track of the current parent of a model, as well as a way to store and retrieve read models. Both of these tasks are handled by the FileLoadContext . The context can be used to resolve relative paths by keeping track of the current parent folder of a model. It also provides a cache for read models, which ensures files are not read more than once. A single FileLoadContext is created at the start of the constructor of the root model as a context variable. Subsequent child models can then reference this FileLoadContext , by retrieving this same FileLoadContext . A convenience context manager is provided through the file_load_context() method in the basemodel.py . The constructor of the filepath performs the following tasks: Request the context. Register itself within the model cache with its file path. Store the absolute file path anchor (i.e. the absolute path to its parent) Resolve its absolute path, to read from. Update the current parent directory. Read all the model data including sub-models. Remove itself as a parent directory. Because the constructor recursively reads child models, and the data is only read after the current parent directory has been updated, the child models will correctly resolve their resolve their relative paths. The FileModel further overrides its __new__ . During the __new__ call, it will verify if the current (resolved) filepath which is being read, has already been defined in the file model cache. If it is, then this instance will be returned, instead of creating a new instance through the __init__ . This ensures no duplicates are created. Saving Models: Traversing the model tree with the ModelTreeTraverser \u00b6 Currently, the save function on the FileModel offers the following options: filepath : Allows the user to set a new file path. If none is defined, the current file path will be used. recurse : A flag indicating whether only this model needs to be saved, or also it child models. As such it is possible to store both individual models, as well as model trees. When saving a model, it will be stored at the save_location . If recurse is true, then the child model will be evaluated with regards to the root model. This may lead to some inconsistencies, especially with the deprecated pathsRelativeToParent set to false in the FlowFM model. As such care needs to be taken by the user. The save_location of relative child models will NOT be automatically updated when the parent filepath is updated. If such an update is required the user is expected to call synchronize_filepaths on the parent model. ModelTreeTraverser \u00b6 For writing the models to file, as well as other operations, we need to be able to traverse the model tree. In order to do so, the ModelTreeTraverser is provided. It can be configured with the following 4 functions: should_traverse : Evaluates whether to traverse to the provided BaseModel. should_execute : Determines whether the traverse functions are executed for the given model. pre_traverse_func : Function called with the current model before traversal into the children, i.e. top-down behaviour. post_traverse_func : Function called with the current model after traversal into the children, i.e. bottom-up behaviour. All functions receive an accumulator, which flows through the program and is finally returned to the caller. This can be used to store state in between calls to traverse or to build an output value while traversing the model tree. Saving a complete model tree \u00b6 In order to store a model as well as its children, we need to perform the following tasks. Ensure the file paths of both the model and all of its children are set. Save the the models and its children recursively. We need to ensure all file paths are set before we store the models, in order to resolve the actual file paths during the save operation. As such these two operations are done in separate steps. Both of these tasks make use of the ModelTreeTraverser . It will traverse through any immediate file link model, and execute the pre and post functions for any file link. In case of task 1, it will generate the file paths if none is set. The save traversal uses the pre and post traverse functions to maintain the parent path used to resolve the relative file paths of any models. The post function is further used to actually write the model to file through a dedicated _save function. Saving a sub-tree relative to some model tree \u00b6 Saving a sub tree is in principle the same as calling save on the root model, but only a child model. One thing that should be taken into account is, the save is called relative to the current value in save_location . As such if changes were made to the filepath of a parent model, synchronize_filepaths should be called on the root model. Saving individual models without their children \u00b6 An individual model can be saved with the save and recurse set to False (i.e. the default behaviour). When this is done, only the model on which save was called will be written to disk at the current save_location . Exporting / Save as \u00b6 Exporting is currently not implemented, but will be as part of issue #170 . Inheritance hierachy of FileModels: SerializableFileModels and DiskOnlyFileModels \u00b6 The FileModel is the abstract base class for any file model. It provides the logic to manage the file paths as well as the common logic to load and save models. In order to do so, it requires child classes to implement a _save and a _load method. Two child classes have been defined which extend the FileModel : ParsableFileModel : Abstract class which defines a FileModel with a serializer and parser. This is the base model used by most in-memory models. DiskOnlyFileModel : A generic file model which does not read data into memory but does copy the underlying file when a parent FileModel is saved recursively. ParsableFileModel \u00b6 The ParsableFileModel defines an abstract base class for in-memory models, it does so by requiring child classes to define a parser, to read input files, and a serializer, to write the data again. This forms the basis for most of the in-memory file models. DiskOnlyFileModel \u00b6 The DiskOnlyFileModel provides a file model implementation for files which do not have a representation in HYDROLIB.Core (yet). The DiskOnlyFileModel ensures the underlying file, specified with the filepath of the FileModel , is copied when a parent model is saved recursively. It does so by maintaining an internal source file path, which is initialized at construction of the DiskOnlyFileModel . When a DiskOnlyFileModel is saved, the underlying file is copied from this internal source file path to the new target path. If the file at the source file model does not exist, or the target path is invalid, no file is copied. Lastly, regardless of whether a file was copied, the internal source file path is updated. Extensions: Caveats to ensure your model plays nice with HYDROLIB-core \u00b6 In the most common case, all of the file reading and writing is handled in the FileModel as such, just inheriting from the FileModel and providing the required parser and setting the _parser and _serializer will be enough to ensure your model works as expected. There might be however some exceptions to your model that require additional configuration. The file model provides several hooks for this: For loading: _post_init_load : function called after a model is initialised but before the current FileLoadContext is changed. This allows the user to put any actions here which require a FileLoadContext . Examples of this can be found in the DIMR and NetworkModel classes. Overwrite __init__ : We can overwrite the __init__ of a child the FileModel however some care needs to be taken in this case. In particular the __super__ needs to be called in order to ensure the model is loaded appropriately. Furthermore, if the FileLoadContext is required within the __init__ , the file_load_context should be called before __super__ : def __init__ ( self , ... ): with file_load_context () as context : __super__ () . __init__ () ... # your code using the context ... For saving: _save : provides the save functionality called by the recursive saving of models. Overwriting this will allow you complete control over how the model is saved. An example of this can be found in the NetworkFile . _serialize : provides the method to serialize your model. This can be overwritten in case a more specialised serialization is required, for example as done in IniBasedModel children. self._resolved_filepath : will provide you with a resolved absolute version of the filepath . This only works in the context of _save and _serialize , as it relies on the context being started in the save method.","title":"Loading and Saving within HYDROLIB-core"},{"location":"topics/loadsave/#loading-and-saving-within-hydrolib-core","text":"This article describes the architectural choices of saving and loading, if you are looking for how to save, please refer to the tutorials. The motivation of HYDROLIB-core is to provide a python library to interact with the D-HYDRO suite files. These files generally form a sort of tree structure, with a single root model (generally a DIMR or an FM model), and different layers of child models which are referenced in their parent models. These child models can either be referenced relative to their parent models or with absolute file paths. This leads to potentially complex model structures, which need to be read and written correctly by HYDROLIB-core without any changes to either the contents or the structure. This article discusses the architectural choices made when designing the read and write capabalities, as well as the considerations that should be taken when implementing your own models. As such we will discuss the following topics: Motivation: HYDROLIB-core should not adjust files when reading and writing Structure of Models Loading Models: Resolving the tree structure with the FileLoadContext Saving Models: Traversing the model tree with the ModelTreeTraverser Extensions: Caveats to ensure your model plays nice with HYDROLIB-core","title":"Loading and Saving within HYDROLIB-core"},{"location":"topics/loadsave/#motivation-hydrolib-core-should-not-adjust-files-when-reading-and-writing","text":"When implementing the model read and write behaviour of HYDROLIB-core, the main design choice is to ensure models are read and written as is. Properties should not be adjusted nor dropped when reading or writing (unless there is a very clear reason to do so). This behaviour should extend to the way the tree structure of the models is handled. Therefor, file paths, stored in the filepath property, which are not explicitly set to be absolute are kept relative and resolved while reading or writing. This has the drawback that the file location of a child model is not explicitly defined without the root model it is part of. Within the current implementation, child models have no reference to their parent. This simplifies the bookkeeping when building models in memory, however it also means that it is not possible to resolve the absolute path of a child model without also providing the root model it is part of. This behaviour is further documented in the following sections. In order to alleviate this shortcoming, each file model internally keeps track of its resolved save location, which can be explicitly synchronized with the file path of the root model, if this is required.","title":"Motivation: HYDROLIB-core should not adjust files when reading and writing"},{"location":"topics/loadsave/#loading-models-resolving-the-tree-structure-with-the-fileloadcontext","text":"In order to load a model from disk, we need to call the appropriate constructor with a file path to an existing model file. The constructor will then ensure the model, and its child models are read. Multiple references to the same sub-model will reference the same sub-model after reading.","title":"Loading Models: Resolving the tree structure with the FileLoadContext"},{"location":"topics/loadsave/#current-behaviour-root-models-are-read-through-the-constructor-while-caching-sub-models","text":"Currently, a model is loaded by calling the constructor with the filepath of the input file. HYDROLIB-core will then load the model as well as any children. Every child will only be read once, multiple references to the same child in the input files will result in references to the same child model in memory. When reading the model and its children, the file structure will be kept intact. Any models with absolute paths will still reference the same absolute paths, while models with relative paths will also have the same relative paths as within the original file.","title":"Current Behaviour: Root models are read through the constructor while caching sub-models"},{"location":"topics/loadsave/#architectural-choices-the-tree-structure-is-resolved-with-the-fileloadcontext","text":"In order to properly resolve the model tree, we need to be able to keep track of the current parent of a model, as well as a way to store and retrieve read models. Both of these tasks are handled by the FileLoadContext . The context can be used to resolve relative paths by keeping track of the current parent folder of a model. It also provides a cache for read models, which ensures files are not read more than once. A single FileLoadContext is created at the start of the constructor of the root model as a context variable. Subsequent child models can then reference this FileLoadContext , by retrieving this same FileLoadContext . A convenience context manager is provided through the file_load_context() method in the basemodel.py . The constructor of the filepath performs the following tasks: Request the context. Register itself within the model cache with its file path. Store the absolute file path anchor (i.e. the absolute path to its parent) Resolve its absolute path, to read from. Update the current parent directory. Read all the model data including sub-models. Remove itself as a parent directory. Because the constructor recursively reads child models, and the data is only read after the current parent directory has been updated, the child models will correctly resolve their resolve their relative paths. The FileModel further overrides its __new__ . During the __new__ call, it will verify if the current (resolved) filepath which is being read, has already been defined in the file model cache. If it is, then this instance will be returned, instead of creating a new instance through the __init__ . This ensures no duplicates are created.","title":"Architectural Choices: The tree structure is resolved with the FileLoadContext"},{"location":"topics/loadsave/#saving-models-traversing-the-model-tree-with-the-modeltreetraverser","text":"Currently, the save function on the FileModel offers the following options: filepath : Allows the user to set a new file path. If none is defined, the current file path will be used. recurse : A flag indicating whether only this model needs to be saved, or also it child models. As such it is possible to store both individual models, as well as model trees. When saving a model, it will be stored at the save_location . If recurse is true, then the child model will be evaluated with regards to the root model. This may lead to some inconsistencies, especially with the deprecated pathsRelativeToParent set to false in the FlowFM model. As such care needs to be taken by the user. The save_location of relative child models will NOT be automatically updated when the parent filepath is updated. If such an update is required the user is expected to call synchronize_filepaths on the parent model.","title":"Saving Models: Traversing the model tree with the ModelTreeTraverser"},{"location":"topics/loadsave/#modeltreetraverser","text":"For writing the models to file, as well as other operations, we need to be able to traverse the model tree. In order to do so, the ModelTreeTraverser is provided. It can be configured with the following 4 functions: should_traverse : Evaluates whether to traverse to the provided BaseModel. should_execute : Determines whether the traverse functions are executed for the given model. pre_traverse_func : Function called with the current model before traversal into the children, i.e. top-down behaviour. post_traverse_func : Function called with the current model after traversal into the children, i.e. bottom-up behaviour. All functions receive an accumulator, which flows through the program and is finally returned to the caller. This can be used to store state in between calls to traverse or to build an output value while traversing the model tree.","title":"ModelTreeTraverser"},{"location":"topics/loadsave/#saving-a-complete-model-tree","text":"In order to store a model as well as its children, we need to perform the following tasks. Ensure the file paths of both the model and all of its children are set. Save the the models and its children recursively. We need to ensure all file paths are set before we store the models, in order to resolve the actual file paths during the save operation. As such these two operations are done in separate steps. Both of these tasks make use of the ModelTreeTraverser . It will traverse through any immediate file link model, and execute the pre and post functions for any file link. In case of task 1, it will generate the file paths if none is set. The save traversal uses the pre and post traverse functions to maintain the parent path used to resolve the relative file paths of any models. The post function is further used to actually write the model to file through a dedicated _save function.","title":"Saving a complete model tree"},{"location":"topics/loadsave/#saving-a-sub-tree-relative-to-some-model-tree","text":"Saving a sub tree is in principle the same as calling save on the root model, but only a child model. One thing that should be taken into account is, the save is called relative to the current value in save_location . As such if changes were made to the filepath of a parent model, synchronize_filepaths should be called on the root model.","title":"Saving a sub-tree relative to some model tree"},{"location":"topics/loadsave/#saving-individual-models-without-their-children","text":"An individual model can be saved with the save and recurse set to False (i.e. the default behaviour). When this is done, only the model on which save was called will be written to disk at the current save_location .","title":"Saving individual models without their children"},{"location":"topics/loadsave/#exporting-save-as","text":"Exporting is currently not implemented, but will be as part of issue #170 .","title":"Exporting / Save as"},{"location":"topics/loadsave/#inheritance-hierachy-of-filemodels-serializablefilemodels-and-diskonlyfilemodels","text":"The FileModel is the abstract base class for any file model. It provides the logic to manage the file paths as well as the common logic to load and save models. In order to do so, it requires child classes to implement a _save and a _load method. Two child classes have been defined which extend the FileModel : ParsableFileModel : Abstract class which defines a FileModel with a serializer and parser. This is the base model used by most in-memory models. DiskOnlyFileModel : A generic file model which does not read data into memory but does copy the underlying file when a parent FileModel is saved recursively.","title":"Inheritance hierachy of FileModels: SerializableFileModels and DiskOnlyFileModels"},{"location":"topics/loadsave/#parsablefilemodel","text":"The ParsableFileModel defines an abstract base class for in-memory models, it does so by requiring child classes to define a parser, to read input files, and a serializer, to write the data again. This forms the basis for most of the in-memory file models.","title":"ParsableFileModel"},{"location":"topics/loadsave/#diskonlyfilemodel","text":"The DiskOnlyFileModel provides a file model implementation for files which do not have a representation in HYDROLIB.Core (yet). The DiskOnlyFileModel ensures the underlying file, specified with the filepath of the FileModel , is copied when a parent model is saved recursively. It does so by maintaining an internal source file path, which is initialized at construction of the DiskOnlyFileModel . When a DiskOnlyFileModel is saved, the underlying file is copied from this internal source file path to the new target path. If the file at the source file model does not exist, or the target path is invalid, no file is copied. Lastly, regardless of whether a file was copied, the internal source file path is updated.","title":"DiskOnlyFileModel"},{"location":"topics/loadsave/#extensions-caveats-to-ensure-your-model-plays-nice-with-hydrolib-core","text":"In the most common case, all of the file reading and writing is handled in the FileModel as such, just inheriting from the FileModel and providing the required parser and setting the _parser and _serializer will be enough to ensure your model works as expected. There might be however some exceptions to your model that require additional configuration. The file model provides several hooks for this: For loading: _post_init_load : function called after a model is initialised but before the current FileLoadContext is changed. This allows the user to put any actions here which require a FileLoadContext . Examples of this can be found in the DIMR and NetworkModel classes. Overwrite __init__ : We can overwrite the __init__ of a child the FileModel however some care needs to be taken in this case. In particular the __super__ needs to be called in order to ensure the model is loaded appropriately. Furthermore, if the FileLoadContext is required within the __init__ , the file_load_context should be called before __super__ : def __init__ ( self , ... ): with file_load_context () as context : __super__ () . __init__ () ... # your code using the context ... For saving: _save : provides the save functionality called by the recursive saving of models. Overwriting this will allow you complete control over how the model is saved. An example of this can be found in the NetworkFile . _serialize : provides the method to serialize your model. This can be overwritten in case a more specialised serialization is required, for example as done in IniBasedModel children. self._resolved_filepath : will provide you with a resolved absolute version of the filepath . This only works in the context of _save and _serialize , as it relies on the context being started in the save method.","title":"Extensions: Caveats to ensure your model plays nice with HYDROLIB-core"},{"location":"topics/principles/","text":"First principles \u00b6 hydrolib-core is structured around the input and output files (I/O) of the DHYDRO suite. Inheritance/file handling \u00b6 Model setups often consist of different files, many implicitly linked to each other. HYDROLIB makes these links explicit, by recursively loading all child configuration files. For example, when parsing a DIMR file, one could happen upon a reference to an MDU file, which contain references to other files, such as cross sections, etc. >>> dimr = DIMR ( filepath = Path ( test_data_dir / \"dimr_config.xml\" )) You can see this tree structure if you call show_tree . >>> dimr . show_tree () DIMR represented by dimr_config . xml . RRComponent FMComponent \u221f FMModel represented by FlowFM . mdu . \u221f Geometry \u221f StructureModel represented by structures . ini . \u221f CrossDefModel represented by crsdef . ini . \u221f CrossLocModel represented by crsloc . ini . \u221f FrictionModel represented by roughness - Main . ini . \u221f FrictionModel represented by roughness - Sewer1 . ini . \u221f FrictionModel represented by roughness - Sewer2 . ini . \u221f ExternalForcing \u221f ExtModel represented by FlowFM_bnd . ext . \u221f Boundary \u221f ForcingModel represented by FlowFM_boundaryconditions1d . bc . \u221f Boundary \u221f ForcingModel represented by FlowFM_boundaryconditions1d . bc . \u221f Boundary \u221f ForcingModel represented by FlowFM_boundaryconditions1d . bc . Program flow while recursively creating FileModels \u00b6 In short: \u00b6 The file resolver and the model cache are stored in context variable context_file_loading , such that referenced files can be found. During loading, the parsed data from files are cached in the FileLoadContext to ensure multiple references to the same model will not result in duplicate parsing and instances. Pydantic first calls the FileModel.validate and then the initializer ( FileModel.__new__ and FileModel.__init__ ). In detail: \u00b6 User initializes a new root FileModel from file : FileModel.__new__(cls, filepath: str/Path) Returns the result of the default __new__ function FileModel.__init__(self, filepath: str/Path) self holds the FileModel instance that was returned in step 1. filepath is holds the file path to the root file. Registers this model in the FileLoadContext with the file path. Resolves the absolute path to this model. Adds the folder of this model to the file resolver, such that the children can be resolved as well. Loads the data ( dict ) from the file. Initialize self with the data. Pydantic tries to convert the data to objects, a.o. sub FileModels : FileModel.validate(value: str) value holds a relative or absolute file path to the referenced file. If value is not an absolute file path, resolves the absolute path by using the FileLoadContext stored in the context_file_loading , previously set in step 2. Calls super().validate(value) with the file path stored in value . Pydantic create a new FileModel with the data : FileModel.__new__(cls, filepath: str) filepath holds the file path. If FileModel._file_models_cache already contains a FileModel instance with this filepath , returns the cached instance, Otherwise, returns the result of the default __new__ function. Repeat steps 2-4 Parsing and serializing INIBasedModels \u00b6 Parsing an INI file should be case-insensitive. To achieve this, the parsable field names of each INIBasedModel should be equal to the expected key in the file in lower case. Some property values are explicitly made case-insensitive for parsing as well. This applies to enum values and values that represent a specific type of INIBasedModel , such as the type property of a structure. To support this, custom validators are placed to compare the given value with the available known values. Structures are initialized based on the value in the type field. The value of this field of each subclass of a Structure is compared to the input and the subclass with the corresponding type is initialized. The serialization of an INIBasedModel to an INI file should respect certain casing rules (overriding the casing used by the user): - Property keys need to be \"lowerCamelCase\" - Section headers need to be \"UpperCamelCase\" To achieve this, each serializable field in a INIBasedModel has an alias. This alias will be written as property key to file. Each INIBasedModel that represents an INI section, has a field _header . The default value of this field will be written to file. Enum values and the values that represent a specific type of INIBasedModel will be serialized to file by how they are defined.","title":"First principles"},{"location":"topics/principles/#first-principles","text":"hydrolib-core is structured around the input and output files (I/O) of the DHYDRO suite.","title":"First principles"},{"location":"topics/principles/#inheritancefile-handling","text":"Model setups often consist of different files, many implicitly linked to each other. HYDROLIB makes these links explicit, by recursively loading all child configuration files. For example, when parsing a DIMR file, one could happen upon a reference to an MDU file, which contain references to other files, such as cross sections, etc. >>> dimr = DIMR ( filepath = Path ( test_data_dir / \"dimr_config.xml\" )) You can see this tree structure if you call show_tree . >>> dimr . show_tree () DIMR represented by dimr_config . xml . RRComponent FMComponent \u221f FMModel represented by FlowFM . mdu . \u221f Geometry \u221f StructureModel represented by structures . ini . \u221f CrossDefModel represented by crsdef . ini . \u221f CrossLocModel represented by crsloc . ini . \u221f FrictionModel represented by roughness - Main . ini . \u221f FrictionModel represented by roughness - Sewer1 . ini . \u221f FrictionModel represented by roughness - Sewer2 . ini . \u221f ExternalForcing \u221f ExtModel represented by FlowFM_bnd . ext . \u221f Boundary \u221f ForcingModel represented by FlowFM_boundaryconditions1d . bc . \u221f Boundary \u221f ForcingModel represented by FlowFM_boundaryconditions1d . bc . \u221f Boundary \u221f ForcingModel represented by FlowFM_boundaryconditions1d . bc .","title":"Inheritance/file handling"},{"location":"topics/principles/#program-flow-while-recursively-creating-filemodels","text":"","title":"Program flow while recursively creating FileModels"},{"location":"topics/principles/#in-short","text":"The file resolver and the model cache are stored in context variable context_file_loading , such that referenced files can be found. During loading, the parsed data from files are cached in the FileLoadContext to ensure multiple references to the same model will not result in duplicate parsing and instances. Pydantic first calls the FileModel.validate and then the initializer ( FileModel.__new__ and FileModel.__init__ ).","title":"In short:"},{"location":"topics/principles/#in-detail","text":"User initializes a new root FileModel from file : FileModel.__new__(cls, filepath: str/Path) Returns the result of the default __new__ function FileModel.__init__(self, filepath: str/Path) self holds the FileModel instance that was returned in step 1. filepath is holds the file path to the root file. Registers this model in the FileLoadContext with the file path. Resolves the absolute path to this model. Adds the folder of this model to the file resolver, such that the children can be resolved as well. Loads the data ( dict ) from the file. Initialize self with the data. Pydantic tries to convert the data to objects, a.o. sub FileModels : FileModel.validate(value: str) value holds a relative or absolute file path to the referenced file. If value is not an absolute file path, resolves the absolute path by using the FileLoadContext stored in the context_file_loading , previously set in step 2. Calls super().validate(value) with the file path stored in value . Pydantic create a new FileModel with the data : FileModel.__new__(cls, filepath: str) filepath holds the file path. If FileModel._file_models_cache already contains a FileModel instance with this filepath , returns the cached instance, Otherwise, returns the result of the default __new__ function. Repeat steps 2-4","title":"In detail:"},{"location":"topics/principles/#parsing-and-serializing-inibasedmodels","text":"Parsing an INI file should be case-insensitive. To achieve this, the parsable field names of each INIBasedModel should be equal to the expected key in the file in lower case. Some property values are explicitly made case-insensitive for parsing as well. This applies to enum values and values that represent a specific type of INIBasedModel , such as the type property of a structure. To support this, custom validators are placed to compare the given value with the available known values. Structures are initialized based on the value in the type field. The value of this field of each subclass of a Structure is compared to the input and the subclass with the corresponding type is initialized. The serialization of an INIBasedModel to an INI file should respect certain casing rules (overriding the casing used by the user): - Property keys need to be \"lowerCamelCase\" - Section headers need to be \"UpperCamelCase\" To achieve this, each serializable field in a INIBasedModel has an alias. This alias will be written as property key to file. Each INIBasedModel that represents an INI section, has a field _header . The default value of this field will be written to file. Enum values and the values that represent a specific type of INIBasedModel will be serialized to file by how they are defined.","title":"Parsing and serializing INIBasedModels"},{"location":"topics/pydantic/","text":"Pydantic \u00b6 Pydantic override \u00b6 We love using Pydantic , but we need have multiple overrides in place to enable specific functionality. This document tries to document these instances, as they are in essence exceptions to an otherwise well understood and documented architecture. BaseModel __init__ override \u00b6 We override de __init__ method to catch all validation errors and reissue them with an better error message. FileModel override \u00b6 We override both __new__ and __init__ of the FileModel to cache models from disk. The FileModel utilises the FileLoadContext to resolve relative paths and to retrieve models previously read as part of the loading of a root model. Specifically we also use it to load a filepath from disk. This mostly happens in validate , a Pydantic override, to make sure that if we initialize with a single unnamed argument (Pydantic only accepts keyword arguments) we try to parse it as a filepath. ForcingBase, Structure and CrossSectionDefinition validate override \u00b6 Validate is overriden to try to initialize the correct subclass of ForcingBase and CrossSectionDefinition, as discriminated unions do not work yet in Pydantic. I.e. if you specify Union{A, B} and A and B have clearly defined Literals it still can't choose whether to create A or B. The PR to fix this hasn't been merged yet. The code is duplicated in three places. INIBasedModel validate override \u00b6 In INIBasedModel we override validate to make sure we can flatten any Section input coming from the parser. Couldn't this be done in the parser? Structure Root validator explicitely checks subclass \u00b6 Because the validation behaviour is different for Compound , Dambreak etc. We might want to split these things once a new Pydantic release has been made that allows a root_validator to be overriden.","title":"Pydantic"},{"location":"topics/pydantic/#pydantic","text":"","title":"Pydantic"},{"location":"topics/pydantic/#pydantic-override","text":"We love using Pydantic , but we need have multiple overrides in place to enable specific functionality. This document tries to document these instances, as they are in essence exceptions to an otherwise well understood and documented architecture.","title":"Pydantic override"},{"location":"topics/pydantic/#basemodel-__init__-override","text":"We override de __init__ method to catch all validation errors and reissue them with an better error message.","title":"BaseModel __init__ override"},{"location":"topics/pydantic/#filemodel-override","text":"We override both __new__ and __init__ of the FileModel to cache models from disk. The FileModel utilises the FileLoadContext to resolve relative paths and to retrieve models previously read as part of the loading of a root model. Specifically we also use it to load a filepath from disk. This mostly happens in validate , a Pydantic override, to make sure that if we initialize with a single unnamed argument (Pydantic only accepts keyword arguments) we try to parse it as a filepath.","title":"FileModel override"},{"location":"topics/pydantic/#forcingbase-structure-and-crosssectiondefinition-validate-override","text":"Validate is overriden to try to initialize the correct subclass of ForcingBase and CrossSectionDefinition, as discriminated unions do not work yet in Pydantic. I.e. if you specify Union{A, B} and A and B have clearly defined Literals it still can't choose whether to create A or B. The PR to fix this hasn't been merged yet. The code is duplicated in three places.","title":"ForcingBase, Structure and CrossSectionDefinition validate override"},{"location":"topics/pydantic/#inibasedmodel-validate-override","text":"In INIBasedModel we override validate to make sure we can flatten any Section input coming from the parser. Couldn't this be done in the parser?","title":"INIBasedModel validate override"},{"location":"topics/pydantic/#structure-root-validator-explicitely-checks-subclass","text":"Because the validation behaviour is different for Compound , Dambreak etc. We might want to split these things once a new Pydantic release has been made that allows a root_validator to be overriden.","title":"Structure Root validator explicitely checks subclass"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/","text":"(function (global, factory) { typeof exports === 'object' && typeof module !== 'undefined' ? module.exports = factory() : typeof define === 'function' && define.amd ? define(factory) : (global = global || self, global.ClipboardCopyElement = factory()); }(this, function () { 'use strict'; function createNode(text) { const node = document.createElement('pre'); node.style.width = '1px'; node.style.height = '1px'; node.style.position = 'fixed'; node.style.top = '5px'; node.textContent = text; 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When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(0, 0, 0, 1); --jp-ui-font-color1: rgba(0, 0, 0, 0.87); --jp-ui-font-color2: rgba(0, 0, 0, 0.54); --jp-ui-font-color3: rgba(0, 0, 0, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color1: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color2: rgba(255, 255, 255, 0.7); --jp-ui-inverse-font-color3: rgba(255, 255, 255, 0.5); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(0, 0, 0, 1); --jp-content-font-color1: rgba(0, 0, 0, 0.87); --jp-content-font-color2: rgba(0, 0, 0, 0.54); --jp-content-font-color3: rgba(0, 0, 0, 0.38); --jp-content-link-color: var(--md-blue-700); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: white; --jp-layout-color1: white; --jp-layout-color2: var(--md-grey-200); --jp-layout-color3: var(--md-grey-400); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: #111111; --jp-inverse-layout-color1: var(--md-grey-900); --jp-inverse-layout-color2: var(--md-grey-800); --jp-inverse-layout-color3: var(--md-grey-700); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-900); --jp-brand-color1: var(--md-blue-700); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-900); --jp-accent-color1: var(--md-green-700); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-900); --jp-warn-color1: var(--md-orange-700); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-900); --jp-error-color1: var(--md-red-700); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-900); --jp-success-color1: var(--md-green-700); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-900); --jp-info-color1: var(--md-cyan-700); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--md-grey-100); --jp-cell-editor-border-color: var(--md-grey-300); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 0.5; --jp-cell-prompt-not-active-font-color: var(--md-grey-700); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: var(--md-blue-50); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: #fdd; --jp-rendermime-table-row-background: var(--md-grey-100); --jp-rendermime-table-row-hover-background: var(--md-light-blue-50); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.25); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color1); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.24); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--md-grey-300); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color1); --jp-input-hover-background: var(--jp-layout-color1); --jp-input-background: var(--md-grey-100); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: #d9d9d9; --jp-editor-selected-focused-background: #d7d4f0; --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: #008000; --jp-mirror-editor-atom-color: #88f; --jp-mirror-editor-number-color: #080; --jp-mirror-editor-def-color: #00f; --jp-mirror-editor-variable-color: var(--md-grey-900); --jp-mirror-editor-variable-2-color: #05a; --jp-mirror-editor-variable-3-color: #085; --jp-mirror-editor-punctuation-color: #05a; --jp-mirror-editor-property-color: #05a; --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ba2121; --jp-mirror-editor-string-2-color: #708; --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: #008000; --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: #170; --jp-mirror-editor-attribute-color: #00c; --jp-mirror-editor-header-color: blue; --jp-mirror-editor-quote-color: #090; --jp-mirror-editor-link-color: #00c; --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: white; /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.5; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(245, 200, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } [data-md-color-scheme=\"slate\"] .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ /* The dark theme shadows need a bit of work, but this will probably also require work on the core layout * colors used in the theme as well. */ --jp-shadow-base-lightness: 32; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-700); --jp-border-color1: var(--md-grey-700); --jp-border-color2: var(--md-grey-800); --jp-border-color3: var(--md-grey-900); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(255, 255, 255, 1); --jp-ui-font-color1: rgba(255, 255, 255, 0.87); --jp-ui-font-color2: rgba(255, 255, 255, 0.54); --jp-ui-font-color3: rgba(255, 255, 255, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(0, 0, 0, 1); --jp-ui-inverse-font-color1: rgba(0, 0, 0, 0.8); --jp-ui-inverse-font-color2: rgba(0, 0, 0, 0.5); --jp-ui-inverse-font-color3: rgba(0, 0, 0, 0.3); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(255, 255, 255, 1); --jp-content-font-color1: rgba(255, 255, 255, 1); --jp-content-font-color2: rgba(255, 255, 255, 0.7); --jp-content-font-color3: rgba(255, 255, 255, 0.5); --jp-content-link-color: var(--md-blue-300); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: #111111; --jp-layout-color1: var(--md-grey-900); --jp-layout-color2: var(--md-grey-800); --jp-layout-color3: var(--md-grey-700); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: white; --jp-inverse-layout-color1: white; --jp-inverse-layout-color2: var(--md-grey-200); --jp-inverse-layout-color3: var(--md-grey-400); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-700); --jp-brand-color1: var(--md-blue-500); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-700); --jp-accent-color1: var(--md-green-500); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-700); --jp-warn-color1: var(--md-orange-500); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-700); --jp-error-color1: var(--md-red-500); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-700); --jp-success-color1: var(--md-green-500); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-700); --jp-info-color1: var(--md-cyan-500); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--jp-layout-color1); --jp-cell-editor-border-color: var(--md-grey-700); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 1; --jp-cell-prompt-not-active-font-color: var(--md-grey-300); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: rgba(33, 150, 243, 0.24); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: rgba(244, 67, 54, 0.28); --jp-rendermime-table-row-background: var(--md-grey-900); --jp-rendermime-table-row-hover-background: rgba(3, 169, 244, 0.2); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.6); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color2); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.8); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--jp-layout-color0); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color0); --jp-input-hover-background: var(--jp-layout-color2); --jp-input-background: var(--md-grey-800); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: var(--jp-layout-color2); --jp-editor-selected-focused-background: rgba(33, 150, 243, 0.24); --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: var(--md-green-500); --jp-mirror-editor-atom-color: var(--md-blue-300); --jp-mirror-editor-number-color: var(--md-green-400); --jp-mirror-editor-def-color: var(--md-blue-600); --jp-mirror-editor-variable-color: var(--md-grey-300); --jp-mirror-editor-variable-2-color: var(--md-blue-400); --jp-mirror-editor-variable-3-color: var(--md-green-600); --jp-mirror-editor-punctuation-color: var(--md-blue-400); --jp-mirror-editor-property-color: var(--md-blue-400); --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ff7070; --jp-mirror-editor-string-2-color: var(--md-purple-300); --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: var(--md-green-600); --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: var(--md-green-700); --jp-mirror-editor-attribute-color: var(--md-blue-700); --jp-mirror-editor-header-color: var(--md-blue-500); --jp-mirror-editor-quote-color: var(--md-green-300); --jp-mirror-editor-link-color: var(--md-blue-700); --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: var(--md-grey-400); /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.6; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(255, 225, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* scrollbar related styles. Supports every browser except Edge. */ /* colors based on JetBrain's Darcula theme */ --jp-scrollbar-background-color: #3f4244; --jp-scrollbar-thumb-color: 88, 96, 97; /* need to specify thumb color as an RGB triplet */ --jp-scrollbar-endpad: 3px; /* the minimum gap between the thumb and the ends of a scrollbar */ /* hacks for setting the thumb shape. These do nothing in Firefox */ --jp-scrollbar-thumb-margin: 3.5px; /* the space in between the sides of the thumb and the track */ --jp-scrollbar-thumb-radius: 9px; /* set to a large-ish value for rounded endcaps on the thumb */ /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } :root{--md-red-50: #ffebee;--md-red-100: #ffcdd2;--md-red-200: #ef9a9a;--md-red-300: #e57373;--md-red-400: #ef5350;--md-red-500: #f44336;--md-red-600: #e53935;--md-red-700: #d32f2f;--md-red-800: #c62828;--md-red-900: #b71c1c;--md-red-A100: #ff8a80;--md-red-A200: #ff5252;--md-red-A400: #ff1744;--md-red-A700: #d50000;--md-pink-50: #fce4ec;--md-pink-100: #f8bbd0;--md-pink-200: #f48fb1;--md-pink-300: #f06292;--md-pink-400: #ec407a;--md-pink-500: #e91e63;--md-pink-600: #d81b60;--md-pink-700: #c2185b;--md-pink-800: 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#7986cb;--md-indigo-400: #5c6bc0;--md-indigo-500: #3f51b5;--md-indigo-600: #3949ab;--md-indigo-700: #303f9f;--md-indigo-800: #283593;--md-indigo-900: #1a237e;--md-indigo-A100: #8c9eff;--md-indigo-A200: #536dfe;--md-indigo-A400: #3d5afe;--md-indigo-A700: #304ffe;--md-blue-50: #e3f2fd;--md-blue-100: #bbdefb;--md-blue-200: #90caf9;--md-blue-300: #64b5f6;--md-blue-400: #42a5f5;--md-blue-500: #2196f3;--md-blue-600: #1e88e5;--md-blue-700: #1976d2;--md-blue-800: #1565c0;--md-blue-900: #0d47a1;--md-blue-A100: #82b1ff;--md-blue-A200: #448aff;--md-blue-A400: #2979ff;--md-blue-A700: #2962ff;--md-light-blue-50: #e1f5fe;--md-light-blue-100: #b3e5fc;--md-light-blue-200: #81d4fa;--md-light-blue-300: #4fc3f7;--md-light-blue-400: #29b6f6;--md-light-blue-500: #03a9f4;--md-light-blue-600: #039be5;--md-light-blue-700: #0288d1;--md-light-blue-800: #0277bd;--md-light-blue-900: #01579b;--md-light-blue-A100: #80d8ff;--md-light-blue-A200: #40c4ff;--md-light-blue-A400: #00b0ff;--md-light-blue-A700: #0091ea;--md-cyan-50: #e0f7fa;--md-cyan-100: #b2ebf2;--md-cyan-200: #80deea;--md-cyan-300: #4dd0e1;--md-cyan-400: #26c6da;--md-cyan-500: #00bcd4;--md-cyan-600: #00acc1;--md-cyan-700: #0097a7;--md-cyan-800: #00838f;--md-cyan-900: #006064;--md-cyan-A100: #84ffff;--md-cyan-A200: #18ffff;--md-cyan-A400: #00e5ff;--md-cyan-A700: #00b8d4;--md-teal-50: #e0f2f1;--md-teal-100: #b2dfdb;--md-teal-200: #80cbc4;--md-teal-300: #4db6ac;--md-teal-400: #26a69a;--md-teal-500: #009688;--md-teal-600: #00897b;--md-teal-700: #00796b;--md-teal-800: #00695c;--md-teal-900: #004d40;--md-teal-A100: #a7ffeb;--md-teal-A200: #64ffda;--md-teal-A400: #1de9b6;--md-teal-A700: #00bfa5;--md-green-50: #e8f5e9;--md-green-100: #c8e6c9;--md-green-200: #a5d6a7;--md-green-300: #81c784;--md-green-400: #66bb6a;--md-green-500: #4caf50;--md-green-600: #43a047;--md-green-700: #388e3c;--md-green-800: #2e7d32;--md-green-900: #1b5e20;--md-green-A100: #b9f6ca;--md-green-A200: #69f0ae;--md-green-A400: #00e676;--md-green-A700: #00c853;--md-light-green-50: #f1f8e9;--md-light-green-100: #dcedc8;--md-light-green-200: #c5e1a5;--md-light-green-300: #aed581;--md-light-green-400: #9ccc65;--md-light-green-500: #8bc34a;--md-light-green-600: #7cb342;--md-light-green-700: #689f38;--md-light-green-800: #558b2f;--md-light-green-900: #33691e;--md-light-green-A100: #ccff90;--md-light-green-A200: #b2ff59;--md-light-green-A400: #76ff03;--md-light-green-A700: #64dd17;--md-lime-50: #f9fbe7;--md-lime-100: #f0f4c3;--md-lime-200: #e6ee9c;--md-lime-300: #dce775;--md-lime-400: #d4e157;--md-lime-500: #cddc39;--md-lime-600: #c0ca33;--md-lime-700: #afb42b;--md-lime-800: #9e9d24;--md-lime-900: #827717;--md-lime-A100: #f4ff81;--md-lime-A200: #eeff41;--md-lime-A400: #c6ff00;--md-lime-A700: #aeea00;--md-yellow-50: #fffde7;--md-yellow-100: #fff9c4;--md-yellow-200: #fff59d;--md-yellow-300: #fff176;--md-yellow-400: #ffee58;--md-yellow-500: #ffeb3b;--md-yellow-600: #fdd835;--md-yellow-700: #fbc02d;--md-yellow-800: #f9a825;--md-yellow-900: #f57f17;--md-yellow-A100: #ffff8d;--md-yellow-A200: #ffff00;--md-yellow-A400: #ffea00;--md-yellow-A700: #ffd600;--md-amber-50: #fff8e1;--md-amber-100: #ffecb3;--md-amber-200: #ffe082;--md-amber-300: #ffd54f;--md-amber-400: #ffca28;--md-amber-500: #ffc107;--md-amber-600: #ffb300;--md-amber-700: #ffa000;--md-amber-800: #ff8f00;--md-amber-900: #ff6f00;--md-amber-A100: #ffe57f;--md-amber-A200: #ffd740;--md-amber-A400: #ffc400;--md-amber-A700: #ffab00;--md-orange-50: #fff3e0;--md-orange-100: #ffe0b2;--md-orange-200: #ffcc80;--md-orange-300: #ffb74d;--md-orange-400: #ffa726;--md-orange-500: #ff9800;--md-orange-600: #fb8c00;--md-orange-700: #f57c00;--md-orange-800: #ef6c00;--md-orange-900: #e65100;--md-orange-A100: #ffd180;--md-orange-A200: #ffab40;--md-orange-A400: #ff9100;--md-orange-A700: #ff6d00;--md-deep-orange-50: #fbe9e7;--md-deep-orange-100: #ffccbc;--md-deep-orange-200: #ffab91;--md-deep-orange-300: #ff8a65;--md-deep-orange-400: #ff7043;--md-deep-orange-500: 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sourceMappingURL=mkdocs-jupyter.css.map*/ init_mathjax = function() { if (window.MathJax) { // MathJax loaded MathJax.Hub.Config({ TeX: { equationNumbers: { autoNumber: \"AMS\", useLabelIds: true } }, tex2jax: { inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ], displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ], processEscapes: true, processEnvironments: true }, displayAlign: 'center', CommonHTML: { linebreaks: { automatic: true } } }); MathJax.Hub.Queue([\"Typeset\", MathJax.Hub]); } } init_mathjax(); Tutorial Delft3D FM 1D2D fluvial flood model of Magdalena river \u00b6 This notebook is an introduction on how to use HYDROLIB-core functionalities to create and adjust a Delft3D FM Suite 1D2D fluvial flood model of the Magdalena river in Columbia. First a 1D river model of the Magdalena river and Canal del Dique will be created, shown in the left figure. This model will be extended with a 2D Flexible Mesh, with a uniform roughness field. Adding a DTM on that 2D mesh is currently not part of this tutorial, but normally this is of course indispensible to mimic the fluvial flood patterns. Running the model or importing the model in the Delft3D FM Suite 1D2D is not shown in this tutorial. Note that the model and tutorial are created for educational purposes and consist partially of fictive/unvalidated model data. HYDROLIB-core is the core library of Python wrappers around the D-HYDRO Suite 1D2D model files (input and output) and model engines (kernel libraries). HYDROLIB is a Python package with tools for pre-processing, post-processing and analysis of hydrodynamical data and simulation results, currently focused on Delft3D Suite 1D2D. HYDROLIB builds upon the basic HYDROLIB-core functionalities. The goal of this tutorial is to familiarize modelers with how to apply HYDROLIB-core functionalities in their modelling procedures for building new models or adjusting existing models. As mentioned above, you will create an 1D2D fluvial flood model from scratch using the D-Flow FM HYDROLIB-core functionalities and the underlying functions from mesh generation ( MeshKernelPy ). The building of the model is done by the following steps Loading libraries Connect to data folder Create empty D-Flow FM model Read branches Create computational grid Add cross-sections Add roughness Add boundary conditions Add initial conditions Add a weir to the model Save 1D model Create 2D flexible mesh Add 2D DTM to model Save 1D2D model Note that HYDROLIB-core also contains functionalities to setup lumped rainfall runoff models ( D-RR ) and to apply real-time control at structures ( D-RTC ), but these are not covered in this tutorial. Installation \u00b6 To run this notebook a simple Python environment with the following packages is required: - python=3.9 - pandas - geopandas - pyogrio - matplotlib - numpy - jupyter - xarray - openpyxl - pip - pip: - hydrolib-core==0.3.1 - meshkernel==1.0.0 Note that all participants received an e-mail to download the material from the Deltares download portal and to create a Conda environment with the packages automatically installed from environment.yml . Furthermore, a dummy model is provided at the download portal to test the environment. Tips for working in the Jupyter Notebook: \u00b6 Tab : Auto-complete on code Shift + Tab : Tooltip Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell Ctrl + Shift + P : Open command palette Let's get started! Loading libraries \u00b6 Several Python packages are required to run the notebook. These packages are imported below. Please consult the HYDROLIB-core documentation if you want to import additional HYDROLIB-core functionalities later. The import of HYDROLIB-core packages will be simplied in future HYDROLIB-core release (> 0.3.1) In [ ]: Copied! # basic packages import numpy as np import pandas as pd import matplotlib.pyplot as plt # I/O from pathlib import Path # vector/polygon packages import geopandas as gpd from shapely import wkt from shapely.geometry import box # HYDROLIB-core libraries from hydrolib.core.mdu.models import FMModel , AutoStartOption from hydrolib.core.net.models import * from hydrolib.core.crosssection.models import CrossLocModel , CrossDefModel , CrossSection , YZCrsDef from hydrolib.core.friction.models import * from hydrolib.core.bc.models import * from hydrolib.core.ext.models import * from hydrolib.core.inifield.models import * from hydrolib.core.onedfield.models import * from hydrolib.core.structure.models import Weir , FlowDirection , StructureModel # basic packages import numpy as np import pandas as pd import matplotlib.pyplot as plt # I/O from pathlib import Path # vector/polygon packages import geopandas as gpd from shapely import wkt from shapely.geometry import box # HYDROLIB-core libraries from hydrolib.core.mdu.models import FMModel, AutoStartOption from hydrolib.core.net.models import * from hydrolib.core.crosssection.models import CrossLocModel, CrossDefModel, CrossSection, YZCrsDef from hydrolib.core.friction.models import * from hydrolib.core.bc.models import * from hydrolib.core.ext.models import * from hydrolib.core.inifield.models import * from hydrolib.core.onedfield.models import * from hydrolib.core.structure.models import Weir, FlowDirection, StructureModel Connect to data \u00b6 The data for this tutorial is provided via the download portal. EX1 : Change the inputdir to the path of your unzipped data folder. In [ ]: Copied! # Get the directory of the notebook location root = Path . cwd () # Answer EX1 # Specify the path to the data folder inputdir = # Get the directory of the notebook location root = Path.cwd() # Answer EX1 # Specify the path to the data folder inputdir = Create empty D-Flow FM model \u00b6 To start a model from scratch you need to create first an empty model without data and assign a filepath to the model. In this case a D-Flow FM model is created. The MDU file (master definition file) is the main file of the D-Flow FM model. This is created with the FMModel() function. The fm model object is only created in memory. To save the actual model file, call fm.save() . EX2 : Set the outputdir of the model and give it a name. Verify that an MDU file has been written in your output directory. In [ ]: Copied! # Create empty D-Flow FM model fm = FMModel () # Answer EX2 # Assign filepath to the D-Flow FM model outputdir = fm . filepath = outputdir / 'Magdalena_1D.mdu' fm . save () # Create empty D-Flow FM model fm = FMModel() # Answer EX2 # Assign filepath to the D-Flow FM model outputdir = fm.filepath = outputdir / 'Magdalena_1D.mdu' fm.save() PART 1: Set up a 1D Delft3D FM model \u00b6 In this part we will build up the complete 1D model schematization step by step. At the end you should have a complete set of model input files for a 1D calculation. Read branches \u00b6 The model will include the lower part of the Magadalena from Cordoba Teton to the river mouth Baranquilla and the Canal del Dique. EX2 : Please investigate the branches variable and answer the following questions for yourself: How many river branches does the model have? What are their names? Which friction type and values are used for each branch? In [ ]: Copied! # Read the branches branches = gpd . read_file ( filename = inputdir / 'branches_Branches.shp' ) # Answer EX3 # Read the branches branches = gpd.read_file(filename = inputdir / 'branches_Branches.shp') # Answer EX3 Create 1D computational grid \u00b6 In the previous step you read the geometry and attributes of the branches into the notebook. These branches will become the network input to our FMModel . The cell below shows how the geometry and name of the branches are assigned to the network. In addition a 1D computational grid ( mesh1d ) with gridpoint every 1000 meter is created on top of this network. Since the network does not yet exist, you need to create an empty network model . Assign the geometry of the branches followed by the generation of the computational grid. The network model should be added to the D-Flow FM model ( fm variable in this notebook) as network in the netfile parameter in the section geometry . Note that you have to specify a filepath for the networkfile. Note that the network model can consist of 1D, 2D flexible mesh ( mesh2d ) and 1D2D links ( links1d2d ). In [ ]: Copied! # Specify 1D computational grid distance dx = 1000.0 # Create an empty network network = Network () # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch in branches . iterrows (): xy = np . transpose ( branch . geometry . xy ) branch_new = Branch ( geometry = xy ) branch_new . generate_nodes ( mesh1d_edge_length = dx ) network . mesh1d_add_branch ( branch_new , name = branch . Name ) # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm . geometry . netfile . network = network fm . geometry . netfile . filepath = \"FlowFM_net.nc\" # Specify 1D computational grid distance dx = 1000.0 # Create an empty network network = Network() # Assign geometry of the branches and generate the computational grid on top of the branches. for index,branch in branches.iterrows(): xy = np.transpose(branch.geometry.xy) branch_new = Branch(geometry=xy) branch_new.generate_nodes(mesh1d_edge_length=dx) network.mesh1d_add_branch(branch_new, name=branch.Name) # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm.geometry.netfile.network = network fm.geometry.netfile.filepath = \"FlowFM_net.nc\" EX3 : Please change the computational grid distance of each branch accordingly: Branch name dx [m] Channel_1D_1_A 1000 Channel_1D_1_B 1000 Channel_1D 500 Tip : Do not forget to create a new network. In [ ]: Copied! # Answer EX3 # Specify 1D computational grid distance dx = # Create an empty network # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch in branches . iterrows (): xy = np . transpose ( branch . geometry . xy ) branch_new = Branch ( geometry = xy ) branch_new . generate_nodes ( mesh1d_edge_length = dx ) network . mesh1d_add_branch ( branch_new , name = branch . Name ) network . _mesh1d . _set_mesh1d () # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm . geometry . netfile . network = fm . geometry . netfile . filepath = # Answer EX3 # Specify 1D computational grid distance dx = # Create an empty network # Assign geometry of the branches and generate the computational grid on top of the branches. for index,branch in branches.iterrows(): xy = np.transpose(branch.geometry.xy) branch_new = Branch(geometry=xy) branch_new.generate_nodes(mesh1d_edge_length=dx) network.mesh1d_add_branch(branch_new, name=branch.Name) network._mesh1d._set_mesh1d() # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm.geometry.netfile.network = fm.geometry.netfile.filepath = The 1D branches are plotted on a map in the figure below. Also, the computational grid points in the mesh1d definition are shown. In [ ]: Copied! # Create a figure with the flowlinks of the model figure , ( ax1 , ax2 ) = plt . subplots ( ncols = 2 ) img = plt . imread ( inputdir / \"osm_background.png\" ) mesh1d_meshkernel = network . _mesh1d . _get_mesh1d () ax1 . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) mesh1d_meshkernel . plot_edges ( ax = ax1 , color = 'red' ) # Add some annotation of branches: for index , branch in branches . iterrows (): middleIndex = int (( len ( branch [ 'geometry' ] . coords ) - 1 ) / 2 ) ax1 . text ( branch [ 'geometry' ] . xy [ 0 ][ middleIndex ], branch [ 'geometry' ] . xy [ 1 ][ middleIndex ], branch [ 'Name' ], ha = 'right' ) # Make a second plot with a zoom-in view of the computational grid points near the junction ax2 . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) ax2 . set_xlim ([ 500000 , 525000 ]) ax2 . set_ylim ([ 1125000 , 1150000 ]) mesh1d_meshkernel . plot_edges ( ax = ax2 , color = 'red' , marker = '.' , markeredgecolor = 'k' , markersize = 1 ) # Create a figure with the flowlinks of the model figure, (ax1, ax2) = plt.subplots(ncols=2) img = plt.imread(inputdir/\"osm_background.png\") mesh1d_meshkernel = network._mesh1d._get_mesh1d() ax1.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) mesh1d_meshkernel.plot_edges(ax=ax1, color='red') # Add some annotation of branches: for index,branch in branches.iterrows(): middleIndex = int((len(branch['geometry'].coords) - 1)/2) ax1.text(branch['geometry'].xy[0][middleIndex], branch['geometry'].xy[1][middleIndex], branch['Name'], ha='right') # Make a second plot with a zoom-in view of the computational grid points near the junction ax2.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) ax2.set_xlim([500000, 525000]) ax2.set_ylim([1125000 ,1150000]) mesh1d_meshkernel.plot_edges(ax=ax2, color='red',marker='.',markeredgecolor='k',markersize=1) Add cross-sections \u00b6 In order to determine the flow area of the 1D model during the computation, you need cross-sections. These cross-sections consist of two components: Cross-section locations ( crosslocfile ): The crosslocfile contains the location of the cross-section on the branches. This is indicated with branchId chainage , where branchId is the name of the branch and chainage the distance to the upstream node. The figure below shows the cross-section locations in grey. In addition the cross-section location consist of the cross-section definition used at that location and a vertical shift of the profile. The latter is mainly used to create a good longitudinal slope over the 1D model (in case of shared cross-sections).

    Cross-section definitions ( crossdeffile ): The crossdeffile has the cross-section definitions in it. These definitions describe the shape of the profile. There are multiple types available: circle, rectangle, ZW- (tabulated), YZ- and XYZ-profiles. Depending on what type of watersystem you try to model you decide which cross-section to use. We recommend to use ZW- or YZ-profiles for rivers.

    Add cross-section locations \u00b6 Below the cross-section locations are read from a CSV-file and added to an empty CrossLocModel . Note that the entire dataframe with the cross-section locations is converted at once to CrossLocModel. More about dataframe handling in HYDROLIB-core can be found here . EX4 : Please investigate the profile_loc variable and answer the following questions for yourself: How many cross-sections are there in the model and per branch? Check the chainage. Also print the cross-sections locations assigned to the D-Flow FM model. Use fm.geometry.crosslocfile.crosssection (part 2). What happens if you only print the first fm.geometry.crosslocfile In [ ]: Copied! # Read profile location file profiles_location_file = inputdir / 'cross_section_locations.csv' profiles_loc = pd . read_csv ( profiles_location_file , index_col = False ) # Answer EX4 - part 1 # Create empty cross-section location model crsloc = CrossLocModel () # Assign filepath to the model crsloc . filepath = 'crsloc.ini' # Convert the dataframe crsloc . crosssection = profiles_loc . to_dict ( \"records\" ) # Assign CrossLocModel to the D-Flow FM model. fm . geometry . crosslocfile = crsloc # Answer EX4 - part 2 # Read profile location file profiles_location_file = inputdir / 'cross_section_locations.csv' profiles_loc = pd.read_csv(profiles_location_file, index_col=False) # Answer EX4 - part 1 # Create empty cross-section location model crsloc = CrossLocModel() # Assign filepath to the model crsloc.filepath = 'crsloc.ini' # Convert the dataframe crsloc.crosssection = profiles_loc.to_dict(\"records\") # Assign CrossLocModel to the D-Flow FM model. fm.geometry.crosslocfile = crsloc # Answer EX4 - part 2 Add cross-section definitions \u00b6 In the following cell the definitions belonging to the cross-section locations are added to the D-Flow FM model. These cross-sections are all YZ-profiles in order to define natural shape of the river. Please see that the following steps are included: Read the cross-section definitions from an excel. Note that the cross-section definitions id's match with the definitions specified in the crossLocModel. Create an empty CrossDefModel and assign filepath Specify some characteristics for YZ profile. Please consult appendix C.16.1.6 from D-Flow FM 1D2D Create YZCrsDef for each profile definition. Append the definition to the CrossDefModel. Append the CrossDefModel to the D-Flow FM model. In [ ]: Copied! # Create cross-section definitions profiles_file = inputdir / '1D_YZ_CrossSections.xlsx' profiles = pd . read_excel ( profiles_file , sheet_name = None ) names = list ( profiles . keys ()) print ( names ) # Create empty CrossDefModel crsdef = CrossDefModel () crsdef . filepath = 'crsdef.ini' # Specify some charachteristics for YZ profile type_crs = 'yz' thalweg = 0.0 singleValued = 'yes' conveyance = 'segmented' sectionCount = 1 # Create the YZ profiles and append them to the CrossDefModel for name in names : yzCount = len ( profiles [ name ] . values ) ycoord = profiles [ name ] . y . to_list () zcoord = profiles [ name ] . z . to_list () frictionIds = 'channels' frictionPositions = [ profiles [ name ] . y [ 0 ], profiles [ name ] . y [ yzCount - 1 ]] crosssection = YZCrsDef ( id = name , type = type_crs , thalweg = thalweg , singleValuedZ = singleValued , conveyance = conveyance , yzCount = yzCount , yCoordinates = ycoord , zCoordinates = zcoord , sectionCount = sectionCount , frictionIds = frictionIds , frictionPositions = frictionPositions ) crsdef . definition . append ( crosssection ) print ( f 'definition of { name } added to cross-section model' ) # Append CrossDefModel to D-Flow FM model fm . geometry . crossdeffile = crsdef # Create cross-section definitions profiles_file = inputdir / '1D_YZ_CrossSections.xlsx' profiles = pd.read_excel(profiles_file, sheet_name=None) names = list(profiles.keys()) print(names) # Create empty CrossDefModel crsdef = CrossDefModel() crsdef.filepath = 'crsdef.ini' # Specify some charachteristics for YZ profile type_crs = 'yz' thalweg = 0.0 singleValued = 'yes' conveyance = 'segmented' sectionCount = 1 # Create the YZ profiles and append them to the CrossDefModel for name in names: yzCount = len(profiles[name].values) ycoord = profiles[name].y.to_list() zcoord = profiles[name].z.to_list() frictionIds = 'channels' frictionPositions = [profiles[name].y[0], profiles[name].y[yzCount-1]] crosssection = YZCrsDef(id=name, type=type_crs, thalweg=thalweg, singleValuedZ=singleValued, conveyance=conveyance, yzCount=yzCount, yCoordinates= ycoord, zCoordinates=zcoord, sectionCount=sectionCount, frictionIds = frictionIds, frictionPositions=frictionPositions) crsdef.definition.append(crosssection) print(f'definition of {name} added to cross-section model') # Append CrossDefModel to D-Flow FM model fm.geometry.crossdeffile = crsdef Add roughness \u00b6 The 1D model has now a network topology, computational 1D grid and cross-sections. Friction is a component that should be added to the model to get the proper bed roughness and channel conveyance. In this step you will add the FrictionModel to the D-Flow FM model by specifying the friction type and value at the upstream cross-section location (chainage=1000.0 m) of each branch in the model ( FrictBranch ). Also a global roughness section is specified ( FrictGlobal ). This global section is used when there is no friction type and values specified for a specific branch. It also contains the frictionId. In the cross-section definition model a reference is made to this frictionId. You can check this with the commands below and search for frictionIds . In [ ]: Copied! # Print directly the modelobject (in this case all definitions) print ( fm . geometry . crossdeffile . definition ) # Or convert it first to a dataframe df_def = pd . DataFrame ([ f . __dict__ for f in fm . geometry . crossdeffile . definition ]) print ( df_def [[ 'frictionids' ]]) # Print directly the modelobject (in this case all definitions) print(fm.geometry.crossdeffile.definition) # Or convert it first to a dataframe df_def = pd.DataFrame([f.__dict__ for f in fm.geometry.crossdeffile.definition]) print(df_def[['frictionids']]) Note that YZ profiles can refer to multiple frictionIds, since the friction can vary over the cross-section. Hence the frictionId is given in a List() . This means indirectly that multiple FrictionModels can be added to one D-Flow FM model. The created FrictionModel should therefore been added in a List() to the D-Flow FM model. In [ ]: Copied! # Specify frictionId(s) for the FrictionModel(s) friction_name = 'channels' # Specify for each FrictionModel a global type and value global_type = FrictionType . manning # Options are chezy,debosbijkerk, manning, strickler, stricklernikuradse, wallawnikuradse, whitecolebrook global_value = 0.023 # Create empty friction model and assign filepath roughness = FrictionModel () roughness . filepath = \"roughness-channels.ini\" # often we specify the filenames as \"roughness-frictionId.ini\" # Create global friction model and add it to frictionmodel roughness . global_ = FrictGlobal ( frictionId = friction_name , frictionType = global_type , frictionValue = global_value ) # Add friction from branches function_type = 'constant' # This model uses constant friction per branch df_friction = branches [[ 'Name' , 'fric_type' , 'fric_value' , 'chainage' ]] df_friction . columns = [ 'branchId' , 'frictionType' , 'frictionValues' , 'chainage' ] df_friction = df_friction . assign ( frictionValues = [[ i ] for i in df_friction . frictionValues . values ]) df_friction = df_friction . assign ( functionType = function_type ) df_friction = df_friction . assign ( chainage = [[ i ] for i in df_friction . chainage . values ]) df_friction = df_friction . assign ( numlocations = 1 ) # you can specify multiple location along the branch with different friction values. roughness . branch = df_friction . to_dict ( 'records' ) # the dataframe is converted to FrictBranch models at once # Add frictionmodel to the D-Flow FM model. fm . geometry . frictfile = [ roughness ] # frictfile is a list of frictionModels # Specify frictionId(s) for the FrictionModel(s) friction_name = 'channels' # Specify for each FrictionModel a global type and value global_type = FrictionType.manning # Options are chezy,debosbijkerk, manning, strickler, stricklernikuradse, wallawnikuradse, whitecolebrook global_value = 0.023 # Create empty friction model and assign filepath roughness = FrictionModel() roughness.filepath = \"roughness-channels.ini\" # often we specify the filenames as \"roughness-frictionId.ini\" # Create global friction model and add it to frictionmodel roughness.global_ = FrictGlobal(frictionId=friction_name,frictionType=global_type,frictionValue=global_value) # Add friction from branches function_type = 'constant' # This model uses constant friction per branch df_friction = branches[['Name', 'fric_type', 'fric_value', 'chainage']] df_friction.columns = ['branchId','frictionType','frictionValues', 'chainage'] df_friction = df_friction.assign(frictionValues = [[i] for i in df_friction.frictionValues.values]) df_friction = df_friction.assign(functionType=function_type) df_friction = df_friction.assign(chainage = [[i] for i in df_friction.chainage.values]) df_friction = df_friction.assign(numlocations=1) # you can specify multiple location along the branch with different friction values. roughness.branch = df_friction.to_dict('records') # the dataframe is converted to FrictBranch models at once # Add frictionmodel to the D-Flow FM model. fm.geometry.frictfile = [roughness] # frictfile is a list of frictionModels EX5 : Let's build another frictionmodel with frictionId dique representing the friction in Canal del Dique. This frictionmodel assumes Chezy as global friction type and has a friction value of 45. In [ ]: Copied! # Answer to EX5 # Specify frictionId(s) for the FrictionModel(s) friction_id2 = # Specify for each FrictionModel a global type and value global_type2 = global_value2 = # Create empty friction model and assign filepath roughness_dique = roughness_dique . filepath = # Create global friction model and add it to frictionmodel roughness_dique . global_ = # Add frictionmodels to the D-Flow FM model. fm . geometry . frictfile = # Note that the other friction needs to be added to the list. # Answer to EX5 # Specify frictionId(s) for the FrictionModel(s) friction_id2 = # Specify for each FrictionModel a global type and value global_type2 = global_value2 = # Create empty friction model and assign filepath roughness_dique = roughness_dique.filepath = # Create global friction model and add it to frictionmodel roughness_dique.global_ = # Add frictionmodels to the D-Flow FM model. fm.geometry.frictfile = # Note that the other friction needs to be added to the list. The cross-sections on the Canal del Dique (Channel_1D_1) do not refer to this new frictionId. Please uncomment the code below to change this after completion of exercise 5. In [ ]: Copied! ## Convert crosssection defintions from D-Flow FM model to dataframe #df_def = pd.DataFrame([f.__dict__ for f in fm.geometry.crossdeffile.definition]) #print(df_def) # ## Check which cross-section locations are located on Channel_1D_1 #df_loc = pd.DataFrame([f.__dict__ for f in fm.geometry.crosslocfile.crosssection]) #print(df_loc.loc[:,['id','branchid','definitionid']]) # ## To which definition do these locations refer: #defs = df_loc.loc[df_loc.index[df_loc.branchid=='Channel_1D_1'],'definitionid'].values # ## Change the Frictionids to dique for Channel_1D_1 #index_defs = df_def.index[df_def.id.isin(defs)] # #for i in index_defs: # df_def.loc[i, 'frictionids'] = ['dique'] # ## Overwrite the definitions in D-Flow FM model with the changes in the dataframe #fm.geometry.crossdeffile.definition = df_def.to_dict(\"records\") ## Convert crosssection defintions from D-Flow FM model to dataframe #df_def = pd.DataFrame([f.__dict__ for f in fm.geometry.crossdeffile.definition]) #print(df_def) # ## Check which cross-section locations are located on Channel_1D_1 #df_loc = pd.DataFrame([f.__dict__ for f in fm.geometry.crosslocfile.crosssection]) #print(df_loc.loc[:,['id','branchid','definitionid']]) # ## To which definition do these locations refer: #defs = df_loc.loc[df_loc.index[df_loc.branchid=='Channel_1D_1'],'definitionid'].values # ## Change the Frictionids to dique for Channel_1D_1 #index_defs = df_def.index[df_def.id.isin(defs)] # #for i in index_defs: # df_def.loc[i, 'frictionids'] = ['dique'] # ## Overwrite the definitions in D-Flow FM model with the changes in the dataframe #fm.geometry.crossdeffile.definition = df_def.to_dict(\"records\") Add boundary conditions to the model \u00b6 Fluvial floods occur when water levels in the river are too high. These high water levels in the rivers can result from several factors. One of those is the occurence of heavy rainfall in the upstream catchment. These heavy rainstorm can lead to a high discharge wave entering the upstream boundary of the river. In this tutorial you will model such a high discharge wave (time series) at the upstream 1D boundary (node id = '521410.278872_1056811.761107'). For the two downstream boundaries (node ids = [wkt_geom Name BridgeCount CrossSectio CulvertCoun GateCount GeometryLen IsLengthCus LateralSour Length LongName OrderNumber PumpCount Source StructureCo Target WeirCount fric_type fric_value chainage]) a constant water level of 0 m AD is assumed. Note that this are tidal boundaries in reality. In order to apply boundary conditions on a model you need two components: Forcing (.bc) file ForcingModel : This model contains the forcing value, time series, astronomical tide, realtime connection with other modules (D-RR) or QHtable. The first two options are created in this tutorial. External Forcing (.ext) file ExtModel : The external forcing specifies the location and type of forcing. Types of forcing are Boundary , Lateral and meteo. In [ ]: Copied! # Get node ids of branches node_ids = fm . geometry . netfile . network . _mesh1d . network1d_node_id print ( node_ids ) # Specify the node ids node_upstream = node_ids [ 0 ] # discharge time series node nodes_downstream = node_ids [ 2 :] # water level nodes # Create an empty external forcing model and forcing model ext = ExtModel () ext . filepath = 'boundary_new.ext' bc = ForcingModel () #bc.filepath = inputdir / 'BoundaryConditions.bc' # Read the upstream boundary time series from excel discharge_file = inputdir / '1D_BoundaryConditions.xlsx' discharge = pd . read_excel ( discharge_file , sheet_name = [ 0 ]) # Create the timeseries bc_up = TimeSeries ( name = node_upstream , nodeid = node_upstream , timeinterpolation = TimeInterpolation . linear , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2012-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], datablock = [[ time , dis ] for [ time , dis ] in discharge [ 0 ] . values ] ) # Create downstream constant boundaries bc_dn1 = Constant ( name = nodes_downstream [ 0 ], nodeid = nodes_downstream [ 0 ], quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], datablock = [[ \"0.0\" ]] ) bc_dn2 = Constant ( name = nodes_downstream [ 1 ], nodeid = nodes_downstream [ 1 ], quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], datablock = [[ \"0.0\" ]] ) # Add the forcing to ForcingModel bc . forcing . extend ([ bc_up , bc_dn1 , bc_dn2 ]) # Create boundary locations in ExtModel ext_up = Boundary ( quantity = 'dischargebnd' , nodeid = node_upstream , forcingfile = bc ) ext_dn1 = Boundary ( quantity = 'waterlevelbnd' , nodeid = nodes_downstream [ 0 ], forcingfile = bc ) ext_dn2 = Boundary ( quantity = 'waterlevelbnd' , nodeid = nodes_downstream [ 1 ], forcingfile = bc ) # Add the boundaries to ExtModel ext . boundary . extend ([ ext_up , ext_dn1 , ext_dn2 ]) # Add the ExtModel to D-Flow FM model fm . external_forcing . extforcefilenew = ext # Get node ids of branches node_ids = fm.geometry.netfile.network._mesh1d.network1d_node_id print(node_ids) # Specify the node ids node_upstream = node_ids[0] # discharge time series node nodes_downstream = node_ids[2:] # water level nodes # Create an empty external forcing model and forcing model ext = ExtModel() ext.filepath = 'boundary_new.ext' bc = ForcingModel() #bc.filepath = inputdir / 'BoundaryConditions.bc' # Read the upstream boundary time series from excel discharge_file = inputdir / '1D_BoundaryConditions.xlsx' discharge = pd.read_excel(discharge_file, sheet_name=[0]) # Create the timeseries bc_up = TimeSeries( name = node_upstream, nodeid = node_upstream, timeinterpolation = TimeInterpolation.linear, quantityunitpair = [QuantityUnitPair(quantity = 'time', unit = 'minutes since 2012-01-01 00:00:00'), QuantityUnitPair(quantity = 'dischargebnd', unit = 'm\u00b3/s')], datablock = [[time, dis] for [time,dis] in discharge[0].values] ) # Create downstream constant boundaries bc_dn1 = Constant( name = nodes_downstream[0], nodeid = nodes_downstream[0], quantityunitpair = [QuantityUnitPair(quantity = 'waterlevelbnd', unit = 'm')], datablock = [[\"0.0\"]] ) bc_dn2 = Constant( name = nodes_downstream[1], nodeid = nodes_downstream[1], quantityunitpair = [QuantityUnitPair(quantity = 'waterlevelbnd', unit = 'm')], datablock = [[\"0.0\"]] ) # Add the forcing to ForcingModel bc.forcing.extend([bc_up,bc_dn1,bc_dn2]) # Create boundary locations in ExtModel ext_up = Boundary( quantity = 'dischargebnd', nodeid = node_upstream, forcingfile = bc ) ext_dn1 = Boundary( quantity = 'waterlevelbnd', nodeid = nodes_downstream[0], forcingfile = bc ) ext_dn2 = Boundary( quantity = 'waterlevelbnd', nodeid = nodes_downstream[1], forcingfile = bc ) # Add the boundaries to ExtModel ext.boundary.extend([ext_up,ext_dn1,ext_dn2]) # Add the ExtModel to D-Flow FM model fm.external_forcing.extforcefilenew = ext Add initial conditions \u00b6 For this model an initial water depth of 1.0 meter is assumed in the 1D model. Below you can see how this initial waterdepth is added to the D-Flow FM model using the following steps: Creating 1D initial conditions field ( 1DField ), which contains the actual waterdepths on each branch. Note that the file is seperately saved from the rest of the model. Creating IniFieldModel (= Initial and parameter field files) in which we collect the initial condition specified in step 1, so that it can be added to the FMModel . In [ ]: Copied! # Create 1D initial conditions field ini_1d = OneDFieldModel () ini_1d . global_ = OneDFieldGlobal ( quantity = 'waterdepth' , unit = 'm' , value = 1.0 ) # only global values are needed in this case, but you could also specify it per branch. ini_1d . filepath = 'initialwaterdepth.ini' ini_1d . save ( outputdir / ini_1d . filepath ) # 1D field ini files needs to be saved seperately from the model save. # Create initial field file ini_field = IniFieldModel () ini_field . filepath = 'inifield.ini' ini_field . initial = InitialField ( quantity = 'waterdepth' , datafile = ini_1d . filepath , datafiletype = DataFileType . onedfield ) fm . geometry . inifieldfile = ini_field # Create 1D initial conditions field ini_1d = OneDFieldModel() ini_1d.global_ = OneDFieldGlobal(quantity='waterdepth', unit='m', value=1.0) # only global values are needed in this case, but you could also specify it per branch. ini_1d.filepath = 'initialwaterdepth.ini' ini_1d.save(outputdir / ini_1d.filepath) # 1D field ini files needs to be saved seperately from the model save. # Create initial field file ini_field = IniFieldModel() ini_field.filepath = 'inifield.ini' ini_field.initial = InitialField(quantity='waterdepth',datafile=ini_1d.filepath, datafiletype=DataFileType.onedfield) fm.geometry.inifieldfile = ini_field Add a weir to the model \u00b6 Many lakes occur close along Canal del Dique. See figure below. This tutorial assumes that these lakes can function as extra storage for the floods from the river. Hence a weir structure, functioning as a small dam, is added downstream of the lakes. This weir structure has the following conditions: It is located at 70 km from the upstream node of the branch. The crestlevel is 4.0 m AD. The crest width is 105.0 m. The flow over the dam is in both directions.

    In [ ]: Copied! # Create weir structure weir = Weir ( id = 'fictive_dam' , name = 'fictive_dam' , branchId = 'Channel_1D_1' , chainage = 70000.0 , allowedFlowDir = FlowDirection . both , crestLevel = 4.0 , crestWidth = 105.0 , corrCoeff = 1.000 , useVelocityHeight = True ) # Create structure model struc = StructureModel () struc . filepath = 'structure.ini' # Append weir to structure struc . structure . append ( weir ) # Assign structure model to D-Flow FM model fm . geometry . structurefile = [ struc ] # Create weir structure weir = Weir( id='fictive_dam', name = 'fictive_dam', branchId='Channel_1D_1', chainage=70000.0, allowedFlowDir=FlowDirection.both, crestLevel=4.0, crestWidth=105.0, corrCoeff=1.000, useVelocityHeight=True ) # Create structure model struc = StructureModel() struc.filepath = 'structure.ini' # Append weir to structure struc.structure.append(weir) # Assign structure model to D-Flow FM model fm.geometry.structurefile = [struc] EX6 : You found out that the dam should be significantly higher. Hence you increase the crestlevel to 10.0 m AD. Your client also decided that flow can only occur from upstream to downstream. Please change the weir above. In [ ]: Copied! # Answer EX6: # Create weir structure weir = # Create structure model struc = StructureModel () struc . filepath = 'structure.ini' # Append weir to structure struc . structure . append ( weir ) # Assign structure model to D-Flow FM model fm . geometry . structurefile = [ struc ] # Answer EX6: # Create weir structure weir = # Create structure model struc = StructureModel() struc.filepath = 'structure.ini' # Append weir to structure struc.structure.append(weir) # Assign structure model to D-Flow FM model fm.geometry.structurefile = [struc] Save 1D model \u00b6 The 1D model is now finished. The commands below are used to save the model to the correct filepath (specified for the MDU-file). Note that the recurse is set to True to make sure all underlying model files are written to the directory. Else the MDU-file will be the only file written to the directory. In [ ]: Copied! # Change some time settings fm . time . refdate = '20120101' fm . time . dtuser = 60. # seconds fm . time . tstart = 43200. fm . time . tstop = 561600. # Save the 1D model. fm . general . autostart = AutoStartOption . no # This is a workaround for a bug in hydrolib-core 0.3.1 fm . save ( recurse = True ) # Change some time settings fm.time.refdate = '20120101' fm.time.dtuser = 60. # seconds fm.time.tstart = 43200. fm.time.tstop = 561600. # Save the 1D model. fm.general.autostart = AutoStartOption.no # This is a workaround for a bug in hydrolib-core 0.3.1 fm.save(recurse=True) PART 2: Extend to a 1D2D Delft3D FM model \u00b6 We will now continue with the model fm from part 1, and add a 2D mesh to it, as well as 1D2D couplings. Create 2D flexible mesh \u00b6 We use a shapefile with the area of interest to define the extent of the new 2D mesh that is to be generated. First, a uniform rectilinear mesh is generated, after which it can be clipped. EX7 : Create a rectangular grid with a cell size of 2500 by 2500 meter. Use create_rectilinear() function. EX8 : Clip the rectangular grid with the clip_geom using clip() function. In [ ]: Copied! # Read grid outline gdf_grid = gpd . read_file ( inputdir / 'outline_2D_grid.shp' ) # Determine the boundary box extent = gdf_grid . geometry [ 0 ] . bounds # Create uniform rectilinear mesh mesh2d = Mesh2d () # Answer EX7 # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np . array ( gdf_grid . geometry [ 0 ] . exterior . xy ) clip_geom = GeometryList ( clip_polygon [ 0 ], clip_polygon [ 1 ]) # Answer EX8 fm . geometry . netfile . network . _mesh2d = mesh2d fm . geometry . netfile . filepath = \"FlowFM_1D2D_net.nc\" # Read grid outline gdf_grid = gpd.read_file(inputdir / 'outline_2D_grid.shp') # Determine the boundary box extent = gdf_grid.geometry[0].bounds # Create uniform rectilinear mesh mesh2d = Mesh2d() # Answer EX7 # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np.array(gdf_grid.geometry[0].exterior.xy) clip_geom = GeometryList(clip_polygon[0],clip_polygon[1]) # Answer EX8 fm.geometry.netfile.network._mesh2d = mesh2d fm.geometry.netfile.filepath = \"FlowFM_1D2D_net.nc\" The cell below produces a basic plot of the 1D + 2D mesh. In [ ]: Copied! # Create a plot mesh2d_mk = network . _mesh2d . get_mesh2d () mesh1d_mk = network . _mesh1d . _get_mesh1d () figure , ax = plt . subplots () ax . set_aspect ( 'equal' ) plt . rcParams [ \"figure.figsize\" ] = 10 , 10 ax . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) # Plot the 1D2D network mesh2d_mk . plot_edges ( ax = ax , color = \"orange\" ) mesh1d_mk . plot_edges ( ax = ax , color = 'blue' ) # Create a plot mesh2d_mk = network._mesh2d.get_mesh2d() mesh1d_mk = network._mesh1d._get_mesh1d() figure, ax = plt.subplots() ax.set_aspect('equal') plt.rcParams[\"figure.figsize\"]=10,10 ax.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) # Plot the 1D2D network mesh2d_mk.plot_edges(ax=ax, color=\"orange\") mesh1d_mk.plot_edges(ax=ax, color='blue') Local refinement of the 2D mesh \u00b6 One of the key functionalities of Delft3D Flexible Mesh is that you can refine the 2D grid locally. The cell below shows how the grid is locally refined around the river by executing the refinement algorithm once ( level=1 ). In [ ]: Copied! # Create empty mesh2d object mesh2d = Mesh2d () # Create rectangular grid mesh2d . create_rectilinear ( extent = extent , dx = 2500.0 , dy = 2500.0 ) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np . array ( gdf_grid . geometry [ 0 ] . exterior . xy ) clip_geom = GeometryList ( clip_polygon [ 0 ], clip_polygon [ 1 ]) mesh2d . clip ( clip_geom ) # Refine the coarse uniform grid in a buffer region around the rivers gdf_refine = gpd . read_file ( inputdir / 'buffer_around_river_proj.shp' ) refine_polygon = np . array ( gdf_refine . geometry [ 0 ] . exterior . xy ) refine_geom = GeometryList ( refine_polygon [ 0 ], refine_polygon [ 1 ]) mesh2d . refine ( refine_geom , level = 1 ) fm . geometry . netfile . network . _mesh2d = mesh2d fm . geometry . netfile . filepath = \"FlowFM_1D2D_refined_net.nc\" # Create empty mesh2d object mesh2d = Mesh2d() # Create rectangular grid mesh2d.create_rectilinear( extent=extent, dx=2500.0, dy=2500.0 ) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np.array(gdf_grid.geometry[0].exterior.xy) clip_geom = GeometryList(clip_polygon[0],clip_polygon[1]) mesh2d.clip(clip_geom) # Refine the coarse uniform grid in a buffer region around the rivers gdf_refine = gpd.read_file(inputdir / 'buffer_around_river_proj.shp') refine_polygon = np.array(gdf_refine.geometry[0].exterior.xy) refine_geom = GeometryList(refine_polygon[0], refine_polygon[1]) mesh2d.refine(refine_geom, level=1) fm.geometry.netfile.network._mesh2d = mesh2d fm.geometry.netfile.filepath = \"FlowFM_1D2D_refined_net.nc\" In [ ]: Copied! # Create a plot mesh2d_mk = network . _mesh2d . get_mesh2d () mesh1d_mk = network . _mesh1d . _get_mesh1d () figure , ax = plt . subplots () ax . set_aspect ( 'equal' ) plt . rcParams [ \"figure.figsize\" ] = 10 , 10 ax . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) # Plot the 1D2D network mesh2d_mk . plot_edges ( ax = ax , color = \"orange\" ) mesh1d_mk . plot_edges ( ax = ax , color = 'blue' ) # Create a plot mesh2d_mk = network._mesh2d.get_mesh2d() mesh1d_mk = network._mesh1d._get_mesh1d() figure, ax = plt.subplots() ax.set_aspect('equal') plt.rcParams[\"figure.figsize\"]=10,10 ax.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) # Plot the 1D2D network mesh2d_mk.plot_edges(ax=ax, color=\"orange\") mesh1d_mk.plot_edges(ax=ax, color='blue') Save 1D2D model \u00b6 The 1D2D model is now finished. The commands below are used to save the model to the correct filepath (specified for the MDU-file). Note that the recurse is set to True to make sure all underlying model files are written to the directory. Else the MDU-file will be the only file written to the directory. Note that the 1D2D links will be generated in the Delft3D FM 1D2D software. Future releases of HYDROLIB-core will consist of 1D2D functionalities. In [ ]: Copied! # Change fm outputdir_1d2d = root / '1D2D_model' fm . filepath = outputdir_1d2d / 'Magdalena_1D2D.mdu' fm . general . autostart = AutoStartOption . no fm . save ( recurse = True ) # Change fm outputdir_1d2d = root / '1D2D_model' fm.filepath = outputdir_1d2d / 'Magdalena_1D2D.mdu' fm.general.autostart = AutoStartOption.no fm.save(recurse=True)","title":"Tutorial Delft3D FM 1D2D fluvial flood model of Magdalena river"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#tutorial-delft3d-fm-1d2d-fluvial-flood-model-of-magdalena-river","text":"This notebook is an introduction on how to use HYDROLIB-core functionalities to create and adjust a Delft3D FM Suite 1D2D fluvial flood model of the Magdalena river in Columbia. First a 1D river model of the Magdalena river and Canal del Dique will be created, shown in the left figure. This model will be extended with a 2D Flexible Mesh, with a uniform roughness field. Adding a DTM on that 2D mesh is currently not part of this tutorial, but normally this is of course indispensible to mimic the fluvial flood patterns. Running the model or importing the model in the Delft3D FM Suite 1D2D is not shown in this tutorial. Note that the model and tutorial are created for educational purposes and consist partially of fictive/unvalidated model data. HYDROLIB-core is the core library of Python wrappers around the D-HYDRO Suite 1D2D model files (input and output) and model engines (kernel libraries). HYDROLIB is a Python package with tools for pre-processing, post-processing and analysis of hydrodynamical data and simulation results, currently focused on Delft3D Suite 1D2D. HYDROLIB builds upon the basic HYDROLIB-core functionalities. The goal of this tutorial is to familiarize modelers with how to apply HYDROLIB-core functionalities in their modelling procedures for building new models or adjusting existing models. As mentioned above, you will create an 1D2D fluvial flood model from scratch using the D-Flow FM HYDROLIB-core functionalities and the underlying functions from mesh generation ( MeshKernelPy ). The building of the model is done by the following steps Loading libraries Connect to data folder Create empty D-Flow FM model Read branches Create computational grid Add cross-sections Add roughness Add boundary conditions Add initial conditions Add a weir to the model Save 1D model Create 2D flexible mesh Add 2D DTM to model Save 1D2D model Note that HYDROLIB-core also contains functionalities to setup lumped rainfall runoff models ( D-RR ) and to apply real-time control at structures ( D-RTC ), but these are not covered in this tutorial.","title":"Tutorial Delft3D FM 1D2D fluvial flood model of Magdalena river"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#installation","text":"To run this notebook a simple Python environment with the following packages is required: - python=3.9 - pandas - geopandas - pyogrio - matplotlib - numpy - jupyter - xarray - openpyxl - pip - pip: - hydrolib-core==0.3.1 - meshkernel==1.0.0 Note that all participants received an e-mail to download the material from the Deltares download portal and to create a Conda environment with the packages automatically installed from environment.yml . Furthermore, a dummy model is provided at the download portal to test the environment.","title":"Installation"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#tips-for-working-in-the-jupyter-notebook","text":"Tab : Auto-complete on code Shift + Tab : Tooltip Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell Ctrl + Shift + P : Open command palette Let's get started!","title":"Tips for working in the Jupyter Notebook:"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#loading-libraries","text":"Several Python packages are required to run the notebook. These packages are imported below. Please consult the HYDROLIB-core documentation if you want to import additional HYDROLIB-core functionalities later. The import of HYDROLIB-core packages will be simplied in future HYDROLIB-core release (> 0.3.1) In [ ]: Copied! # basic packages import numpy as np import pandas as pd import matplotlib.pyplot as plt # I/O from pathlib import Path # vector/polygon packages import geopandas as gpd from shapely import wkt from shapely.geometry import box # HYDROLIB-core libraries from hydrolib.core.mdu.models import FMModel , AutoStartOption from hydrolib.core.net.models import * from hydrolib.core.crosssection.models import CrossLocModel , CrossDefModel , CrossSection , YZCrsDef from hydrolib.core.friction.models import * from hydrolib.core.bc.models import * from hydrolib.core.ext.models import * from hydrolib.core.inifield.models import * from hydrolib.core.onedfield.models import * from hydrolib.core.structure.models import Weir , FlowDirection , StructureModel # basic packages import numpy as np import pandas as pd import matplotlib.pyplot as plt # I/O from pathlib import Path # vector/polygon packages import geopandas as gpd from shapely import wkt from shapely.geometry import box # HYDROLIB-core libraries from hydrolib.core.mdu.models import FMModel, AutoStartOption from hydrolib.core.net.models import * from hydrolib.core.crosssection.models import CrossLocModel, CrossDefModel, CrossSection, YZCrsDef from hydrolib.core.friction.models import * from hydrolib.core.bc.models import * from hydrolib.core.ext.models import * from hydrolib.core.inifield.models import * from hydrolib.core.onedfield.models import * from hydrolib.core.structure.models import Weir, FlowDirection, StructureModel","title":"Loading libraries"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#connect-to-data","text":"The data for this tutorial is provided via the download portal. EX1 : Change the inputdir to the path of your unzipped data folder. In [ ]: Copied! # Get the directory of the notebook location root = Path . cwd () # Answer EX1 # Specify the path to the data folder inputdir = # Get the directory of the notebook location root = Path.cwd() # Answer EX1 # Specify the path to the data folder inputdir =","title":"Connect to data"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#create-empty-d-flow-fm-model","text":"To start a model from scratch you need to create first an empty model without data and assign a filepath to the model. In this case a D-Flow FM model is created. The MDU file (master definition file) is the main file of the D-Flow FM model. This is created with the FMModel() function. The fm model object is only created in memory. To save the actual model file, call fm.save() . EX2 : Set the outputdir of the model and give it a name. Verify that an MDU file has been written in your output directory. In [ ]: Copied! # Create empty D-Flow FM model fm = FMModel () # Answer EX2 # Assign filepath to the D-Flow FM model outputdir = fm . filepath = outputdir / 'Magdalena_1D.mdu' fm . save () # Create empty D-Flow FM model fm = FMModel() # Answer EX2 # Assign filepath to the D-Flow FM model outputdir = fm.filepath = outputdir / 'Magdalena_1D.mdu' fm.save()","title":"Create empty D-Flow FM model"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#part-1-set-up-a-1d-delft3d-fm-model","text":"In this part we will build up the complete 1D model schematization step by step. At the end you should have a complete set of model input files for a 1D calculation.","title":"PART 1: Set up a 1D Delft3D FM model"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#read-branches","text":"The model will include the lower part of the Magadalena from Cordoba Teton to the river mouth Baranquilla and the Canal del Dique. EX2 : Please investigate the branches variable and answer the following questions for yourself: How many river branches does the model have? What are their names? Which friction type and values are used for each branch? In [ ]: Copied! # Read the branches branches = gpd . read_file ( filename = inputdir / 'branches_Branches.shp' ) # Answer EX3 # Read the branches branches = gpd.read_file(filename = inputdir / 'branches_Branches.shp') # Answer EX3","title":"Read branches"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#create-1d-computational-grid","text":"In the previous step you read the geometry and attributes of the branches into the notebook. These branches will become the network input to our FMModel . The cell below shows how the geometry and name of the branches are assigned to the network. In addition a 1D computational grid ( mesh1d ) with gridpoint every 1000 meter is created on top of this network. Since the network does not yet exist, you need to create an empty network model . Assign the geometry of the branches followed by the generation of the computational grid. The network model should be added to the D-Flow FM model ( fm variable in this notebook) as network in the netfile parameter in the section geometry . Note that you have to specify a filepath for the networkfile. Note that the network model can consist of 1D, 2D flexible mesh ( mesh2d ) and 1D2D links ( links1d2d ). In [ ]: Copied! # Specify 1D computational grid distance dx = 1000.0 # Create an empty network network = Network () # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch in branches . iterrows (): xy = np . transpose ( branch . geometry . xy ) branch_new = Branch ( geometry = xy ) branch_new . generate_nodes ( mesh1d_edge_length = dx ) network . mesh1d_add_branch ( branch_new , name = branch . Name ) # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm . geometry . netfile . network = network fm . geometry . netfile . filepath = \"FlowFM_net.nc\" # Specify 1D computational grid distance dx = 1000.0 # Create an empty network network = Network() # Assign geometry of the branches and generate the computational grid on top of the branches. for index,branch in branches.iterrows(): xy = np.transpose(branch.geometry.xy) branch_new = Branch(geometry=xy) branch_new.generate_nodes(mesh1d_edge_length=dx) network.mesh1d_add_branch(branch_new, name=branch.Name) # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm.geometry.netfile.network = network fm.geometry.netfile.filepath = \"FlowFM_net.nc\" EX3 : Please change the computational grid distance of each branch accordingly: Branch name dx [m] Channel_1D_1_A 1000 Channel_1D_1_B 1000 Channel_1D 500 Tip : Do not forget to create a new network. In [ ]: Copied! # Answer EX3 # Specify 1D computational grid distance dx = # Create an empty network # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch in branches . iterrows (): xy = np . transpose ( branch . geometry . xy ) branch_new = Branch ( geometry = xy ) branch_new . generate_nodes ( mesh1d_edge_length = dx ) network . mesh1d_add_branch ( branch_new , name = branch . Name ) network . _mesh1d . _set_mesh1d () # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm . geometry . netfile . network = fm . geometry . netfile . filepath = # Answer EX3 # Specify 1D computational grid distance dx = # Create an empty network # Assign geometry of the branches and generate the computational grid on top of the branches. for index,branch in branches.iterrows(): xy = np.transpose(branch.geometry.xy) branch_new = Branch(geometry=xy) branch_new.generate_nodes(mesh1d_edge_length=dx) network.mesh1d_add_branch(branch_new, name=branch.Name) network._mesh1d._set_mesh1d() # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm.geometry.netfile.network = fm.geometry.netfile.filepath = The 1D branches are plotted on a map in the figure below. Also, the computational grid points in the mesh1d definition are shown. In [ ]: Copied! # Create a figure with the flowlinks of the model figure , ( ax1 , ax2 ) = plt . subplots ( ncols = 2 ) img = plt . imread ( inputdir / \"osm_background.png\" ) mesh1d_meshkernel = network . _mesh1d . _get_mesh1d () ax1 . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) mesh1d_meshkernel . plot_edges ( ax = ax1 , color = 'red' ) # Add some annotation of branches: for index , branch in branches . iterrows (): middleIndex = int (( len ( branch [ 'geometry' ] . coords ) - 1 ) / 2 ) ax1 . text ( branch [ 'geometry' ] . xy [ 0 ][ middleIndex ], branch [ 'geometry' ] . xy [ 1 ][ middleIndex ], branch [ 'Name' ], ha = 'right' ) # Make a second plot with a zoom-in view of the computational grid points near the junction ax2 . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) ax2 . set_xlim ([ 500000 , 525000 ]) ax2 . set_ylim ([ 1125000 , 1150000 ]) mesh1d_meshkernel . plot_edges ( ax = ax2 , color = 'red' , marker = '.' , markeredgecolor = 'k' , markersize = 1 ) # Create a figure with the flowlinks of the model figure, (ax1, ax2) = plt.subplots(ncols=2) img = plt.imread(inputdir/\"osm_background.png\") mesh1d_meshkernel = network._mesh1d._get_mesh1d() ax1.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) mesh1d_meshkernel.plot_edges(ax=ax1, color='red') # Add some annotation of branches: for index,branch in branches.iterrows(): middleIndex = int((len(branch['geometry'].coords) - 1)/2) ax1.text(branch['geometry'].xy[0][middleIndex], branch['geometry'].xy[1][middleIndex], branch['Name'], ha='right') # Make a second plot with a zoom-in view of the computational grid points near the junction ax2.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) ax2.set_xlim([500000, 525000]) ax2.set_ylim([1125000 ,1150000]) mesh1d_meshkernel.plot_edges(ax=ax2, color='red',marker='.',markeredgecolor='k',markersize=1)","title":"Create 1D computational grid"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena/#add-cross-sections","text":"In order to determine the flow area of the 1D model during the computation, you need cross-sections. These cross-sections consist of two components: Cross-section locations ( crosslocfile ): The crosslocfile contains the location of the cross-section on the branches. This is indicated with branchId chainage , where branchId is the name of the branch and chainage the distance to the upstream node. The figure below shows the cross-section locations in grey. In addition the cross-section location consist of the cross-section definition used at that location and a vertical shift of the profile. The latter is mainly used to create a good longitudinal slope over the 1D model (in case of shared cross-sections).

    Cross-section definitions ( crossdeffile ): The crossdeffile has the cross-section definitions in it. These definitions describe the shape of the profile. There are multiple types available: circle, rectangle, ZW- (tabulated), YZ- and XYZ-profiles. Depending on what type of watersystem you try to model you decide which cross-section to use. We recommend to use ZW- or YZ-profiles for rivers.

    ","title":"Add cross-sections"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/","text":"(function (global, factory) { typeof exports === 'object' && typeof module !== 'undefined' ? module.exports = factory() : typeof define === 'function' && define.amd ? define(factory) : (global = global || self, global.ClipboardCopyElement = factory()); }(this, function () { 'use strict'; function createNode(text) { const node = document.createElement('pre'); node.style.width = '1px'; node.style.height = '1px'; node.style.position = 'fixed'; node.style.top = '5px'; node.textContent = text; return node; } function copyNode(node) { if ('clipboard' in navigator) { // eslint-disable-next-line flowtype/no-flow-fix-me-comments // $FlowFixMe Clipboard is not defined in Flow yet. return navigator.clipboard.writeText(node.textContent); } const selection = getSelection(); if (selection == null) { return Promise.reject(new Error()); } selection.removeAllRanges(); const range = document.createRange(); range.selectNodeContents(node); selection.addRange(range); document.execCommand('copy'); selection.removeAllRanges(); return Promise.resolve(); } function copyText(text) { if ('clipboard' in navigator) { // eslint-disable-next-line flowtype/no-flow-fix-me-comments // $FlowFixMe Clipboard is not defined in Flow yet. return navigator.clipboard.writeText(text); } const body = document.body; if (!body) { return Promise.reject(new Error()); } const node = createNode(text); body.appendChild(node); copyNode(node); body.removeChild(node); return Promise.resolve(); } function copy(button) { const id = button.getAttribute('for'); const text = button.getAttribute('value'); function trigger() { button.dispatchEvent(new CustomEvent('clipboard-copy', { bubbles: true })); } if (text) { copyText(text).then(trigger); } else if (id) { const root = 'getRootNode' in Element.prototype ? button.getRootNode() : button.ownerDocument; if (!(root instanceof Document || 'ShadowRoot' in window && root instanceof ShadowRoot)) return; const node = root.getElementById(id); if (node) copyTarget(node).then(trigger); } } function copyTarget(content) { if (content instanceof HTMLInputElement || content instanceof HTMLTextAreaElement) { return copyText(content.value); } else if (content instanceof HTMLAnchorElement && content.hasAttribute('href')) { return copyText(content.href); } else { return copyNode(content); } } function clicked(event) { const button = event.currentTarget; if (button instanceof HTMLElement) { copy(button); } } function keydown(event) { if (event.key === ' ' || event.key === 'Enter') { const button = event.currentTarget; if (button instanceof HTMLElement) { event.preventDefault(); copy(button); } } } function focused(event) { event.currentTarget.addEventListener('keydown', keydown); } function blurred(event) { event.currentTarget.removeEventListener('keydown', keydown); } class ClipboardCopyElement extends HTMLElement { constructor() { super(); this.addEventListener('click', clicked); this.addEventListener('focus', focused); this.addEventListener('blur', blurred); } connectedCallback() { if (!this.hasAttribute('tabindex')) { this.setAttribute('tabindex', '0'); } if (!this.hasAttribute('role')) { this.setAttribute('role', 'button'); } } get value() { return this.getAttribute('value') || ''; } set value(text) { this.setAttribute('value', text); } } if (!window.customElements.get('clipboard-copy')) { window.ClipboardCopyElement = ClipboardCopyElement; window.customElements.define('clipboard-copy', ClipboardCopyElement); } return ClipboardCopyElement; })); document.addEventListener('clipboard-copy', function(event) { const notice = event.target.querySelector('.notice') notice.hidden = false setTimeout(function() { notice.hidden = true }, 1000) }) pre { line-height: 125%; } td.linenos .normal { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; } span.linenos { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; } td.linenos .special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; } span.linenos.special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; } .highlight-ipynb .hll { background-color: var(--jp-cell-editor-active-background) } .highlight-ipynb { background: var(--jp-cell-editor-background); color: var(--jp-mirror-editor-variable-color) } .highlight-ipynb .c { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment */ .highlight-ipynb .err { color: var(--jp-mirror-editor-error-color) } /* Error */ .highlight-ipynb .k { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword */ .highlight-ipynb .o { color: var(--jp-mirror-editor-operator-color); font-weight: bold } /* Operator */ .highlight-ipynb .p { color: var(--jp-mirror-editor-punctuation-color) } /* Punctuation */ .highlight-ipynb .ch { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Hashbang */ .highlight-ipynb .cm { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Multiline */ .highlight-ipynb .cp { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Preproc */ .highlight-ipynb .cpf { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.PreprocFile */ .highlight-ipynb .c1 { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Single */ .highlight-ipynb .cs { color: var(--jp-mirror-editor-comment-color); font-style: italic } /* Comment.Special */ .highlight-ipynb .kc { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Constant */ .highlight-ipynb .kd { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Declaration */ .highlight-ipynb .kn { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Namespace */ .highlight-ipynb .kp { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Pseudo */ .highlight-ipynb .kr { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Reserved */ .highlight-ipynb .kt { color: var(--jp-mirror-editor-keyword-color); font-weight: bold } /* Keyword.Type */ .highlight-ipynb .m { color: var(--jp-mirror-editor-number-color) } /* Literal.Number */ .highlight-ipynb .s { color: var(--jp-mirror-editor-string-color) } /* Literal.String */ .highlight-ipynb .ow { color: var(--jp-mirror-editor-operator-color); font-weight: bold } /* Operator.Word */ .highlight-ipynb .pm { color: var(--jp-mirror-editor-punctuation-color) } /* Punctuation.Marker */ .highlight-ipynb .w { color: var(--jp-mirror-editor-variable-color) } /* Text.Whitespace */ .highlight-ipynb .mb { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Bin */ .highlight-ipynb .mf { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Float */ .highlight-ipynb .mh { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Hex */ .highlight-ipynb .mi { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Integer */ .highlight-ipynb .mo { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Oct */ .highlight-ipynb .sa { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Affix */ .highlight-ipynb .sb { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Backtick */ .highlight-ipynb .sc { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Char */ .highlight-ipynb .dl { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Delimiter */ .highlight-ipynb .sd { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Doc */ .highlight-ipynb .s2 { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Double */ .highlight-ipynb .se { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Escape */ .highlight-ipynb .sh { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Heredoc */ .highlight-ipynb .si { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Interpol */ .highlight-ipynb .sx { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Other */ .highlight-ipynb .sr { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Regex */ .highlight-ipynb .s1 { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Single */ .highlight-ipynb .ss { color: var(--jp-mirror-editor-string-color) } /* Literal.String.Symbol */ .highlight-ipynb .il { color: var(--jp-mirror-editor-number-color) } /* Literal.Number.Integer.Long */ /* This file is taken from the built JupyterLab theme.css Found on share/nbconvert/templates/lab/static Some changes have been made and marked with CHANGE */ .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ --jp-shadow-base-lightness: 0; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-400); --jp-border-color1: var(--md-grey-400); --jp-border-color2: var(--md-grey-300); --jp-border-color3: var(--md-grey-200); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(0, 0, 0, 1); --jp-ui-font-color1: rgba(0, 0, 0, 0.87); --jp-ui-font-color2: rgba(0, 0, 0, 0.54); --jp-ui-font-color3: rgba(0, 0, 0, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color1: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color2: rgba(255, 255, 255, 0.7); --jp-ui-inverse-font-color3: rgba(255, 255, 255, 0.5); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(0, 0, 0, 1); --jp-content-font-color1: rgba(0, 0, 0, 0.87); --jp-content-font-color2: rgba(0, 0, 0, 0.54); --jp-content-font-color3: rgba(0, 0, 0, 0.38); --jp-content-link-color: var(--md-blue-700); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: white; --jp-layout-color1: white; --jp-layout-color2: var(--md-grey-200); --jp-layout-color3: var(--md-grey-400); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: #111111; --jp-inverse-layout-color1: var(--md-grey-900); --jp-inverse-layout-color2: var(--md-grey-800); --jp-inverse-layout-color3: var(--md-grey-700); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-900); --jp-brand-color1: var(--md-blue-700); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-900); --jp-accent-color1: var(--md-green-700); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-900); --jp-warn-color1: var(--md-orange-700); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-900); --jp-error-color1: var(--md-red-700); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-900); --jp-success-color1: var(--md-green-700); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-900); --jp-info-color1: var(--md-cyan-700); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--md-grey-100); --jp-cell-editor-border-color: var(--md-grey-300); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 0.5; --jp-cell-prompt-not-active-font-color: var(--md-grey-700); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: var(--md-blue-50); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: #fdd; --jp-rendermime-table-row-background: var(--md-grey-100); --jp-rendermime-table-row-hover-background: var(--md-light-blue-50); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.25); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color1); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.24); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--md-grey-300); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color1); --jp-input-hover-background: var(--jp-layout-color1); --jp-input-background: var(--md-grey-100); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: #d9d9d9; --jp-editor-selected-focused-background: #d7d4f0; --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: #008000; --jp-mirror-editor-atom-color: #88f; --jp-mirror-editor-number-color: #080; --jp-mirror-editor-def-color: #00f; --jp-mirror-editor-variable-color: var(--md-grey-900); --jp-mirror-editor-variable-2-color: #05a; --jp-mirror-editor-variable-3-color: #085; --jp-mirror-editor-punctuation-color: #05a; --jp-mirror-editor-property-color: #05a; --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ba2121; --jp-mirror-editor-string-2-color: #708; --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: #008000; --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: #170; --jp-mirror-editor-attribute-color: #00c; --jp-mirror-editor-header-color: blue; --jp-mirror-editor-quote-color: #090; --jp-mirror-editor-link-color: #00c; --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: white; /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.5; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(245, 200, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } [data-md-color-scheme=\"slate\"] .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ /* The dark theme shadows need a bit of work, but this will probably also require work on the core layout * colors used in the theme as well. */ --jp-shadow-base-lightness: 32; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-700); --jp-border-color1: var(--md-grey-700); --jp-border-color2: var(--md-grey-800); --jp-border-color3: var(--md-grey-900); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(255, 255, 255, 1); --jp-ui-font-color1: rgba(255, 255, 255, 0.87); --jp-ui-font-color2: rgba(255, 255, 255, 0.54); --jp-ui-font-color3: rgba(255, 255, 255, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(0, 0, 0, 1); --jp-ui-inverse-font-color1: rgba(0, 0, 0, 0.8); --jp-ui-inverse-font-color2: rgba(0, 0, 0, 0.5); --jp-ui-inverse-font-color3: rgba(0, 0, 0, 0.3); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(255, 255, 255, 1); --jp-content-font-color1: rgba(255, 255, 255, 1); --jp-content-font-color2: rgba(255, 255, 255, 0.7); --jp-content-font-color3: rgba(255, 255, 255, 0.5); --jp-content-link-color: var(--md-blue-300); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: #111111; --jp-layout-color1: var(--md-grey-900); --jp-layout-color2: var(--md-grey-800); --jp-layout-color3: var(--md-grey-700); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: white; --jp-inverse-layout-color1: white; --jp-inverse-layout-color2: var(--md-grey-200); --jp-inverse-layout-color3: var(--md-grey-400); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-700); --jp-brand-color1: var(--md-blue-500); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-700); --jp-accent-color1: var(--md-green-500); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-700); --jp-warn-color1: var(--md-orange-500); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-700); --jp-error-color1: var(--md-red-500); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-700); --jp-success-color1: var(--md-green-500); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-700); --jp-info-color1: var(--md-cyan-500); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--jp-layout-color1); --jp-cell-editor-border-color: var(--md-grey-700); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 1; --jp-cell-prompt-not-active-font-color: var(--md-grey-300); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: rgba(33, 150, 243, 0.24); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: rgba(244, 67, 54, 0.28); --jp-rendermime-table-row-background: var(--md-grey-900); --jp-rendermime-table-row-hover-background: rgba(3, 169, 244, 0.2); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.6); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color2); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.8); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--jp-layout-color0); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color0); --jp-input-hover-background: var(--jp-layout-color2); --jp-input-background: var(--md-grey-800); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: var(--jp-layout-color2); --jp-editor-selected-focused-background: rgba(33, 150, 243, 0.24); --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: var(--md-green-500); --jp-mirror-editor-atom-color: var(--md-blue-300); --jp-mirror-editor-number-color: var(--md-green-400); --jp-mirror-editor-def-color: var(--md-blue-600); --jp-mirror-editor-variable-color: var(--md-grey-300); --jp-mirror-editor-variable-2-color: var(--md-blue-400); --jp-mirror-editor-variable-3-color: var(--md-green-600); --jp-mirror-editor-punctuation-color: var(--md-blue-400); --jp-mirror-editor-property-color: var(--md-blue-400); --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ff7070; --jp-mirror-editor-string-2-color: var(--md-purple-300); --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: var(--md-green-600); --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: var(--md-green-700); --jp-mirror-editor-attribute-color: var(--md-blue-700); --jp-mirror-editor-header-color: var(--md-blue-500); --jp-mirror-editor-quote-color: var(--md-green-300); --jp-mirror-editor-link-color: var(--md-blue-700); --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: var(--md-grey-400); /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.6; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(255, 225, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* scrollbar related styles. Supports every browser except Edge. */ /* colors based on JetBrain's Darcula theme */ --jp-scrollbar-background-color: #3f4244; --jp-scrollbar-thumb-color: 88, 96, 97; /* need to specify thumb color as an RGB triplet */ --jp-scrollbar-endpad: 3px; /* the minimum gap between the thumb and the ends of a scrollbar */ /* hacks for setting the thumb shape. These do nothing in Firefox */ --jp-scrollbar-thumb-margin: 3.5px; /* the space in between the sides of the thumb and the track */ --jp-scrollbar-thumb-radius: 9px; /* set to a large-ish value for rounded endcaps on the thumb */ /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } :root{--md-red-50: #ffebee;--md-red-100: #ffcdd2;--md-red-200: #ef9a9a;--md-red-300: #e57373;--md-red-400: #ef5350;--md-red-500: #f44336;--md-red-600: #e53935;--md-red-700: #d32f2f;--md-red-800: #c62828;--md-red-900: #b71c1c;--md-red-A100: #ff8a80;--md-red-A200: #ff5252;--md-red-A400: #ff1744;--md-red-A700: #d50000;--md-pink-50: #fce4ec;--md-pink-100: #f8bbd0;--md-pink-200: #f48fb1;--md-pink-300: #f06292;--md-pink-400: #ec407a;--md-pink-500: #e91e63;--md-pink-600: #d81b60;--md-pink-700: #c2185b;--md-pink-800: #ad1457;--md-pink-900: #880e4f;--md-pink-A100: #ff80ab;--md-pink-A200: #ff4081;--md-pink-A400: #f50057;--md-pink-A700: #c51162;--md-purple-50: #f3e5f5;--md-purple-100: #e1bee7;--md-purple-200: #ce93d8;--md-purple-300: #ba68c8;--md-purple-400: #ab47bc;--md-purple-500: #9c27b0;--md-purple-600: #8e24aa;--md-purple-700: #7b1fa2;--md-purple-800: #6a1b9a;--md-purple-900: #4a148c;--md-purple-A100: #ea80fc;--md-purple-A200: #e040fb;--md-purple-A400: #d500f9;--md-purple-A700: #aa00ff;--md-deep-purple-50: #ede7f6;--md-deep-purple-100: #d1c4e9;--md-deep-purple-200: #b39ddb;--md-deep-purple-300: #9575cd;--md-deep-purple-400: #7e57c2;--md-deep-purple-500: #673ab7;--md-deep-purple-600: #5e35b1;--md-deep-purple-700: #512da8;--md-deep-purple-800: #4527a0;--md-deep-purple-900: #311b92;--md-deep-purple-A100: #b388ff;--md-deep-purple-A200: #7c4dff;--md-deep-purple-A400: #651fff;--md-deep-purple-A700: #6200ea;--md-indigo-50: #e8eaf6;--md-indigo-100: #c5cae9;--md-indigo-200: #9fa8da;--md-indigo-300: #7986cb;--md-indigo-400: #5c6bc0;--md-indigo-500: #3f51b5;--md-indigo-600: #3949ab;--md-indigo-700: #303f9f;--md-indigo-800: #283593;--md-indigo-900: #1a237e;--md-indigo-A100: #8c9eff;--md-indigo-A200: #536dfe;--md-indigo-A400: #3d5afe;--md-indigo-A700: #304ffe;--md-blue-50: #e3f2fd;--md-blue-100: #bbdefb;--md-blue-200: #90caf9;--md-blue-300: #64b5f6;--md-blue-400: #42a5f5;--md-blue-500: #2196f3;--md-blue-600: #1e88e5;--md-blue-700: #1976d2;--md-blue-800: #1565c0;--md-blue-900: #0d47a1;--md-blue-A100: #82b1ff;--md-blue-A200: #448aff;--md-blue-A400: #2979ff;--md-blue-A700: #2962ff;--md-light-blue-50: #e1f5fe;--md-light-blue-100: #b3e5fc;--md-light-blue-200: #81d4fa;--md-light-blue-300: #4fc3f7;--md-light-blue-400: #29b6f6;--md-light-blue-500: #03a9f4;--md-light-blue-600: #039be5;--md-light-blue-700: #0288d1;--md-light-blue-800: #0277bd;--md-light-blue-900: #01579b;--md-light-blue-A100: #80d8ff;--md-light-blue-A200: #40c4ff;--md-light-blue-A400: #00b0ff;--md-light-blue-A700: #0091ea;--md-cyan-50: #e0f7fa;--md-cyan-100: #b2ebf2;--md-cyan-200: #80deea;--md-cyan-300: #4dd0e1;--md-cyan-400: #26c6da;--md-cyan-500: #00bcd4;--md-cyan-600: #00acc1;--md-cyan-700: #0097a7;--md-cyan-800: #00838f;--md-cyan-900: #006064;--md-cyan-A100: #84ffff;--md-cyan-A200: #18ffff;--md-cyan-A400: #00e5ff;--md-cyan-A700: #00b8d4;--md-teal-50: #e0f2f1;--md-teal-100: #b2dfdb;--md-teal-200: #80cbc4;--md-teal-300: #4db6ac;--md-teal-400: #26a69a;--md-teal-500: #009688;--md-teal-600: #00897b;--md-teal-700: #00796b;--md-teal-800: #00695c;--md-teal-900: #004d40;--md-teal-A100: #a7ffeb;--md-teal-A200: #64ffda;--md-teal-A400: #1de9b6;--md-teal-A700: #00bfa5;--md-green-50: #e8f5e9;--md-green-100: #c8e6c9;--md-green-200: #a5d6a7;--md-green-300: #81c784;--md-green-400: #66bb6a;--md-green-500: #4caf50;--md-green-600: #43a047;--md-green-700: #388e3c;--md-green-800: #2e7d32;--md-green-900: #1b5e20;--md-green-A100: #b9f6ca;--md-green-A200: #69f0ae;--md-green-A400: #00e676;--md-green-A700: 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sourceMappingURL=mkdocs-jupyter.css.map*/ init_mathjax = function() { if (window.MathJax) { // MathJax loaded MathJax.Hub.Config({ TeX: { equationNumbers: { autoNumber: \"AMS\", useLabelIds: true } }, tex2jax: { inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ], displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ], processEscapes: true, processEnvironments: true }, displayAlign: 'center', CommonHTML: { linebreaks: { automatic: true } } }); MathJax.Hub.Queue([\"Typeset\", MathJax.Hub]); } } init_mathjax(); Tutorial Delft3D FM 1D2D fluvial flood model of Magdalena river \u00b6 This notebook is an introduction on how to use HYDROLIB-core functionalities to create and adjust a Delft3D FM Suite 1D2D fluvial flood model of the Magdalena river in Columbia. First a 1D river model of the Magdalena river and Canal del Dique will be created, shown in the left figure. This model will be extended with a 2D Flexible Mesh, with a uniform roughness field. Adding a DTM on that 2D mesh is currently not part of this tutorial, but normally this is of course indispensible to mimic the fluvial flood patterns. Running the model or importing the model in the Delft3D FM Suite 1D2D is not shown in this tutorial. Note that the model and tutorial are created for educational purposes and consist partially of fictive/unvalidated model data. HYDROLIB-core is the core library of Python wrappers around the D-HYDRO Suite 1D2D model files (input and output) and model engines (kernel libraries). HYDROLIB is a Python package with tools for pre-processing, post-processing and analysis of hydrodynamical data and simulation results, currently focused on Delft3D Suite 1D2D. HYDROLIB builds upon the basic HYDROLIB-core functionalities. The goal of this tutorial is to familiarize modelers with how to apply HYDROLIB-core functionalities in their modelling procedures for building new models or adjusting existing models. As mentioned above, you will create an 1D2D fluvial flood model from scratch using the D-Flow FM HYDROLIB-core functionalities and the underlying functions from mesh generation ( MeshKernelPy ). The building of the model is done by the following steps Loading libraries Connect to data folder Create empty D-Flow FM model Read branches Create computational grid Add cross-sections Add roughness Add boundary conditions Add initial conditions Add a weir to the model Save 1D model Create 2D flexible mesh Add 2D DTM to model Save 1D2D model Note that HYDROLIB-core also contains functionalities to setup lumped rainfall runoff models ( D-RR ) and to apply real-time control at structures ( D-RTC ), but these are not covered in this tutorial. Installation \u00b6 To run this notebook a simple Python environment with the following packages is required: - python=3.9 - pandas - geopandas - pyogrio - matplotlib - numpy - jupyter - xarray - openpyxl - pip - pip: - hydrolib-core==0.3.1 - meshkernel==1.0.0 Note that all participants received an e-mail to download the material from the Deltares download portal and to create a Conda environment with the packages automatically installed from environment.yml . Furthermore, a dummy model is provided at the download portal to test the environment. Tips for working in the Jupyter Notebook: \u00b6 Tab : Auto-complete on code Shift + Tab : Tooltip Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell Ctrl + Shift + P : Open command palette Let's get started! Loading libraries \u00b6 Several Python packages are required to run the notebook. These packages are imported below. Please consult the HYDROLIB-core documentation if you want to import additional HYDROLIB-core functionalities later. The import of HYDROLIB-core packages will be simplied in future HYDROLIB-core release (> 0.3.1) In [ ]: Copied! # basic packages import numpy as np import pandas as pd import matplotlib.pyplot as plt # I/O from pathlib import Path # vector/polygon packages import geopandas as gpd from shapely import wkt from shapely.geometry import box # HYDROLIB-core libraries from hydrolib.core.mdu.models import FMModel , AutoStartOption from hydrolib.core.net.models import * from hydrolib.core.crosssection.models import CrossLocModel , CrossDefModel , CrossSection , YZCrsDef from hydrolib.core.friction.models import * from hydrolib.core.bc.models import * from hydrolib.core.ext.models import * from hydrolib.core.inifield.models import * from hydrolib.core.onedfield.models import * from hydrolib.core.structure.models import Weir , FlowDirection , StructureModel # basic packages import numpy as np import pandas as pd import matplotlib.pyplot as plt # I/O from pathlib import Path # vector/polygon packages import geopandas as gpd from shapely import wkt from shapely.geometry import box # HYDROLIB-core libraries from hydrolib.core.mdu.models import FMModel, AutoStartOption from hydrolib.core.net.models import * from hydrolib.core.crosssection.models import CrossLocModel, CrossDefModel, CrossSection, YZCrsDef from hydrolib.core.friction.models import * from hydrolib.core.bc.models import * from hydrolib.core.ext.models import * from hydrolib.core.inifield.models import * from hydrolib.core.onedfield.models import * from hydrolib.core.structure.models import Weir, FlowDirection, StructureModel Connect to data \u00b6 The data for this tutorial is provided via the download portal. EX1 : Change the inputdir to the path of your unzipped data folder. In [ ]: Copied! # Get the directory of the notebook location root = Path . cwd () # Answer EX1 # Specify the path to the data folder inputdir = root / 'data' #inputdir = Path(r\"c:\\checkouts\\HYDROLIB-data_git\\magdalena\") # Get the directory of the notebook location root = Path.cwd() # Answer EX1 # Specify the path to the data folder inputdir = root / 'data' #inputdir = Path(r\"c:\\checkouts\\HYDROLIB-data_git\\magdalena\") Create empty D-Flow FM model \u00b6 To start a model from scratch you need to create first an empty model without data and assign a filepath to the model. In this case a D-Flow FM model is created. The MDU file (master definition file) is the main file of the D-Flow FM model. This is created with the FMModel() function. The fm model object is only created in memory. To save the actual model file, call fm.save() . EX2 : Set the outputdir of the model and give it a name. Verify that an MDU file has been written in your output directory. In [ ]: Copied! # Create empty D-Flow FM model fm = FMModel () # Answer EX2 # Assign filepath to the D-Flow FM model outputdir = root / '1D_model' fm . filepath = outputdir / 'Magdalena_1D.mdu' fm . save () # Create empty D-Flow FM model fm = FMModel() # Answer EX2 # Assign filepath to the D-Flow FM model outputdir = root / '1D_model' fm.filepath = outputdir / 'Magdalena_1D.mdu' fm.save() PART 1: Set up a 1D Delft3D FM model \u00b6 In this part we will build up the complete 1D model schematization step by step. At the end you should have a complete set of model input files for a 1D calculation. Read branches \u00b6 The model will include the lower part of the Magadalena from Cordoba Teton to the river mouth Baranquilla and the Canal del Dique. EX2 : Please investigate the branches variable and answer the following questions for yourself: How many river branches does the model have? What are their names? Which friction type and values are used for each branch? In [ ]: Copied! # Read the branches branches = gpd . read_file ( filename = inputdir / 'branches_Branches.shp' ) # Answer EX3 print ( branches . head ()) # To show the first part of the dataframe print ( branches . Name ) # To get the names of the branches # The model consist of 3 branches # The names of these branches are Channel_1D_1_A, Channel_1D_1_B and Channel_1D_1. # Manning is used as friction type. Branches Channel_1D_1_B and Channel_1D_1 have a friction value of 0.02. Branch Channel_1D_1_A has a value of 0.03. # Read the branches branches = gpd.read_file(filename = inputdir / 'branches_Branches.shp') # Answer EX3 print(branches.head()) # To show the first part of the dataframe print(branches.Name) # To get the names of the branches # The model consist of 3 branches # The names of these branches are Channel_1D_1_A, Channel_1D_1_B and Channel_1D_1. # Manning is used as friction type. Branches Channel_1D_1_B and Channel_1D_1 have a friction value of 0.02. Branch Channel_1D_1_A has a value of 0.03. Create 1D computational grid \u00b6 In the previous step you read the geometry and attributes of the branches into the notebook. These branches will become the network input to our FMModel . The cell below shows how the geometry and name of the branches are assigned to the network. In addition a 1D computational grid ( mesh1d ) with gridpoint every 1000 meter is created on top of this network. Since the network does not yet exist, you need to create an empty network model . Assign the geometry of the branches followed by the generation of the computational grid. The network model should be added to the D-Flow FM model ( fm variable in this notebook) as network in the netfile parameter in the section geometry . Note that you have to specify a filepath for the networkfile. Note that the network model can consist of 1D, 2D flexible mesh ( mesh2d ) and 1D2D links ( links1d2d ). In [ ]: Copied! # Specify 1D computational grid distance dx = 1000.0 # Create an empty network network = Network () # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch in branches . iterrows (): xy = np . transpose ( branch . geometry . xy ) branch_new = Branch ( geometry = xy ) branch_new . generate_nodes ( mesh1d_edge_length = dx ) network . mesh1d_add_branch ( branch_new , name = branch . Name ) # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm . geometry . netfile . network = network fm . geometry . netfile . filepath = \"FlowFM_net.nc\" # Specify 1D computational grid distance dx = 1000.0 # Create an empty network network = Network() # Assign geometry of the branches and generate the computational grid on top of the branches. for index,branch in branches.iterrows(): xy = np.transpose(branch.geometry.xy) branch_new = Branch(geometry=xy) branch_new.generate_nodes(mesh1d_edge_length=dx) network.mesh1d_add_branch(branch_new, name=branch.Name) # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm.geometry.netfile.network = network fm.geometry.netfile.filepath = \"FlowFM_net.nc\" EX3 : Please change the computational grid distance of each branch accordingly: Branch name dx [m] Channel_1D_1_A 1000 Channel_1D_1_B 1000 Channel_1D 500 Tip : Do not forget to create a new network. In [ ]: Copied! # Answer EX3 # Specify 1D computational grid distance dx = [ 1000. , 1000. , 500. ] # Create an empty network network = Network () # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch in branches . iterrows (): xy = np . transpose ( branch . geometry . xy ) branch_new = Branch ( geometry = xy ) branch_new . generate_nodes ( mesh1d_edge_length = dx [ index ]) network . mesh1d_add_branch ( branch_new , name = branch . Name ) network . _mesh1d . _set_mesh1d () # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm . geometry . netfile . network = network fm . geometry . netfile . filepath = \"FlowFM_EX3_net.nc\" # Answer EX3 # Specify 1D computational grid distance dx = [1000., 1000., 500.] # Create an empty network network = Network() # Assign geometry of the branches and generate the computational grid on top of the branches. for index,branch in branches.iterrows(): xy = np.transpose(branch.geometry.xy) branch_new = Branch(geometry=xy) branch_new.generate_nodes(mesh1d_edge_length=dx[index]) network.mesh1d_add_branch(branch_new, name=branch.Name) network._mesh1d._set_mesh1d() # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm.geometry.netfile.network = network fm.geometry.netfile.filepath = \"FlowFM_EX3_net.nc\" The 1D branches are plotted on a map in the figure below. Also, the computational grid points in the mesh1d definition are shown. In [ ]: Copied! # Create a figure with the flowlinks of the model figure , ( ax1 , ax2 ) = plt . subplots ( ncols = 2 ) img = plt . imread ( inputdir / \"osm_background.png\" ) mesh1d_meshkernel = network . _mesh1d . _get_mesh1d () ax1 . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) mesh1d_meshkernel . plot_edges ( ax = ax1 , color = 'red' ) # Add some annotation of branches: for index , branch in branches . iterrows (): middleIndex = int (( len ( branch [ 'geometry' ] . coords ) - 1 ) / 2 ) ax1 . text ( branch [ 'geometry' ] . xy [ 0 ][ middleIndex ], branch [ 'geometry' ] . xy [ 1 ][ middleIndex ], branch [ 'Name' ], ha = 'right' ) # Make a second plot with a zoom-in view of the computational grid points near the junction ax2 . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) ax2 . set_xlim ([ 500000 , 525000 ]) ax2 . set_ylim ([ 1125000 , 1150000 ]) mesh1d_meshkernel . plot_edges ( ax = ax2 , color = 'red' , marker = '.' , markeredgecolor = 'k' , markersize = 1 ) # Create a figure with the flowlinks of the model figure, (ax1, ax2) = plt.subplots(ncols=2) img = plt.imread(inputdir/\"osm_background.png\") mesh1d_meshkernel = network._mesh1d._get_mesh1d() ax1.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) mesh1d_meshkernel.plot_edges(ax=ax1, color='red') # Add some annotation of branches: for index,branch in branches.iterrows(): middleIndex = int((len(branch['geometry'].coords) - 1)/2) ax1.text(branch['geometry'].xy[0][middleIndex], branch['geometry'].xy[1][middleIndex], branch['Name'], ha='right') # Make a second plot with a zoom-in view of the computational grid points near the junction ax2.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) ax2.set_xlim([500000, 525000]) ax2.set_ylim([1125000 ,1150000]) mesh1d_meshkernel.plot_edges(ax=ax2, color='red',marker='.',markeredgecolor='k',markersize=1) Add cross-sections \u00b6 In order to determine the flow area of the 1D model during the computation, you need cross-sections. These cross-sections consist of two components: Cross-section locations ( crosslocfile ): The crosslocfile contains the location of the cross-section on the branches. This is indicated with branchId chainage , where branchId is the name of the branch and chainage the distance to the upstream node. The figure below shows the cross-section locations in grey. In addition the cross-section location consist of the cross-section definition used at that location and a vertical shift of the profile. The latter is mainly used to create a good longitudinal slope over the 1D model (in case of shared cross-sections).

    Cross-section definitions ( crossdeffile ): The crossdeffile has the cross-section definitions in it. These definitions describe the shape of the profile. There are multiple types available: circle, rectangle, ZW- (tabulated), YZ- and XYZ-profiles. Depending on what type of watersystem you try to model you decide which cross-section to use. We recommend to use ZW- or YZ-profiles for rivers.

    Add cross-section locations \u00b6 Below the cross-section locations are read from a CSV-file and added to an empty CrossLocModel . Note that the entire dataframe with the cross-section locations is converted at once to CrossLocModel. More about dataframe handling in HYDROLIB-core can be found here . EX4 : Please investigate the profile_loc variable and answer the following questions for yourself: How many cross-sections are there in the model and per branch? Check the chainage. Also print the cross-sections locations assigned to the D-Flow FM model. Use fm.geometry.crosslocfile.crosssection (part 2). What happens if you only print the first fm.geometry.crosslocfile In [ ]: Copied! # Read profile location file profiles_location_file = inputdir / 'cross_section_locations.csv' profiles_loc = pd . read_csv ( profiles_location_file , index_col = False ) # Answer EX4 - part 1 print ( profiles_loc . head ()) # There are 6 cross-sections in the model with 2 cross-sections per branch. # The chainage of the cross-sections indicate that the profiles are located upstream and downstream of the branch. # Create empty cross-section location model crsloc = CrossLocModel () # Assign filepath to the model crsloc . filepath = 'crsloc.ini' # Convert the dataframe crsloc . crosssection = profiles_loc . to_dict ( \"records\" ) # Assign CrossLocModel to the D-Flow FM model. fm . geometry . crosslocfile = crsloc # Answer EX4 - part 2 print ( fm . geometry . crosslocfile . crosssection ) print ( fm . geometry . crosslocfile ) # You only get filepath relatively to the MDU-file. # Read profile location file profiles_location_file = inputdir / 'cross_section_locations.csv' profiles_loc = pd.read_csv(profiles_location_file, index_col=False) # Answer EX4 - part 1 print(profiles_loc.head()) # There are 6 cross-sections in the model with 2 cross-sections per branch. # The chainage of the cross-sections indicate that the profiles are located upstream and downstream of the branch. # Create empty cross-section location model crsloc = CrossLocModel() # Assign filepath to the model crsloc.filepath = 'crsloc.ini' # Convert the dataframe crsloc.crosssection = profiles_loc.to_dict(\"records\") # Assign CrossLocModel to the D-Flow FM model. fm.geometry.crosslocfile = crsloc # Answer EX4 - part 2 print(fm.geometry.crosslocfile.crosssection) print(fm.geometry.crosslocfile) # You only get filepath relatively to the MDU-file. Add cross-section definitions \u00b6 In the following cell the definitions belonging to the cross-section locations are added to the D-Flow FM model. These cross-sections are all YZ-profiles in order to define natural shape of the river. Please see that the following steps are included: Read the cross-section definitions from an excel. Note that the cross-section definitions id's match with the definitions specified in the crossLocModel. Create an empty CrossDefModel and assign filepath Specify some characteristics for YZ profile. Please consult appendix C.16.1.6 from D-Flow FM 1D2D Create YZCrsDef for each profile definition. Append the definition to the CrossDefModel. Append the CrossDefModel to the D-Flow FM model. In [ ]: Copied! # Create cross-section definitions profiles_file = inputdir / '1D_YZ_CrossSections.xlsx' profiles = pd . read_excel ( profiles_file , sheet_name = None ) names = list ( profiles . keys ()) print ( names ) # Create empty CrossDefModel crsdef = CrossDefModel () crsdef . filepath = 'crsdef.ini' # Specify some charachteristics for YZ profile type_crs = 'yz' thalweg = 0.0 singleValued = 'yes' conveyance = 'segmented' sectionCount = 1 # Create the YZ profiles and append them to the CrossDefModel for name in names : yzCount = len ( profiles [ name ] . values ) ycoord = profiles [ name ] . y . to_list () zcoord = profiles [ name ] . z . to_list () frictionIds = 'channels' frictionPositions = [ profiles [ name ] . y [ 0 ], profiles [ name ] . y [ yzCount - 1 ]] crosssection = YZCrsDef ( id = name , type = type_crs , thalweg = thalweg , singleValuedZ = singleValued , conveyance = conveyance , yzCount = yzCount , yCoordinates = ycoord , zCoordinates = zcoord , sectionCount = sectionCount , frictionIds = frictionIds , frictionPositions = frictionPositions ) crsdef . definition . append ( crosssection ) print ( f 'definition of { name } added to cross-section model' ) # Append CrossDefModel to D-Flow FM model fm . geometry . crossdeffile = crsdef # Create cross-section definitions profiles_file = inputdir / '1D_YZ_CrossSections.xlsx' profiles = pd.read_excel(profiles_file, sheet_name=None) names = list(profiles.keys()) print(names) # Create empty CrossDefModel crsdef = CrossDefModel() crsdef.filepath = 'crsdef.ini' # Specify some charachteristics for YZ profile type_crs = 'yz' thalweg = 0.0 singleValued = 'yes' conveyance = 'segmented' sectionCount = 1 # Create the YZ profiles and append them to the CrossDefModel for name in names: yzCount = len(profiles[name].values) ycoord = profiles[name].y.to_list() zcoord = profiles[name].z.to_list() frictionIds = 'channels' frictionPositions = [profiles[name].y[0], profiles[name].y[yzCount-1]] crosssection = YZCrsDef(id=name, type=type_crs, thalweg=thalweg, singleValuedZ=singleValued, conveyance=conveyance, yzCount=yzCount, yCoordinates= ycoord, zCoordinates=zcoord, sectionCount=sectionCount, frictionIds = frictionIds, frictionPositions=frictionPositions) crsdef.definition.append(crosssection) print(f'definition of {name} added to cross-section model') # Append CrossDefModel to D-Flow FM model fm.geometry.crossdeffile = crsdef Add roughness \u00b6 The 1D model has now a network topology, computational 1D grid and cross-sections. Friction is a component that should be added to the model to get the proper bed roughness and channel conveyance. In this step you will add the FrictionModel to the D-Flow FM model by specifying the friction type and value at the upstream cross-section location (chainage=1000.0 m) of each branch in the model ( FrictBranch ). Also a global roughness section is specified ( FrictGlobal ). This global section is used when there is no friction type and values specified for a specific branch. It also contains the frictionId. In the cross-section definition model a reference is made to this frictionId. You can check this with the commands below and search for frictionIds . In [ ]: Copied! # Print directly the modelobject (in this case all definitions) print ( fm . geometry . crossdeffile . definition ) # Or convert it first to a dataframe df_def = pd . DataFrame ([ f . __dict__ for f in fm . geometry . crossdeffile . definition ]) print ( df_def [[ 'frictionids' ]]) # Print directly the modelobject (in this case all definitions) print(fm.geometry.crossdeffile.definition) # Or convert it first to a dataframe df_def = pd.DataFrame([f.__dict__ for f in fm.geometry.crossdeffile.definition]) print(df_def[['frictionids']]) Note that YZ profiles can refer to multiple frictionIds, since the friction can vary over the cross-section. Hence the frictionId is given in a List() . This means indirectly that multiple FrictionModels can be added to one D-Flow FM model. The created FrictionModel should therefore been added in a List() to the D-Flow FM model. In [ ]: Copied! # Specify frictionId(s) for the FrictionModel(s) friction_name = 'channels' # Specify for each FrictionModel a global type and value global_type = FrictionType . manning # Options are chezy,debosbijkerk, manning, strickler, stricklernikuradse, wallawnikuradse, whitecolebrook global_value = 0.023 # Create empty friction model and assign filepath roughness = FrictionModel () roughness . filepath = \"roughness-channels.ini\" # often we specify the filenames as \"roughness-frictionId.ini\" # Create global friction model and add it to frictionmodel roughness . global_ = FrictGlobal ( frictionId = friction_name , frictionType = global_type , frictionValue = global_value ) # Add friction from branches function_type = 'constant' # This model uses constant friction per branch df_friction = branches [[ 'Name' , 'fric_type' , 'fric_value' , 'chainage' ]] df_friction . columns = [ 'branchId' , 'frictionType' , 'frictionValues' , 'chainage' ] df_friction = df_friction . assign ( frictionValues = [[ i ] for i in df_friction . frictionValues . values ]) df_friction = df_friction . assign ( functionType = function_type ) df_friction = df_friction . assign ( chainage = [[ i ] for i in df_friction . chainage . values ]) df_friction = df_friction . assign ( numlocations = 1 ) # you can specify multiple location along the branch with different friction values. roughness . branch = df_friction . to_dict ( 'records' ) # the dataframe is converted to FrictBranch models at once # Add frictionmodel to the D-Flow FM model. fm . geometry . frictfile = [ roughness ] # frictfile is a list of frictionModels # Specify frictionId(s) for the FrictionModel(s) friction_name = 'channels' # Specify for each FrictionModel a global type and value global_type = FrictionType.manning # Options are chezy,debosbijkerk, manning, strickler, stricklernikuradse, wallawnikuradse, whitecolebrook global_value = 0.023 # Create empty friction model and assign filepath roughness = FrictionModel() roughness.filepath = \"roughness-channels.ini\" # often we specify the filenames as \"roughness-frictionId.ini\" # Create global friction model and add it to frictionmodel roughness.global_ = FrictGlobal(frictionId=friction_name,frictionType=global_type,frictionValue=global_value) # Add friction from branches function_type = 'constant' # This model uses constant friction per branch df_friction = branches[['Name', 'fric_type', 'fric_value', 'chainage']] df_friction.columns = ['branchId','frictionType','frictionValues', 'chainage'] df_friction = df_friction.assign(frictionValues = [[i] for i in df_friction.frictionValues.values]) df_friction = df_friction.assign(functionType=function_type) df_friction = df_friction.assign(chainage = [[i] for i in df_friction.chainage.values]) df_friction = df_friction.assign(numlocations=1) # you can specify multiple location along the branch with different friction values. roughness.branch = df_friction.to_dict('records') # the dataframe is converted to FrictBranch models at once # Add frictionmodel to the D-Flow FM model. fm.geometry.frictfile = [roughness] # frictfile is a list of frictionModels EX5 : Let's build another frictionmodel with frictionId dique representing the friction in Canal del Dique. This frictionmodel assumes Chezy as global friction type and has a friction value of 45. In [ ]: Copied! # Answer to EX5 # Specify frictionId(s) for the FrictionModel(s) friction_id2 = 'dique' # Specify for each FrictionModel a global type and value global_type2 = FrictionType . chezy global_value2 = 45.0 # Create empty friction model and assign filepath roughness_dique = FrictionModel () roughness_dique . filepath = 'roughness-dique.ini' # Create global friction model and add it to frictionmodel roughness_dique . global_ = FrictGlobal ( frictionId = friction_id2 , frictionType = global_type2 , frictionValue = global_value2 ) # Add frictionmodels to the D-Flow FM model. fm . geometry . frictfile = [ roughness , roughness_dique ] # Note that the other friction needs to be added to the list. # Answer to EX5 # Specify frictionId(s) for the FrictionModel(s) friction_id2 = 'dique' # Specify for each FrictionModel a global type and value global_type2 = FrictionType.chezy global_value2 = 45.0 # Create empty friction model and assign filepath roughness_dique = FrictionModel() roughness_dique.filepath = 'roughness-dique.ini' # Create global friction model and add it to frictionmodel roughness_dique.global_ = FrictGlobal(frictionId=friction_id2,frictionType=global_type2,frictionValue=global_value2) # Add frictionmodels to the D-Flow FM model. fm.geometry.frictfile = [roughness, roughness_dique] # Note that the other friction needs to be added to the list. The cross-sections on the Canal del Dique (Channel_1D_1) do not refer to this new frictionId. Please uncomment the code below to change this after completion of exercise 5. In [ ]: Copied! # Convert crosssection defintions from D-Flow FM model to dataframe df_def = pd . DataFrame ([ f . __dict__ for f in fm . geometry . crossdeffile . definition ]) print ( df_def ) # Check which cross-section locations are located on Channel_1D_1 df_loc = pd . DataFrame ([ f . __dict__ for f in fm . geometry . crosslocfile . crosssection ]) print ( df_loc . loc [:,[ 'id' , 'branchid' , 'definitionid' ]]) # To which definition do these locations refer: defs = df_loc . loc [ df_loc . index [ df_loc . branchid == 'Channel_1D_1' ], 'definitionid' ] . values # Change the Frictionids to dique for Channel_1D_1 index_defs = df_def . index [ df_def . id . isin ( defs )] for i in index_defs : df_def . loc [ i , 'frictionids' ] = [ 'dique' ] # Overwrite the definitions in D-Flow FM model with the changes in the dataframe fm . geometry . crossdeffile . definition = df_def . to_dict ( \"records\" ) # Convert crosssection defintions from D-Flow FM model to dataframe df_def = pd.DataFrame([f.__dict__ for f in fm.geometry.crossdeffile.definition]) print(df_def) # Check which cross-section locations are located on Channel_1D_1 df_loc = pd.DataFrame([f.__dict__ for f in fm.geometry.crosslocfile.crosssection]) print(df_loc.loc[:,['id','branchid','definitionid']]) # To which definition do these locations refer: defs = df_loc.loc[df_loc.index[df_loc.branchid=='Channel_1D_1'],'definitionid'].values # Change the Frictionids to dique for Channel_1D_1 index_defs = df_def.index[df_def.id.isin(defs)] for i in index_defs: df_def.loc[i, 'frictionids'] = ['dique'] # Overwrite the definitions in D-Flow FM model with the changes in the dataframe fm.geometry.crossdeffile.definition = df_def.to_dict(\"records\") Add boundary conditions to the model \u00b6 Fluvial floods occur when water levels in the river are too high. These high water levels in the rivers can result from several factors. One of those is the occurence of heavy rainfall in the upstream catchment. These heavy rainstorm can lead to a high discharge wave entering the upstream boundary of the river. In this tutorial you will model such a high discharge wave (time series) at the upstream 1D boundary (node id = '521410.278872_1056811.761107'). For the two downstream boundaries (node ids = [wkt_geom Name BridgeCount CrossSectio CulvertCoun GateCount GeometryLen IsLengthCus LateralSour Length LongName OrderNumber PumpCount Source StructureCo Target WeirCount fric_type fric_value chainage]) a constant water level of 0 m AD is assumed. Note that this are tidal boundaries in reality. In order to apply boundary conditions on a model you need two components: Forcing (.bc) file ForcingModel : This model contains the forcing value, time series, astronomical tide, realtime connection with other modules (D-RR) or QHtable. The first two options are created in this tutorial. External Forcing (.ext) file ExtModel : The external forcing specifies the location and type of forcing. Types of forcing are Boundary , Lateral and meteo. In [ ]: Copied! # Get node ids of branches node_ids = fm . geometry . netfile . network . _mesh1d . network1d_node_id print ( node_ids ) # Specify the node ids node_upstream = node_ids [ 0 ] # discharge time series node nodes_downstream = node_ids [ 2 :] # water level nodes # Create an empty external forcing model and forcing model ext = ExtModel () ext . filepath = 'boundary_new.ext' bc = ForcingModel () #bc.filepath = inputdir / 'BoundaryConditions.bc' # Read the upstream boundary time series from excel discharge_file = inputdir / '1D_BoundaryConditions.xlsx' discharge = pd . read_excel ( discharge_file , sheet_name = [ 0 ]) # Create the timeseries bc_up = TimeSeries ( name = node_upstream , nodeid = node_upstream , timeinterpolation = TimeInterpolation . linear , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2012-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], datablock = [[ time , dis ] for [ time , dis ] in discharge [ 0 ] . values ] ) # Create downstream constant boundaries bc_dn1 = Constant ( name = nodes_downstream [ 0 ], nodeid = nodes_downstream [ 0 ], quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], datablock = [[ \"0.0\" ]] ) bc_dn2 = Constant ( name = nodes_downstream [ 1 ], nodeid = nodes_downstream [ 1 ], quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], datablock = [[ \"0.0\" ]] ) # Add the forcing to ForcingModel bc . forcing . extend ([ bc_up , bc_dn1 , bc_dn2 ]) # Create boundary locations in ExtModel ext_up = Boundary ( quantity = 'dischargebnd' , nodeid = node_upstream , forcingfile = bc ) ext_dn1 = Boundary ( quantity = 'waterlevelbnd' , nodeid = nodes_downstream [ 0 ], forcingfile = bc ) ext_dn2 = Boundary ( quantity = 'waterlevelbnd' , nodeid = nodes_downstream [ 1 ], forcingfile = bc ) # Add the boundaries to ExtModel ext . boundary . extend ([ ext_up , ext_dn1 , ext_dn2 ]) # Add the ExtModel to D-Flow FM model fm . external_forcing . extforcefilenew = ext # Get node ids of branches node_ids = fm.geometry.netfile.network._mesh1d.network1d_node_id print(node_ids) # Specify the node ids node_upstream = node_ids[0] # discharge time series node nodes_downstream = node_ids[2:] # water level nodes # Create an empty external forcing model and forcing model ext = ExtModel() ext.filepath = 'boundary_new.ext' bc = ForcingModel() #bc.filepath = inputdir / 'BoundaryConditions.bc' # Read the upstream boundary time series from excel discharge_file = inputdir / '1D_BoundaryConditions.xlsx' discharge = pd.read_excel(discharge_file, sheet_name=[0]) # Create the timeseries bc_up = TimeSeries( name = node_upstream, nodeid = node_upstream, timeinterpolation = TimeInterpolation.linear, quantityunitpair = [QuantityUnitPair(quantity = 'time', unit = 'minutes since 2012-01-01 00:00:00'), QuantityUnitPair(quantity = 'dischargebnd', unit = 'm\u00b3/s')], datablock = [[time, dis] for [time,dis] in discharge[0].values] ) # Create downstream constant boundaries bc_dn1 = Constant( name = nodes_downstream[0], nodeid = nodes_downstream[0], quantityunitpair = [QuantityUnitPair(quantity = 'waterlevelbnd', unit = 'm')], datablock = [[\"0.0\"]] ) bc_dn2 = Constant( name = nodes_downstream[1], nodeid = nodes_downstream[1], quantityunitpair = [QuantityUnitPair(quantity = 'waterlevelbnd', unit = 'm')], datablock = [[\"0.0\"]] ) # Add the forcing to ForcingModel bc.forcing.extend([bc_up,bc_dn1,bc_dn2]) # Create boundary locations in ExtModel ext_up = Boundary( quantity = 'dischargebnd', nodeid = node_upstream, forcingfile = bc ) ext_dn1 = Boundary( quantity = 'waterlevelbnd', nodeid = nodes_downstream[0], forcingfile = bc ) ext_dn2 = Boundary( quantity = 'waterlevelbnd', nodeid = nodes_downstream[1], forcingfile = bc ) # Add the boundaries to ExtModel ext.boundary.extend([ext_up,ext_dn1,ext_dn2]) # Add the ExtModel to D-Flow FM model fm.external_forcing.extforcefilenew = ext Add initial conditions \u00b6 For this model an initial water depth of 1.0 meter is assumed in the 1D model. Below you can see how this initial waterdepth is added to the D-Flow FM model using the following steps: Creating 1D initial conditions field ( 1DField ), which contains the actual waterdepths on each branch. Note that the file is seperately saved from the rest of the model. Creating IniFieldModel (= Initial and parameter field files) in which we collect the initial condition specified in step 1, so that it can be added to the FMModel . In [ ]: Copied! # Create 1D initial conditions field ini_1d = OneDFieldModel () ini_1d . global_ = OneDFieldGlobal ( quantity = 'waterdepth' , unit = 'm' , value = 1.0 ) # only global values are needed in this case, but you could also specify it per branch. ini_1d . filepath = 'initialwaterdepth.ini' ini_1d . save ( outputdir / ini_1d . filepath ) # 1D field ini files needs to be saved seperately from the model save. # Create initial field file ini_field = IniFieldModel () ini_field . filepath = 'inifield.ini' ini_field . initial = InitialField ( quantity = 'waterdepth' , datafile = ini_1d . filepath , datafiletype = DataFileType . onedfield ) fm . geometry . inifieldfile = ini_field # Create 1D initial conditions field ini_1d = OneDFieldModel() ini_1d.global_ = OneDFieldGlobal(quantity='waterdepth', unit='m', value=1.0) # only global values are needed in this case, but you could also specify it per branch. ini_1d.filepath = 'initialwaterdepth.ini' ini_1d.save(outputdir / ini_1d.filepath) # 1D field ini files needs to be saved seperately from the model save. # Create initial field file ini_field = IniFieldModel() ini_field.filepath = 'inifield.ini' ini_field.initial = InitialField(quantity='waterdepth',datafile=ini_1d.filepath, datafiletype=DataFileType.onedfield) fm.geometry.inifieldfile = ini_field Add a weir to the model \u00b6 Many lakes occur close along Canal del Dique. See figure below. This tutorial assumes that these lakes can function as extra storage for the floods from the river. Hence a weir structure, functioning as a small dam, is added downstream of the lakes. This weir structure has the following conditions: It is located at 70 km from the upstream node of the branch. The crestlevel is 4.0 m AD. The crest width is 105.0 m. The flow over the dam is in both directions.

    In [ ]: Copied! # Create weir structure weir = Weir ( id = 'fictive_dam' , name = 'fictive_dam' , branchId = 'Channel_1D_1' , chainage = 70000.0 , allowedFlowDir = FlowDirection . both , crestLevel = 4.0 , crestWidth = 105.0 , corrCoeff = 1.000 , useVelocityHeight = True ) # Create structure model struc = StructureModel () struc . filepath = 'structure.ini' # Append weir to structure struc . structure . append ( weir ) # Assign structure model to D-Flow FM model fm . geometry . structurefile = [ struc ] # Create weir structure weir = Weir( id='fictive_dam', name = 'fictive_dam', branchId='Channel_1D_1', chainage=70000.0, allowedFlowDir=FlowDirection.both, crestLevel=4.0, crestWidth=105.0, corrCoeff=1.000, useVelocityHeight=True ) # Create structure model struc = StructureModel() struc.filepath = 'structure.ini' # Append weir to structure struc.structure.append(weir) # Assign structure model to D-Flow FM model fm.geometry.structurefile = [struc] EX6 : You found out that the dam should be significantly higher. Hence you increase the crestlevel to 10.0 m AD. Your client also decided that flow can only occur from upstream to downstream. Please change the weir above. In [ ]: Copied! # Answer EX6: # Create weir structure weir = Weir ( id = 'fictive_dam' , name = 'fictive_dam' , branchId = 'Channel_1D_1' , chainage = 70000.0 , allowedFlowDir = FlowDirection . positive , crestLevel = 10.0 , crestWidth = 105.0 , corrCoeff = 1.000 , useVelocityHeight = True ) # Create structure model struc = StructureModel () struc . filepath = 'structure.ini' # Append weir to structure struc . structure . append ( weir ) # Assign structure model to D-Flow FM model fm . geometry . structurefile = [ struc ] # Answer EX6: # Create weir structure weir = Weir( id='fictive_dam', name = 'fictive_dam', branchId='Channel_1D_1', chainage=70000.0, allowedFlowDir=FlowDirection.positive, crestLevel=10.0, crestWidth=105.0, corrCoeff=1.000, useVelocityHeight=True ) # Create structure model struc = StructureModel() struc.filepath = 'structure.ini' # Append weir to structure struc.structure.append(weir) # Assign structure model to D-Flow FM model fm.geometry.structurefile = [struc] Save 1D model \u00b6 The 1D model is now finished. The commands below are used to save the model to the correct filepath (specified for the MDU-file). Note that the recurse is set to True to make sure all underlying model files are written to the directory. Else the MDU-file will be the only file written to the directory. In [ ]: Copied! # Change some time settings fm . time . refdate = '20120101' fm . time . dtuser = 60. # seconds fm . time . tstart = 43200. fm . time . tstop = 561600. # Save the 1D model. fm . general . autostart = AutoStartOption . no # This is a workaround for a bug in hydrolib-core 0.3.1 fm . save ( recurse = True ) # Change some time settings fm.time.refdate = '20120101' fm.time.dtuser = 60. # seconds fm.time.tstart = 43200. fm.time.tstop = 561600. # Save the 1D model. fm.general.autostart = AutoStartOption.no # This is a workaround for a bug in hydrolib-core 0.3.1 fm.save(recurse=True) PART 2: Extend to a 1D2D Delft3D FM model \u00b6 We will now continue with the model fm from part 1, and add a 2D mesh to it, as well as 1D2D couplings. Create 2D flexible mesh \u00b6 We use a shapefile with the area of interest to define the extent of the new 2D mesh that is to be generated. First, a uniform rectilinear mesh is generated, after which it can be clipped. EX7 : Create a rectangular grid with a cell size of 2500 by 2500 meter. Use create_rectilinear() function. EX8 : Clip the rectangular grid with the clip_geom using clip() function. In [ ]: Copied! # Read grid outline gdf_grid = gpd . read_file ( inputdir / 'outline_2D_grid.shp' ) # Determine the boundary box extent = gdf_grid . geometry [ 0 ] . bounds # Create uniform rectilinear mesh mesh2d = Mesh2d () # Answer EX7 mesh2d . create_rectilinear ( extent = extent , dx = 2500.0 , dy = 2500.0 ) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np . array ( gdf_grid . geometry [ 0 ] . exterior . xy ) clip_geom = GeometryList ( clip_polygon [ 0 ], clip_polygon [ 1 ]) # Answer EX8 mesh2d . clip ( clip_geom ) fm . geometry . netfile . network . _mesh2d = mesh2d fm . geometry . netfile . filepath = \"FlowFM_1D2D_net.nc\" # Read grid outline gdf_grid = gpd.read_file(inputdir / 'outline_2D_grid.shp') # Determine the boundary box extent = gdf_grid.geometry[0].bounds # Create uniform rectilinear mesh mesh2d = Mesh2d() # Answer EX7 mesh2d.create_rectilinear( extent=extent, dx=2500.0, dy=2500.0 ) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np.array(gdf_grid.geometry[0].exterior.xy) clip_geom = GeometryList(clip_polygon[0],clip_polygon[1]) # Answer EX8 mesh2d.clip(clip_geom) fm.geometry.netfile.network._mesh2d = mesh2d fm.geometry.netfile.filepath = \"FlowFM_1D2D_net.nc\" The cell below produces a basic plot of the 1D + 2D mesh. In [ ]: Copied! # Create a plot mesh2d_mk = network . _mesh2d . get_mesh2d () mesh1d_mk = network . _mesh1d . _get_mesh1d () figure , ax = plt . subplots () ax . set_aspect ( 'equal' ) plt . rcParams [ \"figure.figsize\" ] = 10 , 10 ax . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) # Plot the 1D2D network mesh2d_mk . plot_edges ( ax = ax , color = \"orange\" ) mesh1d_mk . plot_edges ( ax = ax , color = 'blue' ) # Create a plot mesh2d_mk = network._mesh2d.get_mesh2d() mesh1d_mk = network._mesh1d._get_mesh1d() figure, ax = plt.subplots() ax.set_aspect('equal') plt.rcParams[\"figure.figsize\"]=10,10 ax.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) # Plot the 1D2D network mesh2d_mk.plot_edges(ax=ax, color=\"orange\") mesh1d_mk.plot_edges(ax=ax, color='blue') Local refinement of the 2D mesh \u00b6 One of the key functionalities of Delft3D Flexible Mesh is that you can refine the 2D grid locally. The cell below shows how the grid is locally refined around the river by executing the refinement algorithm once ( level=1 ). In [ ]: Copied! # Create empty mesh2d object mesh2d = Mesh2d () # Create rectangular grid mesh2d . create_rectilinear ( extent = extent , dx = 2500.0 , dy = 2500.0 ) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np . array ( gdf_grid . geometry [ 0 ] . exterior . xy ) clip_geom = GeometryList ( clip_polygon [ 0 ], clip_polygon [ 1 ]) mesh2d . clip ( clip_geom ) # Refine the coarse uniform grid in a buffer region around the rivers gdf_refine = gpd . read_file ( inputdir / 'buffer_around_river_proj.shp' ) refine_polygon = np . array ( gdf_refine . geometry [ 0 ] . exterior . xy ) refine_geom = GeometryList ( refine_polygon [ 0 ], refine_polygon [ 1 ]) mesh2d . refine ( refine_geom , level = 1 ) fm . geometry . netfile . network . _mesh2d = mesh2d fm . geometry . netfile . filepath = \"FlowFM_1D2D_refined_net.nc\" # Create empty mesh2d object mesh2d = Mesh2d() # Create rectangular grid mesh2d.create_rectilinear( extent=extent, dx=2500.0, dy=2500.0 ) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np.array(gdf_grid.geometry[0].exterior.xy) clip_geom = GeometryList(clip_polygon[0],clip_polygon[1]) mesh2d.clip(clip_geom) # Refine the coarse uniform grid in a buffer region around the rivers gdf_refine = gpd.read_file(inputdir / 'buffer_around_river_proj.shp') refine_polygon = np.array(gdf_refine.geometry[0].exterior.xy) refine_geom = GeometryList(refine_polygon[0], refine_polygon[1]) mesh2d.refine(refine_geom, level=1) fm.geometry.netfile.network._mesh2d = mesh2d fm.geometry.netfile.filepath = \"FlowFM_1D2D_refined_net.nc\" In [ ]: Copied! # Create a plot mesh2d_mk = network . _mesh2d . get_mesh2d () mesh1d_mk = network . _mesh1d . _get_mesh1d () figure , ax = plt . subplots () ax . set_aspect ( 'equal' ) plt . rcParams [ \"figure.figsize\" ] = 10 , 10 ax . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) # Plot the 1D2D network mesh2d_mk . plot_edges ( ax = ax , color = \"orange\" ) mesh1d_mk . plot_edges ( ax = ax , color = 'blue' ) # Create a plot mesh2d_mk = network._mesh2d.get_mesh2d() mesh1d_mk = network._mesh1d._get_mesh1d() figure, ax = plt.subplots() ax.set_aspect('equal') plt.rcParams[\"figure.figsize\"]=10,10 ax.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) # Plot the 1D2D network mesh2d_mk.plot_edges(ax=ax, color=\"orange\") mesh1d_mk.plot_edges(ax=ax, color='blue') Save 1D2D model \u00b6 The 1D2D model is now finished. The commands below are used to save the model to the correct filepath (specified for the MDU-file). Note that the recurse is set to True to make sure all underlying model files are written to the directory. Else the MDU-file will be the only file written to the directory. Note that the 1D2D links will be generated in the Delft3D FM 1D2D software. Future releases of HYDROLIB-core will consist of 1D2D functionalities. In [ ]: Copied! # Change fm outputdir_1d2d = root / '1D2D_model' fm . filepath = outputdir_1d2d / 'Magdalena_1D2D.mdu' fm . general . autostart = AutoStartOption . no fm . save ( recurse = True ) # Change fm outputdir_1d2d = root / '1D2D_model' fm.filepath = outputdir_1d2d / 'Magdalena_1D2D.mdu' fm.general.autostart = AutoStartOption.no fm.save(recurse=True)","title":"Tutorial Delft3D FM 1D2D fluvial flood model of Magdalena river"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#tutorial-delft3d-fm-1d2d-fluvial-flood-model-of-magdalena-river","text":"This notebook is an introduction on how to use HYDROLIB-core functionalities to create and adjust a Delft3D FM Suite 1D2D fluvial flood model of the Magdalena river in Columbia. First a 1D river model of the Magdalena river and Canal del Dique will be created, shown in the left figure. This model will be extended with a 2D Flexible Mesh, with a uniform roughness field. Adding a DTM on that 2D mesh is currently not part of this tutorial, but normally this is of course indispensible to mimic the fluvial flood patterns. Running the model or importing the model in the Delft3D FM Suite 1D2D is not shown in this tutorial. Note that the model and tutorial are created for educational purposes and consist partially of fictive/unvalidated model data. HYDROLIB-core is the core library of Python wrappers around the D-HYDRO Suite 1D2D model files (input and output) and model engines (kernel libraries). HYDROLIB is a Python package with tools for pre-processing, post-processing and analysis of hydrodynamical data and simulation results, currently focused on Delft3D Suite 1D2D. HYDROLIB builds upon the basic HYDROLIB-core functionalities. The goal of this tutorial is to familiarize modelers with how to apply HYDROLIB-core functionalities in their modelling procedures for building new models or adjusting existing models. As mentioned above, you will create an 1D2D fluvial flood model from scratch using the D-Flow FM HYDROLIB-core functionalities and the underlying functions from mesh generation ( MeshKernelPy ). The building of the model is done by the following steps Loading libraries Connect to data folder Create empty D-Flow FM model Read branches Create computational grid Add cross-sections Add roughness Add boundary conditions Add initial conditions Add a weir to the model Save 1D model Create 2D flexible mesh Add 2D DTM to model Save 1D2D model Note that HYDROLIB-core also contains functionalities to setup lumped rainfall runoff models ( D-RR ) and to apply real-time control at structures ( D-RTC ), but these are not covered in this tutorial.","title":"Tutorial Delft3D FM 1D2D fluvial flood model of Magdalena river"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#installation","text":"To run this notebook a simple Python environment with the following packages is required: - python=3.9 - pandas - geopandas - pyogrio - matplotlib - numpy - jupyter - xarray - openpyxl - pip - pip: - hydrolib-core==0.3.1 - meshkernel==1.0.0 Note that all participants received an e-mail to download the material from the Deltares download portal and to create a Conda environment with the packages automatically installed from environment.yml . Furthermore, a dummy model is provided at the download portal to test the environment.","title":"Installation"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#tips-for-working-in-the-jupyter-notebook","text":"Tab : Auto-complete on code Shift + Tab : Tooltip Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell Ctrl + Shift + P : Open command palette Let's get started!","title":"Tips for working in the Jupyter Notebook:"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#loading-libraries","text":"Several Python packages are required to run the notebook. These packages are imported below. Please consult the HYDROLIB-core documentation if you want to import additional HYDROLIB-core functionalities later. The import of HYDROLIB-core packages will be simplied in future HYDROLIB-core release (> 0.3.1) In [ ]: Copied! # basic packages import numpy as np import pandas as pd import matplotlib.pyplot as plt # I/O from pathlib import Path # vector/polygon packages import geopandas as gpd from shapely import wkt from shapely.geometry import box # HYDROLIB-core libraries from hydrolib.core.mdu.models import FMModel , AutoStartOption from hydrolib.core.net.models import * from hydrolib.core.crosssection.models import CrossLocModel , CrossDefModel , CrossSection , YZCrsDef from hydrolib.core.friction.models import * from hydrolib.core.bc.models import * from hydrolib.core.ext.models import * from hydrolib.core.inifield.models import * from hydrolib.core.onedfield.models import * from hydrolib.core.structure.models import Weir , FlowDirection , StructureModel # basic packages import numpy as np import pandas as pd import matplotlib.pyplot as plt # I/O from pathlib import Path # vector/polygon packages import geopandas as gpd from shapely import wkt from shapely.geometry import box # HYDROLIB-core libraries from hydrolib.core.mdu.models import FMModel, AutoStartOption from hydrolib.core.net.models import * from hydrolib.core.crosssection.models import CrossLocModel, CrossDefModel, CrossSection, YZCrsDef from hydrolib.core.friction.models import * from hydrolib.core.bc.models import * from hydrolib.core.ext.models import * from hydrolib.core.inifield.models import * from hydrolib.core.onedfield.models import * from hydrolib.core.structure.models import Weir, FlowDirection, StructureModel","title":"Loading libraries"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#connect-to-data","text":"The data for this tutorial is provided via the download portal. EX1 : Change the inputdir to the path of your unzipped data folder. In [ ]: Copied! # Get the directory of the notebook location root = Path . cwd () # Answer EX1 # Specify the path to the data folder inputdir = root / 'data' #inputdir = Path(r\"c:\\checkouts\\HYDROLIB-data_git\\magdalena\") # Get the directory of the notebook location root = Path.cwd() # Answer EX1 # Specify the path to the data folder inputdir = root / 'data' #inputdir = Path(r\"c:\\checkouts\\HYDROLIB-data_git\\magdalena\")","title":"Connect to data"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#create-empty-d-flow-fm-model","text":"To start a model from scratch you need to create first an empty model without data and assign a filepath to the model. In this case a D-Flow FM model is created. The MDU file (master definition file) is the main file of the D-Flow FM model. This is created with the FMModel() function. The fm model object is only created in memory. To save the actual model file, call fm.save() . EX2 : Set the outputdir of the model and give it a name. Verify that an MDU file has been written in your output directory. In [ ]: Copied! # Create empty D-Flow FM model fm = FMModel () # Answer EX2 # Assign filepath to the D-Flow FM model outputdir = root / '1D_model' fm . filepath = outputdir / 'Magdalena_1D.mdu' fm . save () # Create empty D-Flow FM model fm = FMModel() # Answer EX2 # Assign filepath to the D-Flow FM model outputdir = root / '1D_model' fm.filepath = outputdir / 'Magdalena_1D.mdu' fm.save()","title":"Create empty D-Flow FM model"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#part-1-set-up-a-1d-delft3d-fm-model","text":"In this part we will build up the complete 1D model schematization step by step. At the end you should have a complete set of model input files for a 1D calculation.","title":"PART 1: Set up a 1D Delft3D FM model"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#read-branches","text":"The model will include the lower part of the Magadalena from Cordoba Teton to the river mouth Baranquilla and the Canal del Dique. EX2 : Please investigate the branches variable and answer the following questions for yourself: How many river branches does the model have? What are their names? Which friction type and values are used for each branch? In [ ]: Copied! # Read the branches branches = gpd . read_file ( filename = inputdir / 'branches_Branches.shp' ) # Answer EX3 print ( branches . head ()) # To show the first part of the dataframe print ( branches . Name ) # To get the names of the branches # The model consist of 3 branches # The names of these branches are Channel_1D_1_A, Channel_1D_1_B and Channel_1D_1. # Manning is used as friction type. Branches Channel_1D_1_B and Channel_1D_1 have a friction value of 0.02. Branch Channel_1D_1_A has a value of 0.03. # Read the branches branches = gpd.read_file(filename = inputdir / 'branches_Branches.shp') # Answer EX3 print(branches.head()) # To show the first part of the dataframe print(branches.Name) # To get the names of the branches # The model consist of 3 branches # The names of these branches are Channel_1D_1_A, Channel_1D_1_B and Channel_1D_1. # Manning is used as friction type. Branches Channel_1D_1_B and Channel_1D_1 have a friction value of 0.02. Branch Channel_1D_1_A has a value of 0.03.","title":"Read branches"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#create-1d-computational-grid","text":"In the previous step you read the geometry and attributes of the branches into the notebook. These branches will become the network input to our FMModel . The cell below shows how the geometry and name of the branches are assigned to the network. In addition a 1D computational grid ( mesh1d ) with gridpoint every 1000 meter is created on top of this network. Since the network does not yet exist, you need to create an empty network model . Assign the geometry of the branches followed by the generation of the computational grid. The network model should be added to the D-Flow FM model ( fm variable in this notebook) as network in the netfile parameter in the section geometry . Note that you have to specify a filepath for the networkfile. Note that the network model can consist of 1D, 2D flexible mesh ( mesh2d ) and 1D2D links ( links1d2d ). In [ ]: Copied! # Specify 1D computational grid distance dx = 1000.0 # Create an empty network network = Network () # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch in branches . iterrows (): xy = np . transpose ( branch . geometry . xy ) branch_new = Branch ( geometry = xy ) branch_new . generate_nodes ( mesh1d_edge_length = dx ) network . mesh1d_add_branch ( branch_new , name = branch . Name ) # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm . geometry . netfile . network = network fm . geometry . netfile . filepath = \"FlowFM_net.nc\" # Specify 1D computational grid distance dx = 1000.0 # Create an empty network network = Network() # Assign geometry of the branches and generate the computational grid on top of the branches. for index,branch in branches.iterrows(): xy = np.transpose(branch.geometry.xy) branch_new = Branch(geometry=xy) branch_new.generate_nodes(mesh1d_edge_length=dx) network.mesh1d_add_branch(branch_new, name=branch.Name) # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm.geometry.netfile.network = network fm.geometry.netfile.filepath = \"FlowFM_net.nc\" EX3 : Please change the computational grid distance of each branch accordingly: Branch name dx [m] Channel_1D_1_A 1000 Channel_1D_1_B 1000 Channel_1D 500 Tip : Do not forget to create a new network. In [ ]: Copied! # Answer EX3 # Specify 1D computational grid distance dx = [ 1000. , 1000. , 500. ] # Create an empty network network = Network () # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch in branches . iterrows (): xy = np . transpose ( branch . geometry . xy ) branch_new = Branch ( geometry = xy ) branch_new . generate_nodes ( mesh1d_edge_length = dx [ index ]) network . mesh1d_add_branch ( branch_new , name = branch . Name ) network . _mesh1d . _set_mesh1d () # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm . geometry . netfile . network = network fm . geometry . netfile . filepath = \"FlowFM_EX3_net.nc\" # Answer EX3 # Specify 1D computational grid distance dx = [1000., 1000., 500.] # Create an empty network network = Network() # Assign geometry of the branches and generate the computational grid on top of the branches. for index,branch in branches.iterrows(): xy = np.transpose(branch.geometry.xy) branch_new = Branch(geometry=xy) branch_new.generate_nodes(mesh1d_edge_length=dx[index]) network.mesh1d_add_branch(branch_new, name=branch.Name) network._mesh1d._set_mesh1d() # Assign the 1D network with 1D mesh to the D-Flow FM model and specify filepath fm.geometry.netfile.network = network fm.geometry.netfile.filepath = \"FlowFM_EX3_net.nc\" The 1D branches are plotted on a map in the figure below. Also, the computational grid points in the mesh1d definition are shown. In [ ]: Copied! # Create a figure with the flowlinks of the model figure , ( ax1 , ax2 ) = plt . subplots ( ncols = 2 ) img = plt . imread ( inputdir / \"osm_background.png\" ) mesh1d_meshkernel = network . _mesh1d . _get_mesh1d () ax1 . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) mesh1d_meshkernel . plot_edges ( ax = ax1 , color = 'red' ) # Add some annotation of branches: for index , branch in branches . iterrows (): middleIndex = int (( len ( branch [ 'geometry' ] . coords ) - 1 ) / 2 ) ax1 . text ( branch [ 'geometry' ] . xy [ 0 ][ middleIndex ], branch [ 'geometry' ] . xy [ 1 ][ middleIndex ], branch [ 'Name' ], ha = 'right' ) # Make a second plot with a zoom-in view of the computational grid points near the junction ax2 . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) ax2 . set_xlim ([ 500000 , 525000 ]) ax2 . set_ylim ([ 1125000 , 1150000 ]) mesh1d_meshkernel . plot_edges ( ax = ax2 , color = 'red' , marker = '.' , markeredgecolor = 'k' , markersize = 1 ) # Create a figure with the flowlinks of the model figure, (ax1, ax2) = plt.subplots(ncols=2) img = plt.imread(inputdir/\"osm_background.png\") mesh1d_meshkernel = network._mesh1d._get_mesh1d() ax1.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) mesh1d_meshkernel.plot_edges(ax=ax1, color='red') # Add some annotation of branches: for index,branch in branches.iterrows(): middleIndex = int((len(branch['geometry'].coords) - 1)/2) ax1.text(branch['geometry'].xy[0][middleIndex], branch['geometry'].xy[1][middleIndex], branch['Name'], ha='right') # Make a second plot with a zoom-in view of the computational grid points near the junction ax2.imshow(img, extent=[440000,531544.97964175534434617 ,1057000 ,1228644.01383191486820579 ]) ax2.set_xlim([500000, 525000]) ax2.set_ylim([1125000 ,1150000]) mesh1d_meshkernel.plot_edges(ax=ax2, color='red',marker='.',markeredgecolor='k',markersize=1)","title":"Create 1D computational grid"},{"location":"tutorials/Tutorial_1d2d_fluvial_flood_model_for_Magdalena_with_answers/#add-cross-sections","text":"In order to determine the flow area of the 1D model during the computation, you need cross-sections. These cross-sections consist of two components: Cross-section locations ( crosslocfile ): The crosslocfile contains the location of the cross-section on the branches. This is indicated with branchId chainage , where branchId is the name of the branch and chainage the distance to the upstream node. The figure below shows the cross-section locations in grey. In addition the cross-section location consist of the cross-section definition used at that location and a vertical shift of the profile. The latter is mainly used to create a good longitudinal slope over the 1D model (in case of shared cross-sections).

    Cross-section definitions ( crossdeffile ): The crossdeffile has the cross-section definitions in it. These definitions describe the shape of the profile. There are multiple types available: circle, rectangle, ZW- (tabulated), YZ- and XYZ-profiles. Depending on what type of watersystem you try to model you decide which cross-section to use. We recommend to use ZW- or YZ-profiles for rivers.

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In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: #111111; --jp-inverse-layout-color1: var(--md-grey-900); --jp-inverse-layout-color2: var(--md-grey-800); --jp-inverse-layout-color3: var(--md-grey-700); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-900); --jp-brand-color1: var(--md-blue-700); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-900); --jp-accent-color1: var(--md-green-700); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-900); --jp-warn-color1: var(--md-orange-700); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-900); --jp-error-color1: var(--md-red-700); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-900); --jp-success-color1: var(--md-green-700); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-900); --jp-info-color1: var(--md-cyan-700); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--md-grey-100); --jp-cell-editor-border-color: var(--md-grey-300); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 0.5; --jp-cell-prompt-not-active-font-color: var(--md-grey-700); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: var(--md-blue-50); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: #fdd; --jp-rendermime-table-row-background: var(--md-grey-100); --jp-rendermime-table-row-hover-background: var(--md-light-blue-50); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.25); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color1); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.24); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--md-grey-300); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color1); --jp-input-hover-background: var(--jp-layout-color1); --jp-input-background: var(--md-grey-100); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: #d9d9d9; --jp-editor-selected-focused-background: #d7d4f0; --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: #008000; --jp-mirror-editor-atom-color: #88f; --jp-mirror-editor-number-color: #080; --jp-mirror-editor-def-color: #00f; --jp-mirror-editor-variable-color: var(--md-grey-900); --jp-mirror-editor-variable-2-color: #05a; --jp-mirror-editor-variable-3-color: #085; --jp-mirror-editor-punctuation-color: #05a; --jp-mirror-editor-property-color: #05a; --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ba2121; --jp-mirror-editor-string-2-color: #708; --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: #008000; --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: #170; --jp-mirror-editor-attribute-color: #00c; --jp-mirror-editor-header-color: blue; --jp-mirror-editor-quote-color: #090; --jp-mirror-editor-link-color: #00c; --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: white; /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.5; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(245, 200, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } [data-md-color-scheme=\"slate\"] .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ /* The dark theme shadows need a bit of work, but this will probably also require work on the core layout * colors used in the theme as well. */ --jp-shadow-base-lightness: 32; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-700); --jp-border-color1: var(--md-grey-700); --jp-border-color2: var(--md-grey-800); --jp-border-color3: var(--md-grey-900); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(255, 255, 255, 1); --jp-ui-font-color1: rgba(255, 255, 255, 0.87); --jp-ui-font-color2: rgba(255, 255, 255, 0.54); --jp-ui-font-color3: rgba(255, 255, 255, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(0, 0, 0, 1); --jp-ui-inverse-font-color1: rgba(0, 0, 0, 0.8); --jp-ui-inverse-font-color2: rgba(0, 0, 0, 0.5); --jp-ui-inverse-font-color3: rgba(0, 0, 0, 0.3); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(255, 255, 255, 1); --jp-content-font-color1: rgba(255, 255, 255, 1); --jp-content-font-color2: rgba(255, 255, 255, 0.7); --jp-content-font-color3: rgba(255, 255, 255, 0.5); --jp-content-link-color: var(--md-blue-300); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: #111111; --jp-layout-color1: var(--md-grey-900); --jp-layout-color2: var(--md-grey-800); --jp-layout-color3: var(--md-grey-700); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: white; --jp-inverse-layout-color1: white; --jp-inverse-layout-color2: var(--md-grey-200); --jp-inverse-layout-color3: var(--md-grey-400); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-700); --jp-brand-color1: var(--md-blue-500); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-700); --jp-accent-color1: var(--md-green-500); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-700); --jp-warn-color1: var(--md-orange-500); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-700); --jp-error-color1: var(--md-red-500); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-700); --jp-success-color1: var(--md-green-500); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-700); --jp-info-color1: var(--md-cyan-500); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--jp-layout-color1); --jp-cell-editor-border-color: var(--md-grey-700); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 1; --jp-cell-prompt-not-active-font-color: var(--md-grey-300); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: rgba(33, 150, 243, 0.24); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: rgba(244, 67, 54, 0.28); --jp-rendermime-table-row-background: var(--md-grey-900); --jp-rendermime-table-row-hover-background: rgba(3, 169, 244, 0.2); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.6); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color2); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.8); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--jp-layout-color0); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color0); --jp-input-hover-background: var(--jp-layout-color2); --jp-input-background: var(--md-grey-800); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: var(--jp-layout-color2); --jp-editor-selected-focused-background: rgba(33, 150, 243, 0.24); --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: var(--md-green-500); --jp-mirror-editor-atom-color: var(--md-blue-300); --jp-mirror-editor-number-color: var(--md-green-400); --jp-mirror-editor-def-color: var(--md-blue-600); --jp-mirror-editor-variable-color: var(--md-grey-300); --jp-mirror-editor-variable-2-color: var(--md-blue-400); --jp-mirror-editor-variable-3-color: var(--md-green-600); --jp-mirror-editor-punctuation-color: var(--md-blue-400); --jp-mirror-editor-property-color: var(--md-blue-400); --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ff7070; --jp-mirror-editor-string-2-color: var(--md-purple-300); --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: var(--md-green-600); --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: var(--md-green-700); --jp-mirror-editor-attribute-color: var(--md-blue-700); --jp-mirror-editor-header-color: var(--md-blue-500); --jp-mirror-editor-quote-color: var(--md-green-300); --jp-mirror-editor-link-color: var(--md-blue-700); --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: var(--md-grey-400); /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.6; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(255, 225, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* scrollbar related styles. Supports every browser except Edge. */ /* colors based on JetBrain's Darcula theme */ --jp-scrollbar-background-color: #3f4244; --jp-scrollbar-thumb-color: 88, 96, 97; /* need to specify thumb color as an RGB triplet */ --jp-scrollbar-endpad: 3px; /* the minimum gap between the thumb and the ends of a scrollbar */ /* hacks for setting the thumb shape. These do nothing in Firefox */ --jp-scrollbar-thumb-margin: 3.5px; /* the space in between the sides of the thumb and the track */ --jp-scrollbar-thumb-radius: 9px; /* set to a large-ish value for rounded endcaps on the thumb */ /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } :root{--md-red-50: #ffebee;--md-red-100: #ffcdd2;--md-red-200: #ef9a9a;--md-red-300: #e57373;--md-red-400: #ef5350;--md-red-500: #f44336;--md-red-600: #e53935;--md-red-700: #d32f2f;--md-red-800: #c62828;--md-red-900: #b71c1c;--md-red-A100: #ff8a80;--md-red-A200: #ff5252;--md-red-A400: #ff1744;--md-red-A700: #d50000;--md-pink-50: #fce4ec;--md-pink-100: #f8bbd0;--md-pink-200: #f48fb1;--md-pink-300: #f06292;--md-pink-400: #ec407a;--md-pink-500: #e91e63;--md-pink-600: #d81b60;--md-pink-700: #c2185b;--md-pink-800: #ad1457;--md-pink-900: #880e4f;--md-pink-A100: #ff80ab;--md-pink-A200: #ff4081;--md-pink-A400: #f50057;--md-pink-A700: #c51162;--md-purple-50: #f3e5f5;--md-purple-100: #e1bee7;--md-purple-200: #ce93d8;--md-purple-300: #ba68c8;--md-purple-400: #ab47bc;--md-purple-500: #9c27b0;--md-purple-600: #8e24aa;--md-purple-700: #7b1fa2;--md-purple-800: #6a1b9a;--md-purple-900: #4a148c;--md-purple-A100: #ea80fc;--md-purple-A200: #e040fb;--md-purple-A400: #d500f9;--md-purple-A700: #aa00ff;--md-deep-purple-50: #ede7f6;--md-deep-purple-100: #d1c4e9;--md-deep-purple-200: #b39ddb;--md-deep-purple-300: #9575cd;--md-deep-purple-400: #7e57c2;--md-deep-purple-500: #673ab7;--md-deep-purple-600: #5e35b1;--md-deep-purple-700: #512da8;--md-deep-purple-800: #4527a0;--md-deep-purple-900: #311b92;--md-deep-purple-A100: #b388ff;--md-deep-purple-A200: #7c4dff;--md-deep-purple-A400: #651fff;--md-deep-purple-A700: #6200ea;--md-indigo-50: #e8eaf6;--md-indigo-100: #c5cae9;--md-indigo-200: #9fa8da;--md-indigo-300: 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sourceMappingURL=mkdocs-jupyter.css.map*/ init_mathjax = function() { if (window.MathJax) { // MathJax loaded MathJax.Hub.Config({ TeX: { equationNumbers: { autoNumber: \"AMS\", useLabelIds: true } }, tex2jax: { inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ], displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ], processEscapes: true, processEnvironments: true }, displayAlign: 'center', CommonHTML: { linebreaks: { automatic: true } } }); MathJax.Hub.Queue([\"Typeset\", MathJax.Hub]); } } init_mathjax(); Build a basic model \u00b6 This Build a basic model tutorial illustrates how to build a simple D-Flow FM model from scratch using HYDROLIB-core . Import HYDROLIB-core functionalities and setup D-Flow FM model \u00b6 The commands below import all needed packages and will prepare a model that will be saved in a subdir testmodel/ within the current working dir. In [ ]: Copied! from hydrolib.core.structure.models import FlowDirection , StructureModel , Weir from hydrolib.core.mdu.models import FMModel from pathlib import Path print ( \"Package import successful!\" ) from hydrolib.core.structure.models import FlowDirection, StructureModel, Weir from hydrolib.core.mdu.models import FMModel from pathlib import Path print(\"Package import successful!\") In [ ]: Copied! workdir = Path ( \"testmodel\" ) mdufile = \"test.mdu\" fm = FMModel () fm . filepath = workdir / mdufile workdir = Path(\"testmodel\") mdufile = \"test.mdu\" fm = FMModel() fm.filepath = workdir / mdufile Add a hydraulic structure; note that this is invalid because the model does not have a 1D network with branches and coordinates yet, but it will work for demo purposes and the network may be added later. In [ ]: Copied! # Add weir to the structure set/model and add this structure set to D-Flow FM model struc = Weir ( branchId = 'someBranch' , chainage = 123.0 , allowedflowdir = FlowDirection . none , crestlevel = 0.0 ) struc . comments . crestlevel = \"This is a comment\" fm . geometry . structurefile = [ StructureModel ( structure = [ struc ])] # Add weir to the structure set/model and add this structure set to D-Flow FM model struc = Weir(branchId='someBranch', chainage = 123.0, allowedflowdir=FlowDirection.none, crestlevel=0.0) struc.comments.crestlevel = \"This is a comment\" fm.geometry.structurefile = [StructureModel(structure=[struc])] Note that the creation of a Weir and other model objects requires several input arguments. A ValidationError will be raised when the model is invalid or incomplete. For instance, in the above example, if the StructureModel had been assigned directly to structurefile instead of as a list, that would have triggered a ValidationError . Setup a DIMR model \u00b6 Now let's add this model to an integrated model (DIMR config) and save it. In [ ]: Copied! from hydrolib.core.dimr.models import DIMR , FMComponent dimr = DIMR () dimr . component . append ( FMComponent ( name = \"test\" , workingDir = workdir , inputfile = mdufile , model = fm ) ) dimr_config = Path ( \"dimr_config.xml\" ) dimr . save ( filepath = dimr_config , recurse = True ) from hydrolib.core.dimr.models import DIMR, FMComponent dimr = DIMR() dimr.component.append( FMComponent(name=\"test\", workingDir=workdir, inputfile=mdufile, model=fm) ) dimr_config = Path(\"dimr_config.xml\") dimr.save(filepath=dimr_config, recurse=True) The model files on disk \u00b6 Now, let's see which model input files were saved: In [ ]: Copied! dimr . show_tree () dimr.show_tree() The save call on the highest-level DIMR object will result in recursive saves of all child models in the model hierarchy, so this results in four files ( dimr_config.xml , network.nc , structures.ini , test.mdu ) in the working directory. Some more in-depth background about recursive saving of a model tree is given in another tutorial: Loading and saving .","title":"Build a basic model"},{"location":"tutorials/build_basic_model/#build-a-basic-model","text":"This Build a basic model tutorial illustrates how to build a simple D-Flow FM model from scratch using HYDROLIB-core .","title":"Build a basic model"},{"location":"tutorials/build_basic_model/#import-hydrolib-core-functionalities-and-setup-d-flow-fm-model","text":"The commands below import all needed packages and will prepare a model that will be saved in a subdir testmodel/ within the current working dir. In [ ]: Copied! from hydrolib.core.structure.models import FlowDirection , StructureModel , Weir from hydrolib.core.mdu.models import FMModel from pathlib import Path print ( \"Package import successful!\" ) from hydrolib.core.structure.models import FlowDirection, StructureModel, Weir from hydrolib.core.mdu.models import FMModel from pathlib import Path print(\"Package import successful!\") In [ ]: Copied! workdir = Path ( \"testmodel\" ) mdufile = \"test.mdu\" fm = FMModel () fm . filepath = workdir / mdufile workdir = Path(\"testmodel\") mdufile = \"test.mdu\" fm = FMModel() fm.filepath = workdir / mdufile Add a hydraulic structure; note that this is invalid because the model does not have a 1D network with branches and coordinates yet, but it will work for demo purposes and the network may be added later. In [ ]: Copied! # Add weir to the structure set/model and add this structure set to D-Flow FM model struc = Weir ( branchId = 'someBranch' , chainage = 123.0 , allowedflowdir = FlowDirection . none , crestlevel = 0.0 ) struc . comments . crestlevel = \"This is a comment\" fm . geometry . structurefile = [ StructureModel ( structure = [ struc ])] # Add weir to the structure set/model and add this structure set to D-Flow FM model struc = Weir(branchId='someBranch', chainage = 123.0, allowedflowdir=FlowDirection.none, crestlevel=0.0) struc.comments.crestlevel = \"This is a comment\" fm.geometry.structurefile = [StructureModel(structure=[struc])] Note that the creation of a Weir and other model objects requires several input arguments. A ValidationError will be raised when the model is invalid or incomplete. For instance, in the above example, if the StructureModel had been assigned directly to structurefile instead of as a list, that would have triggered a ValidationError .","title":"Import HYDROLIB-core functionalities and setup D-Flow FM model"},{"location":"tutorials/build_basic_model/#setup-a-dimr-model","text":"Now let's add this model to an integrated model (DIMR config) and save it. In [ ]: Copied! from hydrolib.core.dimr.models import DIMR , FMComponent dimr = DIMR () dimr . component . append ( FMComponent ( name = \"test\" , workingDir = workdir , inputfile = mdufile , model = fm ) ) dimr_config = Path ( \"dimr_config.xml\" ) dimr . save ( filepath = dimr_config , recurse = True ) from hydrolib.core.dimr.models import DIMR, FMComponent dimr = DIMR() dimr.component.append( FMComponent(name=\"test\", workingDir=workdir, inputfile=mdufile, model=fm) ) dimr_config = Path(\"dimr_config.xml\") dimr.save(filepath=dimr_config, recurse=True)","title":"Setup a DIMR model"},{"location":"tutorials/build_basic_model/#the-model-files-on-disk","text":"Now, let's see which model input files were saved: In [ ]: Copied! dimr . show_tree () dimr.show_tree() The save call on the highest-level DIMR object will result in recursive saves of all child models in the model hierarchy, so this results in four files ( dimr_config.xml , network.nc , structures.ini , test.mdu ) in the working directory. Some more in-depth background about recursive saving of a model tree is given in another tutorial: Loading and saving .","title":"The model files on disk"},{"location":"tutorials/dataframe_handling/","text":"Dataframe handling \u00b6 We can use DataFrame s from pandas together with hydrolib-core. Note that this functionality can only work on files that are in essence tables and are represented by a List of objects in hydrolib-core. Examples of such ParsableFileModel s with their List fields are: - ForcingModel.forcing - CrossDefModel.definition - CrossLocModel.crosssection - ExtModel.boundary - ExtModel.lateral Say we load in a .bc file and want the resulting forcing in a dataframe. from hydrolib.core.dflowfm.bc.models import ForcingModel filepath = ( \"tests/data/input/e02/f101_1D-boundaries/c01_steady-state-flow/BoundaryConditions.bc\" ) m = ForcingModel ( filepath ) m . forcing [ Constant ( comments = None , datablock = [[ 2.5 ]], name = 'T1_Dwn_Bnd' , function = 'constant' , quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], offset = 0.0 , factor = 1.0 ), Constant ( comments = None , datablock = [[ 100.0 ]], name = 'T1_Up_Bnd' , function = 'constant' , quantityunitpair = [ QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], offset = 0.0 , factor = 1.0 ), Constant ( comments = None , datablock = [[ 2.5 ]], name = 'T2_Dwn_Bnd' , function = 'constant' , quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ 0.0 , 0.0 ], [ 1800.0 , 100.0 ], [ 4320.0 , 100.0 ]], name = 'T2_Up_Bnd' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ 0.0 , 0.0 ], [ 1800.0 , 2.5 ], [ 4320.0 , 2.5 ]], name = 'T3_Dwn_Bnd' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), Constant ( comments = None , datablock = [[ 100.0 ]], name = 'T3_Up_Bnd' , function = 'constant' , quantityunitpair = [ QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ 0.0 , 0.0 ], [ 1800.0 , 100.0 ], [ 4320.0 , 100.0 ]], name = 'T4_Up_Bnd' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), QHTable ( comments = None , datablock = [[ 50.0 , 1.25 ], [ 100.0 , 2.5 ], [ 150.0 , 3.75 ]], name = 'T4_Dwn_Bnd' , function = 'qhtable' , quantityunitpair = [ QuantityUnitPair ( quantity = 'qhbnd discharge' , unit = 'm\u00b3/s' ), QuantityUnitPair ( quantity = 'qhbnd waterlevel' , unit = 'm' )]), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'wind_speed' , unit = 'm/s' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'wind_from_direction' , unit = 'degree' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'air_temperature' , unit = 'degrees C' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'humidity' , unit = 'percentage' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'cloudiness' , unit = 'percentage' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 )] We now have a list of forcings that we can convert into a DataFrame. import pandas as pd df = pd . DataFrame ([ f . __dict__ for f in m . forcing ]) comments datablock name function ... offset factor _header timeinterpolation 0 None [[ 2.5 ]] T1_Dwn_Bnd constant ... 0.0 1.0 forcing linear 1 None [[ 100.0 ]] T1_Up_Bnd constant ... 0.0 1.0 forcing linear 2 None [[ 2.5 ]] T2_Dwn_Bnd constant ... 0.0 1.0 forcing linear 3 None [[ 0.0 , 0.0 ], [ 1800.0 , 100.0 ], [ 4320.0 , 100.0 ]] T2_Up_Bnd timeseries ... 0.0 1.0 forcing linear 4 None [[ 0.0 , 0.0 ], [ 1800.0 , 2.5 ], [ 4320.0 , 2.5 ]] T3_Dwn_Bnd timeseries ... 0.0 1.0 forcing linear 5 None [[ 100.0 ]] T3_Up_Bnd constant ... 0.0 1.0 forcing linear 6 None [[ 0.0 , 0.0 ], [ 1800.0 , 100.0 ], [ 4320.0 , 100.0 ]] T4_Up_Bnd timeseries ... 0.0 1.0 forcing linear 7 None [[ 50.0 , 1.25 ], [ 100.0 , 2.5 ], [ 150.0 , 3.75 ]] T4_Dwn_Bnd qhtable ... NaN NaN forcing NaN 8 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear 9 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear 10 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear 11 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear 12 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear [ 13 rows x 10 columns ] Note that because there are several types of forcings, with different fields, some values have become NaN. We can also convert this DataFrame back to a ForcingModel . fm = ForcingModel ( forcing = df . to_dict ( 'records' )) fm . forcing == m . forcing True","title":"Dataframe handling"},{"location":"tutorials/dataframe_handling/#dataframe-handling","text":"We can use DataFrame s from pandas together with hydrolib-core. Note that this functionality can only work on files that are in essence tables and are represented by a List of objects in hydrolib-core. Examples of such ParsableFileModel s with their List fields are: - ForcingModel.forcing - CrossDefModel.definition - CrossLocModel.crosssection - ExtModel.boundary - ExtModel.lateral Say we load in a .bc file and want the resulting forcing in a dataframe. from hydrolib.core.dflowfm.bc.models import ForcingModel filepath = ( \"tests/data/input/e02/f101_1D-boundaries/c01_steady-state-flow/BoundaryConditions.bc\" ) m = ForcingModel ( filepath ) m . forcing [ Constant ( comments = None , datablock = [[ 2.5 ]], name = 'T1_Dwn_Bnd' , function = 'constant' , quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], offset = 0.0 , factor = 1.0 ), Constant ( comments = None , datablock = [[ 100.0 ]], name = 'T1_Up_Bnd' , function = 'constant' , quantityunitpair = [ QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], offset = 0.0 , factor = 1.0 ), Constant ( comments = None , datablock = [[ 2.5 ]], name = 'T2_Dwn_Bnd' , function = 'constant' , quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ 0.0 , 0.0 ], [ 1800.0 , 100.0 ], [ 4320.0 , 100.0 ]], name = 'T2_Up_Bnd' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ 0.0 , 0.0 ], [ 1800.0 , 2.5 ], [ 4320.0 , 2.5 ]], name = 'T3_Dwn_Bnd' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), Constant ( comments = None , datablock = [[ 100.0 ]], name = 'T3_Up_Bnd' , function = 'constant' , quantityunitpair = [ QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ 0.0 , 0.0 ], [ 1800.0 , 100.0 ], [ 4320.0 , 100.0 ]], name = 'T4_Up_Bnd' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), QHTable ( comments = None , datablock = [[ 50.0 , 1.25 ], [ 100.0 , 2.5 ], [ 150.0 , 3.75 ]], name = 'T4_Dwn_Bnd' , function = 'qhtable' , quantityunitpair = [ QuantityUnitPair ( quantity = 'qhbnd discharge' , unit = 'm\u00b3/s' ), QuantityUnitPair ( quantity = 'qhbnd waterlevel' , unit = 'm' )]), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'wind_speed' , unit = 'm/s' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'wind_from_direction' , unit = 'degree' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'air_temperature' , unit = 'degrees C' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'humidity' , unit = 'percentage' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 ), TimeSeries ( comments = None , datablock = [[ - 2629440.0 , 0.0 ]], name = 'model_wide' , function = 'timeseries' , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2015-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'cloudiness' , unit = 'percentage' )], timeinterpolation = 'linear' , offset = 0.0 , factor = 1.0 )] We now have a list of forcings that we can convert into a DataFrame. import pandas as pd df = pd . DataFrame ([ f . __dict__ for f in m . forcing ]) comments datablock name function ... offset factor _header timeinterpolation 0 None [[ 2.5 ]] T1_Dwn_Bnd constant ... 0.0 1.0 forcing linear 1 None [[ 100.0 ]] T1_Up_Bnd constant ... 0.0 1.0 forcing linear 2 None [[ 2.5 ]] T2_Dwn_Bnd constant ... 0.0 1.0 forcing linear 3 None [[ 0.0 , 0.0 ], [ 1800.0 , 100.0 ], [ 4320.0 , 100.0 ]] T2_Up_Bnd timeseries ... 0.0 1.0 forcing linear 4 None [[ 0.0 , 0.0 ], [ 1800.0 , 2.5 ], [ 4320.0 , 2.5 ]] T3_Dwn_Bnd timeseries ... 0.0 1.0 forcing linear 5 None [[ 100.0 ]] T3_Up_Bnd constant ... 0.0 1.0 forcing linear 6 None [[ 0.0 , 0.0 ], [ 1800.0 , 100.0 ], [ 4320.0 , 100.0 ]] T4_Up_Bnd timeseries ... 0.0 1.0 forcing linear 7 None [[ 50.0 , 1.25 ], [ 100.0 , 2.5 ], [ 150.0 , 3.75 ]] T4_Dwn_Bnd qhtable ... NaN NaN forcing NaN 8 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear 9 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear 10 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear 11 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear 12 None [[ - 2629440.0 , 0.0 ]] model_wide timeseries ... 0.0 1.0 forcing linear [ 13 rows x 10 columns ] Note that because there are several types of forcings, with different fields, some values have become NaN. We can also convert this DataFrame back to a ForcingModel . fm = ForcingModel ( forcing = df . to_dict ( 'records' )) fm . forcing == m . forcing True","title":"Dataframe handling"},{"location":"tutorials/loading_and_saving_a_model/","text":"Loading and saving a model \u00b6 In this article we will look at loading and saving a model. First we will load a model, and store it in a new location. Then make adjustments to one of the sub models, and store the model in place. Lastly, we will look at some caveats of saving and loading models. If you do not have a DIMR model, you can use the example model in the test data . Load the model \u00b6 We can load a model by constructing a new DIMR model by calling the DIMR with the file path to this model: # assuming the DIMR model is stored in your current working directory. model_path = Path ( \"./dimr_config.xml\" ) dimr_model = DIMR ( filepath = model_path ) It is also possible to not recursively load models: dimr_model = DIMR ( filepath = model_path , recurse = False ) This will only load a DIMR model without its underlying child file models, such as the Flow FM model. Save the model in a new location \u00b6 If we want to store the full model in a different location we can use the save function: # Adjust this new_path to a path convenient for you. new_path = Path ( \"some/other/path/dimr_config.xml\" ) dimr_model . save ( filepath = new_path , recurse = True ) By setting recurse to True we will ensure all files (which are supported by HYDROLIB-core) are written to the new location, relative to the file path of the root model. Providing the filepath argument has the same result as first setting the filepath, and then calling save: new_path = Path ( \"some/other/path/dimr_config.xml\" ) dimr_model . filepath = new_path dimr_model . save ( recurse = True ) As such, when calling filepath after save it should be the same as new_path . Once save has been called all files (supported by HYDROLIB-core) should be located in the parent folder. Adjust the model in a update it on disk \u00b6 Now that we have written our model in a different location, we can make some adjustments to it. We can retrieve the FM sub model as follows: fm_component = dimr_model . component [ 1 ] # Index 0 corresponds with the RRComponent. fm_model = fm_component . model We can adjust the model, by for example changing some of the properties. For example let's change the MapInterval from 60 to 30: fm_model . output . mapinterval = 30.0 With that change made we can go ahead and save just this specific sub model, in order to update the values on disk: fm_model . save () By default, if no filepath is selected, it will be stored in the current save_location . This should correspond with the place where it was last stored on disk. Furthermore, by default recurse is set to False , as such we will only rewrite the .mdu file. If we now inspect the .mdu file, we should see that the MapInterval in the output header has been set to 30: ... [output] ... MapInterval = 30.0 ... Loading models on case-sensitive systems \u00b6 Model files may contain references to other model files of which the casing does not match with the file on disk. On Windows, loading a model with differently cased references will work just fine, since Windows is case-insensitive. However on Linux, the referenced file cannot be found and will raise an error. To aid users in migrating their models, HYDROLIB-core offers a feature to resolve the casing of referenced files and supports three operating systems: Windows, Linux and MacOS. Consider an MDU model file that references a network file: Network/flowfm_net.nc . The file on disk is actually called network/FlowFM_net.nc . To load the model and simultaneously repair the file references in the in-memory model: from hydrolib.core.dflowfm.mdu.models import FMModel model = FMModel ( \"FlowFM.mdu\" , resolve_casing = True ) # assert that file reference has been updated from Network/flowfm_net.nc to network/FlowFM_net.nc assert model . geometry . netfile . filepath == Path ( \"network/FlowFM_net.nc\" ) The resolve_casing argument is by default False . Using the resolve_casing functionality might heavily influence the performance of model loading depending on the model size, the file tree structure and the operating system. Saving and loading models between different operating systems \u00b6 In certain cases, it may be necessary to switch effortlessly between operating systems (OS) using the same model. This allows the model to be loaded seamlessly on both Unix and Windows systems. However, it is important to note that the file paths look different for both OSs. Absolute file paths on Unix have a leading slash, while on Windows systems they start with a drive letter. Additionally, Unix systems don't allow backward slashes, whereas Windows supports both forward and backward slashes in file paths. These unique differences may cause issues when attempting to interpret files references within the model on another OS. Fortunately, HYDROLIB-core features a functionality that allows the conversion of file paths from one OS path style to another. This resolves the issue and ensures that the model functions seamlessly on both Unix and Windows systems. Examples \u00b6 Loading a model with Unix file paths on Windows: model = FMModel ( filepath = Path ( \"p:/model/FlowFM.mdu\" ), path_style = \"unix\" ) Loading a model with Windows file paths on Linux/MacOS: model = FMModel ( filepath = Path ( \"/p/model/FlowFM.mdu\" ), path_style = \"windows\" ) In the two examples mentioned above, the path_style option specifies the path style that is used in the model files to be loaded. This information allows HYDROLIB-core to accurately convert the file paths to match the path style of the running operating system and interpret them correctly. Saving a model with Unix file paths on Windows: model . save ( filepath = Path ( \"p:/model/FlowFM.mdu\" ), recurse = True , path_style = \"unix\" ) Saving a model with Windows file paths on Linux/MacOS: model . save ( filepath = Path ( \"/p/model/FlowFM.mdu\" ), recurse = True , path_style = \"windows\" ) In the two examples mentioned above, the path_style option specifies the preferred path style of the saved model files. However, if this option is not specified when initializing or saving the model, it will default to the path style of the current operating system. The path_style option supports these three values: * None (will default to either \"windows\" or \"unix\" depending on the running OS) * \"windows\" * \"unix\" Other values are not supported and an error will be raised. Caveats when saving models \u00b6 There are some caveats to take into account when saving models. Filepath changes do not automatically propagate \u00b6 When changing the filepath property of a parent model, the changes in save_location will not automatically propagate. As such, when saving a child model with a relative path, if the parent model's filepath has been changed, the child model will still be saved at its original save location. In order to update the save location, synchronize_filepaths should be called on the root model. Synchronizing filepaths is relative to the model it is called upon \u00b6 synchronize_filepaths will only update the file paths of child models. As such it will not propagate changes mode in a parent model: dimr_model.filepath = Path(\"some/other/path/dimr_config.xml\") fm_model.synchronize_filepaths() # This has no effect. Because the save_location of the fm_model has not been changed, none of the child models will change either. Furthermore, extra care needs to be taken when dealing with FM models with the pathsRelativeToParent set to False . This option will make all relative paths of child models relative to the .mdu . If synchronize_filepaths is called on a child model of the fm model, it will instead make all save_locations relative to this child model, which is incorrect. It is recommended to not use pathsRelativeToParent set to False .","title":"Loading and saving a model"},{"location":"tutorials/loading_and_saving_a_model/#loading-and-saving-a-model","text":"In this article we will look at loading and saving a model. First we will load a model, and store it in a new location. Then make adjustments to one of the sub models, and store the model in place. Lastly, we will look at some caveats of saving and loading models. If you do not have a DIMR model, you can use the example model in the test data .","title":"Loading and saving a model"},{"location":"tutorials/loading_and_saving_a_model/#load-the-model","text":"We can load a model by constructing a new DIMR model by calling the DIMR with the file path to this model: # assuming the DIMR model is stored in your current working directory. model_path = Path ( \"./dimr_config.xml\" ) dimr_model = DIMR ( filepath = model_path ) It is also possible to not recursively load models: dimr_model = DIMR ( filepath = model_path , recurse = False ) This will only load a DIMR model without its underlying child file models, such as the Flow FM model.","title":"Load the model"},{"location":"tutorials/loading_and_saving_a_model/#save-the-model-in-a-new-location","text":"If we want to store the full model in a different location we can use the save function: # Adjust this new_path to a path convenient for you. new_path = Path ( \"some/other/path/dimr_config.xml\" ) dimr_model . save ( filepath = new_path , recurse = True ) By setting recurse to True we will ensure all files (which are supported by HYDROLIB-core) are written to the new location, relative to the file path of the root model. Providing the filepath argument has the same result as first setting the filepath, and then calling save: new_path = Path ( \"some/other/path/dimr_config.xml\" ) dimr_model . filepath = new_path dimr_model . save ( recurse = True ) As such, when calling filepath after save it should be the same as new_path . Once save has been called all files (supported by HYDROLIB-core) should be located in the parent folder.","title":"Save the model in a new location"},{"location":"tutorials/loading_and_saving_a_model/#adjust-the-model-in-a-update-it-on-disk","text":"Now that we have written our model in a different location, we can make some adjustments to it. We can retrieve the FM sub model as follows: fm_component = dimr_model . component [ 1 ] # Index 0 corresponds with the RRComponent. fm_model = fm_component . model We can adjust the model, by for example changing some of the properties. For example let's change the MapInterval from 60 to 30: fm_model . output . mapinterval = 30.0 With that change made we can go ahead and save just this specific sub model, in order to update the values on disk: fm_model . save () By default, if no filepath is selected, it will be stored in the current save_location . This should correspond with the place where it was last stored on disk. Furthermore, by default recurse is set to False , as such we will only rewrite the .mdu file. If we now inspect the .mdu file, we should see that the MapInterval in the output header has been set to 30: ... [output] ... MapInterval = 30.0 ...","title":"Adjust the model in a update it on disk"},{"location":"tutorials/loading_and_saving_a_model/#loading-models-on-case-sensitive-systems","text":"Model files may contain references to other model files of which the casing does not match with the file on disk. On Windows, loading a model with differently cased references will work just fine, since Windows is case-insensitive. However on Linux, the referenced file cannot be found and will raise an error. To aid users in migrating their models, HYDROLIB-core offers a feature to resolve the casing of referenced files and supports three operating systems: Windows, Linux and MacOS. Consider an MDU model file that references a network file: Network/flowfm_net.nc . The file on disk is actually called network/FlowFM_net.nc . To load the model and simultaneously repair the file references in the in-memory model: from hydrolib.core.dflowfm.mdu.models import FMModel model = FMModel ( \"FlowFM.mdu\" , resolve_casing = True ) # assert that file reference has been updated from Network/flowfm_net.nc to network/FlowFM_net.nc assert model . geometry . netfile . filepath == Path ( \"network/FlowFM_net.nc\" ) The resolve_casing argument is by default False . Using the resolve_casing functionality might heavily influence the performance of model loading depending on the model size, the file tree structure and the operating system.","title":"Loading models on case-sensitive systems"},{"location":"tutorials/loading_and_saving_a_model/#saving-and-loading-models-between-different-operating-systems","text":"In certain cases, it may be necessary to switch effortlessly between operating systems (OS) using the same model. This allows the model to be loaded seamlessly on both Unix and Windows systems. However, it is important to note that the file paths look different for both OSs. Absolute file paths on Unix have a leading slash, while on Windows systems they start with a drive letter. Additionally, Unix systems don't allow backward slashes, whereas Windows supports both forward and backward slashes in file paths. These unique differences may cause issues when attempting to interpret files references within the model on another OS. Fortunately, HYDROLIB-core features a functionality that allows the conversion of file paths from one OS path style to another. This resolves the issue and ensures that the model functions seamlessly on both Unix and Windows systems.","title":"Saving and loading models between different operating systems"},{"location":"tutorials/loading_and_saving_a_model/#examples","text":"Loading a model with Unix file paths on Windows: model = FMModel ( filepath = Path ( \"p:/model/FlowFM.mdu\" ), path_style = \"unix\" ) Loading a model with Windows file paths on Linux/MacOS: model = FMModel ( filepath = Path ( \"/p/model/FlowFM.mdu\" ), path_style = \"windows\" ) In the two examples mentioned above, the path_style option specifies the path style that is used in the model files to be loaded. This information allows HYDROLIB-core to accurately convert the file paths to match the path style of the running operating system and interpret them correctly. Saving a model with Unix file paths on Windows: model . save ( filepath = Path ( \"p:/model/FlowFM.mdu\" ), recurse = True , path_style = \"unix\" ) Saving a model with Windows file paths on Linux/MacOS: model . save ( filepath = Path ( \"/p/model/FlowFM.mdu\" ), recurse = True , path_style = \"windows\" ) In the two examples mentioned above, the path_style option specifies the preferred path style of the saved model files. However, if this option is not specified when initializing or saving the model, it will default to the path style of the current operating system. The path_style option supports these three values: * None (will default to either \"windows\" or \"unix\" depending on the running OS) * \"windows\" * \"unix\" Other values are not supported and an error will be raised.","title":"Examples"},{"location":"tutorials/loading_and_saving_a_model/#caveats-when-saving-models","text":"There are some caveats to take into account when saving models.","title":"Caveats when saving models"},{"location":"tutorials/loading_and_saving_a_model/#filepath-changes-do-not-automatically-propagate","text":"When changing the filepath property of a parent model, the changes in save_location will not automatically propagate. As such, when saving a child model with a relative path, if the parent model's filepath has been changed, the child model will still be saved at its original save location. In order to update the save location, synchronize_filepaths should be called on the root model.","title":"Filepath changes do not automatically propagate"},{"location":"tutorials/loading_and_saving_a_model/#synchronizing-filepaths-is-relative-to-the-model-it-is-called-upon","text":"synchronize_filepaths will only update the file paths of child models. As such it will not propagate changes mode in a parent model: dimr_model.filepath = Path(\"some/other/path/dimr_config.xml\") fm_model.synchronize_filepaths() # This has no effect. Because the save_location of the fm_model has not been changed, none of the child models will change either. Furthermore, extra care needs to be taken when dealing with FM models with the pathsRelativeToParent set to False . This option will make all relative paths of child models relative to the .mdu . If synchronize_filepaths is called on a child model of the fm model, it will instead make all save_locations relative to this child model, which is incorrect. It is recommended to not use pathsRelativeToParent set to False .","title":"Synchronizing filepaths is relative to the model it is called upon"},{"location":"tutorials/plotting_a_network/","text":"Plotting a network \u00b6 We can visualise a Network with the following code: from hydrolib.core.dflowfm.net.models import Network import matplotlib from matplotlib.collections import LineCollection import numpy as np def plot ( network : Network , ax : matplotlib . axes . _subplots . AxesSubplot , mesh1d_kwargs : dict = None , mesh2d_kwargs : dict = None , links1d2d_kwargs : dict = None , ) -> None : if mesh1d_kwargs is None : mesh1d_kwargs = { \"color\" : \"C3\" , \"lw\" : 1.0 } if mesh2d_kwargs is None : mesh2d_kwargs = { \"color\" : \"C0\" , \"lw\" : 0.5 } if links1d2d_kwargs is None : links1d2d_kwargs = { \"color\" : \"k\" , \"lw\" : 1.0 } # Mesh 1d if not network . _mesh1d . is_empty (): nodes1d = np . stack ( [ network . _mesh1d . mesh1d_node_x , network . _mesh1d . mesh1d_node_y ], axis = 1 ) edge_nodes = network . _mesh1d . mesh1d_edge_nodes lc_mesh1d = LineCollection ( nodes1d [ edge_nodes ], ** mesh1d_kwargs ) ax . add_collection ( lc_mesh1d ) # Mesh 2d if not network . _mesh2d . is_empty (): nodes2d = np . stack ( [ network . _mesh2d . mesh2d_node_x , network . _mesh2d . mesh2d_node_y ], axis = 1 ) edge_nodes = network . _mesh2d . mesh2d_edge_nodes lc_mesh2d = LineCollection ( nodes2d [ edge_nodes ], ** mesh2d_kwargs ) ax . add_collection ( lc_mesh2d ) # Links if not network . _link1d2d . is_empty (): faces2d = np . stack ( [ network . _mesh2d . mesh2d_face_x , network . _mesh2d . mesh2d_face_y ], axis = 1 ) link_coords = np . stack ( [ nodes1d [ network . _link1d2d . link1d2d [:, 0 ]], faces2d [ network . _link1d2d . link1d2d [:, 1 ]], ], axis = 1 , ) lc_link1d2d = LineCollection ( link_coords , ** links1d2d_kwargs ) ax . add_collection ( lc_link1d2d )","title":"Plotting a network"},{"location":"tutorials/plotting_a_network/#plotting-a-network","text":"We can visualise a Network with the following code: from hydrolib.core.dflowfm.net.models import Network import matplotlib from matplotlib.collections import LineCollection import numpy as np def plot ( network : Network , ax : matplotlib . axes . _subplots . AxesSubplot , mesh1d_kwargs : dict = None , mesh2d_kwargs : dict = None , links1d2d_kwargs : dict = None , ) -> None : if mesh1d_kwargs is None : mesh1d_kwargs = { \"color\" : \"C3\" , \"lw\" : 1.0 } if mesh2d_kwargs is None : mesh2d_kwargs = { \"color\" : \"C0\" , \"lw\" : 0.5 } if links1d2d_kwargs is None : links1d2d_kwargs = { \"color\" : \"k\" , \"lw\" : 1.0 } # Mesh 1d if not network . _mesh1d . is_empty (): nodes1d = np . stack ( [ network . _mesh1d . mesh1d_node_x , network . _mesh1d . mesh1d_node_y ], axis = 1 ) edge_nodes = network . _mesh1d . mesh1d_edge_nodes lc_mesh1d = LineCollection ( nodes1d [ edge_nodes ], ** mesh1d_kwargs ) ax . add_collection ( lc_mesh1d ) # Mesh 2d if not network . _mesh2d . is_empty (): nodes2d = np . stack ( [ network . _mesh2d . mesh2d_node_x , network . _mesh2d . mesh2d_node_y ], axis = 1 ) edge_nodes = network . _mesh2d . mesh2d_edge_nodes lc_mesh2d = LineCollection ( nodes2d [ edge_nodes ], ** mesh2d_kwargs ) ax . add_collection ( lc_mesh2d ) # Links if not network . _link1d2d . is_empty (): faces2d = np . stack ( [ network . _mesh2d . mesh2d_face_x , network . _mesh2d . mesh2d_face_y ], axis = 1 ) link_coords = np . stack ( [ nodes1d [ network . _link1d2d . link1d2d [:, 0 ]], faces2d [ network . _link1d2d . link1d2d [:, 1 ]], ], axis = 1 , ) lc_link1d2d = LineCollection ( link_coords , ** links1d2d_kwargs ) ax . add_collection ( lc_link1d2d )","title":"Plotting a network"},{"location":"tutorials/tutorials/","text":"Introduction to tutorials \u00b6 The tutorials below can help you becoming familiar with the basics as well as the more advanced use of HYDROLIB-core: Tutorial: Build a basic model - iPython notebook Tutorial: Loading and saving a model Tutorial: Dataframe handling Tutorial: Plotting a network To run these examples on your local machine you need a copy of the repository and an installation of HYDROLIB-core including some additional packages. The installation of HYDROLIB-core is explained in Installation . The tutorials are then located in docs/tutorials/ .","title":"Introduction to tutorials"},{"location":"tutorials/tutorials/#introduction-to-tutorials","text":"The tutorials below can help you becoming familiar with the basics as well as the more advanced use of HYDROLIB-core: Tutorial: Build a basic model - iPython notebook Tutorial: Loading and saving a model Tutorial: Dataframe handling Tutorial: Plotting a network To run these examples on your local machine you need a copy of the repository and an installation of HYDROLIB-core including some additional packages. The installation of HYDROLIB-core is explained in Installation . 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When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(0, 0, 0, 1); --jp-content-font-color1: rgba(0, 0, 0, 0.87); --jp-content-font-color2: rgba(0, 0, 0, 0.54); --jp-content-font-color3: rgba(0, 0, 0, 0.38); --jp-content-link-color: var(--md-blue-700); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: white; --jp-layout-color1: white; --jp-layout-color2: var(--md-grey-200); --jp-layout-color3: var(--md-grey-400); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: #111111; --jp-inverse-layout-color1: var(--md-grey-900); --jp-inverse-layout-color2: var(--md-grey-800); --jp-inverse-layout-color3: var(--md-grey-700); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-900); --jp-brand-color1: var(--md-blue-700); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-900); --jp-accent-color1: var(--md-green-700); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-900); --jp-warn-color1: var(--md-orange-700); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-900); --jp-error-color1: var(--md-red-700); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-900); --jp-success-color1: var(--md-green-700); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-900); --jp-info-color1: var(--md-cyan-700); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--md-grey-100); --jp-cell-editor-border-color: var(--md-grey-300); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 0.5; --jp-cell-prompt-not-active-font-color: var(--md-grey-700); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: var(--md-blue-50); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: #fdd; --jp-rendermime-table-row-background: var(--md-grey-100); --jp-rendermime-table-row-hover-background: var(--md-light-blue-50); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.25); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color1); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.24); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--md-grey-300); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color1); --jp-input-hover-background: var(--jp-layout-color1); --jp-input-background: var(--md-grey-100); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: #d9d9d9; --jp-editor-selected-focused-background: #d7d4f0; --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: #008000; --jp-mirror-editor-atom-color: #88f; --jp-mirror-editor-number-color: #080; --jp-mirror-editor-def-color: #00f; --jp-mirror-editor-variable-color: var(--md-grey-900); --jp-mirror-editor-variable-2-color: #05a; --jp-mirror-editor-variable-3-color: #085; --jp-mirror-editor-punctuation-color: #05a; --jp-mirror-editor-property-color: #05a; --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ba2121; --jp-mirror-editor-string-2-color: #708; --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: #008000; --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: #170; --jp-mirror-editor-attribute-color: #00c; --jp-mirror-editor-header-color: blue; --jp-mirror-editor-quote-color: #090; --jp-mirror-editor-link-color: #00c; --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: white; /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.5; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(245, 200, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } [data-md-color-scheme=\"slate\"] .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ /* The dark theme shadows need a bit of work, but this will probably also require work on the core layout * colors used in the theme as well. */ --jp-shadow-base-lightness: 32; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-700); --jp-border-color1: var(--md-grey-700); --jp-border-color2: var(--md-grey-800); --jp-border-color3: var(--md-grey-900); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(255, 255, 255, 1); --jp-ui-font-color1: rgba(255, 255, 255, 0.87); --jp-ui-font-color2: rgba(255, 255, 255, 0.54); --jp-ui-font-color3: rgba(255, 255, 255, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(0, 0, 0, 1); --jp-ui-inverse-font-color1: rgba(0, 0, 0, 0.8); --jp-ui-inverse-font-color2: rgba(0, 0, 0, 0.5); --jp-ui-inverse-font-color3: rgba(0, 0, 0, 0.3); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(255, 255, 255, 1); --jp-content-font-color1: rgba(255, 255, 255, 1); --jp-content-font-color2: rgba(255, 255, 255, 0.7); --jp-content-font-color3: rgba(255, 255, 255, 0.5); --jp-content-link-color: var(--md-blue-300); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: #111111; --jp-layout-color1: var(--md-grey-900); --jp-layout-color2: var(--md-grey-800); --jp-layout-color3: var(--md-grey-700); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: white; --jp-inverse-layout-color1: white; --jp-inverse-layout-color2: var(--md-grey-200); --jp-inverse-layout-color3: var(--md-grey-400); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-700); --jp-brand-color1: var(--md-blue-500); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-700); --jp-accent-color1: var(--md-green-500); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-700); --jp-warn-color1: var(--md-orange-500); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-700); --jp-error-color1: var(--md-red-500); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-700); --jp-success-color1: var(--md-green-500); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-700); --jp-info-color1: var(--md-cyan-500); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--jp-layout-color1); --jp-cell-editor-border-color: var(--md-grey-700); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 1; --jp-cell-prompt-not-active-font-color: var(--md-grey-300); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: rgba(33, 150, 243, 0.24); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: rgba(244, 67, 54, 0.28); --jp-rendermime-table-row-background: var(--md-grey-900); --jp-rendermime-table-row-hover-background: rgba(3, 169, 244, 0.2); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.6); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color2); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.8); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--jp-layout-color0); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color0); --jp-input-hover-background: var(--jp-layout-color2); --jp-input-background: var(--md-grey-800); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: var(--jp-layout-color2); --jp-editor-selected-focused-background: rgba(33, 150, 243, 0.24); --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: var(--md-green-500); --jp-mirror-editor-atom-color: var(--md-blue-300); --jp-mirror-editor-number-color: var(--md-green-400); --jp-mirror-editor-def-color: var(--md-blue-600); --jp-mirror-editor-variable-color: var(--md-grey-300); --jp-mirror-editor-variable-2-color: var(--md-blue-400); --jp-mirror-editor-variable-3-color: var(--md-green-600); --jp-mirror-editor-punctuation-color: var(--md-blue-400); --jp-mirror-editor-property-color: var(--md-blue-400); --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ff7070; --jp-mirror-editor-string-2-color: var(--md-purple-300); --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: var(--md-green-600); --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: var(--md-green-700); --jp-mirror-editor-attribute-color: var(--md-blue-700); --jp-mirror-editor-header-color: var(--md-blue-500); --jp-mirror-editor-quote-color: var(--md-green-300); --jp-mirror-editor-link-color: var(--md-blue-700); --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: var(--md-grey-400); /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.6; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(255, 225, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* scrollbar related styles. Supports every browser except Edge. */ /* colors based on JetBrain's Darcula theme */ --jp-scrollbar-background-color: #3f4244; --jp-scrollbar-thumb-color: 88, 96, 97; /* need to specify thumb color as an RGB triplet */ --jp-scrollbar-endpad: 3px; /* the minimum gap between the thumb and the ends of a scrollbar */ /* hacks for setting the thumb shape. 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sourceMappingURL=mkdocs-jupyter.css.map*/ init_mathjax = function() { if (window.MathJax) { // MathJax loaded MathJax.Hub.Config({ TeX: { equationNumbers: { autoNumber: \"AMS\", useLabelIds: true } }, tex2jax: { inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ], displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ], processEscapes: true, processEnvironments: true }, displayAlign: 'center', CommonHTML: { linebreaks: { automatic: true } } }); MathJax.Hub.Queue([\"Typeset\", MathJax.Hub]); } } init_mathjax(); Deltares Software Days 2022: A simple hydrolib-core demo \u00b6 Hydrolib-core is a pip-installable python package. It consists of wrappers around the D-HYDRO model files. Classes in Hydrolib-core are hierarchically organized by file type, and can be accessed via hydrolib.core.io..models . File objects in Hydrolib-core reflect the same structure as the file contents. In this demo, we will load a Flow FM model, make some changes to the model and save it again. \ud83d\udca1 Tips for working in the Jupyter Notebook: Tab : Auto-complete on code Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell Ctrl + Shift + P : Open command palette Step 0) Importing the modules and setting the path variables \u00b6 In [ ]: Copied! from hydrolib.core.dflowfm import ( FMModel , Lateral , Weir , FlowDirection ) from pathlib import Path root = Path . cwd () demo_data_folder = root / \"data\" work_folder = root / \"work\" from hydrolib.core.dflowfm import ( FMModel, Lateral, Weir, FlowDirection ) from pathlib import Path root = Path.cwd() demo_data_folder = root / \"data\" work_folder = root / \"work\" Step 1) Loading a Flow FM model \u00b6 In [ ]: Copied! mdu_file_path = demo_data_folder / \"FlowFM.mdu\" model = FMModel ( filepath = mdu_file_path ) print ( f \"Loaded the model from { model . filepath } \" ) mdu_file_path = demo_data_folder / \"FlowFM.mdu\" model = FMModel(filepath=mdu_file_path) print(f\"Loaded the model from {model.filepath}\") Step 2) Inspecting the model \u00b6 We can see the hierarchy tree of the model by calling the following function: In [ ]: Copied! model . show_tree () model.show_tree() We can also inspect sub-parts of the model, like the structures. Note that a model can have multiple structure files, but this model only has one, so we will get the first and only one. In [ ]: Copied! assert model . geometry . structurefile is not None structure_file = model . geometry . structurefile [ 0 ] # Show the list of all the structures print ( f \"Number of structures: { len ( structure_file . structure ) } \" ) print ( structure_file . structure ) assert model.geometry.structurefile is not None structure_file = model.geometry.structurefile[0] # Show the list of all the structures print(f\"Number of structures: {len(structure_file.structure)}\") print(structure_file.structure) Step 3) Adjusting the model \u00b6 a) Creating a new weir and adding it to the structures \u00b6 In [ ]: Copied! # Create a new weir. weir = Weir ( id = \"DV_1471\" , branchId = \"458\" , chainage = 106.277467 , allowedFlowDir = FlowDirection . both , crestLevel = 0.400 , crestWidth = 40.000 , corrCoeff = 1.000 , useVelocityHeight = True ) # It is also possible to create objects with a dictionary. weir_data = { \"id\" : \"DV_1471\" , \"branchId\" : \"458\" , \"chainage\" : 106.277467 , \"allowedFlowDir\" : FlowDirection . both , \"crestLevel\" : 0.400 , \"crestWidth\" : 40.000 , \"corrCoeff\" : 1.000 , \"useVelocityHeight\" : True } weir = Weir ( ** weir_data ) # Add the weir to the model structure_file . structure . append ( weir ) print ( f \"Number of structures: { len ( structure_file . structure ) } \" ) # Create a new weir. weir = Weir( id=\"DV_1471\", branchId=\"458\", chainage=106.277467, allowedFlowDir=FlowDirection.both, crestLevel=0.400, crestWidth=40.000, corrCoeff=1.000, useVelocityHeight=True ) # It is also possible to create objects with a dictionary. weir_data = { \"id\": \"DV_1471\", \"branchId\": \"458\", \"chainage\": 106.277467, \"allowedFlowDir\": FlowDirection.both, \"crestLevel\": 0.400, \"crestWidth\": 40.000, \"corrCoeff\": 1.000, \"useVelocityHeight\": True } weir = Weir(**weir_data) # Add the weir to the model structure_file.structure.append(weir) print(f\"Number of structures: {len(structure_file.structure)}\") b) Adjusting some parameters of the model \u00b6 In [ ]: Copied! model . physics . backgroundsalinity = 30 # [ppt] model . physics . backgroundwatertemperature = 6 # [\u00b0C] model . time . dtuser = 900 # [s] model.physics.backgroundsalinity = 30 # [ppt] model.physics.backgroundwatertemperature = 6 # [\u00b0C] model.time.dtuser = 900 # [s] Hydrolib-core offers instant validation of objects that are created, either by loading them from file or by manually creating them. This makes it easier for users to create valid models. A lateral, like many other objects, should have a valid location specification, specified by: A node id, A branch id with a chainage, or Coordinates Let's create an invalid Lateral. We \"forget\" to specify a chainage. In [ ]: Copied! try : lateral = Lateral ( id = \"lateral_1\" , name = \"lateral_1\" , branchid = \"branch_a\" , discharge = \"realtime\" ) except ValueError as error : print ( error ) try: lateral = Lateral( id=\"lateral_1\", name=\"lateral_1\", branchid=\"branch_a\", discharge=\"realtime\" ) except ValueError as error: print(error) Now let's create a valid lateral. In [ ]: Copied! lateral = Lateral ( id = \"lateral_1\" , name = \"lateral_1\" , branchid = \"branch_a\" , chainage = 100 , discharge = \"realtime\" ) print ( \"Lateral with branch id and chainage is correct!\" ) lateral = Lateral( id=\"lateral_1\", name=\"lateral_1\", branchid=\"branch_a\", chainage=100, discharge=\"realtime\" ) print(\"Lateral with branch id and chainage is correct!\") Step 5) Saving the model \u00b6 If we save the model now, it will overwrite the current model files. So let's save it in a different location. In [ ]: Copied! print ( f \"The original model is located at { model . filepath } \" ) save_mdu_file_path = work_folder / \"save_model\" / \"FlowFM.mdu\" model . filepath = save_mdu_file_path # Set recurse to True. If it is False, only the MDU file will be saved. model . save ( recurse = True ) print ( f \"The saved model is located at { model . filepath } \" ) print(f\"The original model is located at {model.filepath}\") save_mdu_file_path = work_folder / \"save_model\" / \"FlowFM.mdu\" model.filepath = save_mdu_file_path # Set recurse to True. If it is False, only the MDU file will be saved. model.save(recurse=True) print(f\"The saved model is located at {model.filepath}\") Saving only a sub-part of the model \u00b6 It is also possible to save individual child model files, such as the cross section definition file. In [ ]: Copied! crossdef_file = model . geometry . crossdeffile assert crossdef_file is not None crossdef_file . filepath = work_folder / \"save_crossdef\" / \"crsdef.ini\" crossdef_file . save () print ( f \"The saved cross section definition model is located at { crossdef_file . filepath } \" ) crossdef_file = model.geometry.crossdeffile assert crossdef_file is not None crossdef_file.filepath = work_folder / \"save_crossdef\" / \"crsdef.ini\" crossdef_file.save() print(f\"The saved cross section definition model is located at {crossdef_file.filepath}\") In [ ]: Copied!","title":"Deltares Software Days 2022: A simple hydrolib-core demo"},{"location":"tutorials/dsd_2022_demo/demo_dsd/#deltares-software-days-2022-a-simple-hydrolib-core-demo","text":"Hydrolib-core is a pip-installable python package. It consists of wrappers around the D-HYDRO model files. Classes in Hydrolib-core are hierarchically organized by file type, and can be accessed via hydrolib.core.io..models . File objects in Hydrolib-core reflect the same structure as the file contents. In this demo, we will load a Flow FM model, make some changes to the model and save it again. \ud83d\udca1 Tips for working in the Jupyter Notebook: Tab : Auto-complete on code Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell Ctrl + Shift + P : Open command palette","title":"Deltares Software Days 2022: A simple hydrolib-core demo"},{"location":"tutorials/dsd_2022_demo/demo_dsd/#step-0-importing-the-modules-and-setting-the-path-variables","text":"In [ ]: Copied! from hydrolib.core.dflowfm import ( FMModel , Lateral , Weir , FlowDirection ) from pathlib import Path root = Path . cwd () demo_data_folder = root / \"data\" work_folder = root / \"work\" from hydrolib.core.dflowfm import ( FMModel, Lateral, Weir, FlowDirection ) from pathlib import Path root = Path.cwd() demo_data_folder = root / \"data\" work_folder = root / \"work\"","title":"Step 0) Importing the modules and setting the path variables"},{"location":"tutorials/dsd_2022_demo/demo_dsd/#step-1-loading-a-flow-fm-model","text":"In [ ]: Copied! mdu_file_path = demo_data_folder / \"FlowFM.mdu\" model = FMModel ( filepath = mdu_file_path ) print ( f \"Loaded the model from { model . filepath } \" ) mdu_file_path = demo_data_folder / \"FlowFM.mdu\" model = FMModel(filepath=mdu_file_path) print(f\"Loaded the model from {model.filepath}\")","title":"Step 1) Loading a Flow FM model"},{"location":"tutorials/dsd_2022_demo/demo_dsd/#step-2-inspecting-the-model","text":"We can see the hierarchy tree of the model by calling the following function: In [ ]: Copied! model . show_tree () model.show_tree() We can also inspect sub-parts of the model, like the structures. Note that a model can have multiple structure files, but this model only has one, so we will get the first and only one. In [ ]: Copied! assert model . geometry . structurefile is not None structure_file = model . geometry . structurefile [ 0 ] # Show the list of all the structures print ( f \"Number of structures: { len ( structure_file . structure ) } \" ) print ( structure_file . structure ) assert model.geometry.structurefile is not None structure_file = model.geometry.structurefile[0] # Show the list of all the structures print(f\"Number of structures: {len(structure_file.structure)}\") print(structure_file.structure)","title":"Step 2) Inspecting the model"},{"location":"tutorials/dsd_2022_demo/demo_dsd/#step-3-adjusting-the-model","text":"","title":"Step 3) Adjusting the model"},{"location":"tutorials/dsd_2022_demo/demo_dsd/#a-creating-a-new-weir-and-adding-it-to-the-structures","text":"In [ ]: Copied! # Create a new weir. weir = Weir ( id = \"DV_1471\" , branchId = \"458\" , chainage = 106.277467 , allowedFlowDir = FlowDirection . both , crestLevel = 0.400 , crestWidth = 40.000 , corrCoeff = 1.000 , useVelocityHeight = True ) # It is also possible to create objects with a dictionary. weir_data = { \"id\" : \"DV_1471\" , \"branchId\" : \"458\" , \"chainage\" : 106.277467 , \"allowedFlowDir\" : FlowDirection . both , \"crestLevel\" : 0.400 , \"crestWidth\" : 40.000 , \"corrCoeff\" : 1.000 , \"useVelocityHeight\" : True } weir = Weir ( ** weir_data ) # Add the weir to the model structure_file . structure . append ( weir ) print ( f \"Number of structures: { len ( structure_file . structure ) } \" ) # Create a new weir. weir = Weir( id=\"DV_1471\", branchId=\"458\", chainage=106.277467, allowedFlowDir=FlowDirection.both, crestLevel=0.400, crestWidth=40.000, corrCoeff=1.000, useVelocityHeight=True ) # It is also possible to create objects with a dictionary. weir_data = { \"id\": \"DV_1471\", \"branchId\": \"458\", \"chainage\": 106.277467, \"allowedFlowDir\": FlowDirection.both, \"crestLevel\": 0.400, \"crestWidth\": 40.000, \"corrCoeff\": 1.000, \"useVelocityHeight\": True } weir = Weir(**weir_data) # Add the weir to the model structure_file.structure.append(weir) print(f\"Number of structures: {len(structure_file.structure)}\")","title":"a) Creating a new weir and adding it to the structures"},{"location":"tutorials/dsd_2022_demo/demo_dsd/#b-adjusting-some-parameters-of-the-model","text":"In [ ]: Copied! model . physics . backgroundsalinity = 30 # [ppt] model . physics . backgroundwatertemperature = 6 # [\u00b0C] model . time . dtuser = 900 # [s] model.physics.backgroundsalinity = 30 # [ppt] model.physics.backgroundwatertemperature = 6 # [\u00b0C] model.time.dtuser = 900 # [s] Hydrolib-core offers instant validation of objects that are created, either by loading them from file or by manually creating them. This makes it easier for users to create valid models. A lateral, like many other objects, should have a valid location specification, specified by: A node id, A branch id with a chainage, or Coordinates Let's create an invalid Lateral. We \"forget\" to specify a chainage. In [ ]: Copied! try : lateral = Lateral ( id = \"lateral_1\" , name = \"lateral_1\" , branchid = \"branch_a\" , discharge = \"realtime\" ) except ValueError as error : print ( error ) try: lateral = Lateral( id=\"lateral_1\", name=\"lateral_1\", branchid=\"branch_a\", discharge=\"realtime\" ) except ValueError as error: print(error) Now let's create a valid lateral. In [ ]: Copied! lateral = Lateral ( id = \"lateral_1\" , name = \"lateral_1\" , branchid = \"branch_a\" , chainage = 100 , discharge = \"realtime\" ) print ( \"Lateral with branch id and chainage is correct!\" ) lateral = Lateral( id=\"lateral_1\", name=\"lateral_1\", branchid=\"branch_a\", chainage=100, discharge=\"realtime\" ) print(\"Lateral with branch id and chainage is correct!\")","title":"b) Adjusting some parameters of the model"},{"location":"tutorials/dsd_2022_demo/demo_dsd/#step-5-saving-the-model","text":"If we save the model now, it will overwrite the current model files. So let's save it in a different location. In [ ]: Copied! print ( f \"The original model is located at { model . filepath } \" ) save_mdu_file_path = work_folder / \"save_model\" / \"FlowFM.mdu\" model . filepath = save_mdu_file_path # Set recurse to True. If it is False, only the MDU file will be saved. model . save ( recurse = True ) print ( f \"The saved model is located at { model . filepath } \" ) print(f\"The original model is located at {model.filepath}\") save_mdu_file_path = work_folder / \"save_model\" / \"FlowFM.mdu\" model.filepath = save_mdu_file_path # Set recurse to True. If it is False, only the MDU file will be saved. model.save(recurse=True) print(f\"The saved model is located at {model.filepath}\")","title":"Step 5) Saving the model"},{"location":"tutorials/dsd_2022_demo/demo_dsd/#saving-only-a-sub-part-of-the-model","text":"It is also possible to save individual child model files, such as the cross section definition file. In [ ]: Copied! crossdef_file = model . geometry . crossdeffile assert crossdef_file is not None crossdef_file . filepath = work_folder / \"save_crossdef\" / \"crsdef.ini\" crossdef_file . save () print ( f \"The saved cross section definition model is located at { crossdef_file . filepath } \" ) crossdef_file = model.geometry.crossdeffile assert crossdef_file is not None crossdef_file.filepath = work_folder / \"save_crossdef\" / \"crsdef.ini\" crossdef_file.save() print(f\"The saved cross section definition model is located at {crossdef_file.filepath}\") In [ ]: Copied!","title":"Saving only a sub-part of the model"},{"location":"tutorials/dsd_2023/instructions/","text":"HYDROLIB-core guide for the Delft Software Days 2023 \u00b6 Contents \u00b6 HYDROLIB-core guide for the Delft Software Days 2023 Contents Introduction User guide Requirements Installation Run the demo notebook Cheat sheet Kernel files vs HYDROLIB-core FileModels Commonly used functions of a FileModel Introduction \u00b6 This document contains instructions about the installation and usage of HYDROLIB-core during the Delft Software Days 2023. HYDROLIB-core is a Python package that offers functionality to process D-HYDRO input files. It offers Python-wrapped classes that represent these files and their content. HYDROLIB-core serves as the basis for various pre- and postprocessing tools for a modelling workflow of hydrodynamic simulations in D-HYDRO. User guide \u00b6 Requirements \u00b6 Before getting started with HYDROLIB-core, make sure you have the following software and tools installed: Anaconda : https://www.anaconda.com/download Anaconda is an open-source distribution for Python and contains the package manager \"conda\". (!) Make sure to add Anaconda to your PATH environment variable during installation. Installation \u00b6 Once you've installed the required software, you can create a Python 3.11 environment with HYDROLIB-core 0.5.2, the latest release. Note that the environment that we are creating now contains not only HYDROLIB-core, but also the other packages that are needed today during the breakout sessions. Follow these steps: Open your command line interface Enter the following commands: conda create --name dsd_env python=3.11 git -c conda-forge -y conda activate dsd_env pip install hydromt_delft3dfm[examples] dfm_tools pyogrio openpyxl conda deactivate After executing these commands, an Anaconda environment with the latest HYDROLIB-core is created. After deactivation, you can reactivate this environment at any time by using the following command: conda activate dsd_env If you'd like to remove the environment entirely, call the following command: conda remove -n dsd_env --all This will remove all the packages in the environment and the environment folder itself. Run the demo notebook \u00b6 We'd like to be able to run the provided demo notebook. We can set it up with the following steps: Open a command line in the HYDROLIB-core folder Activate the conda environment: conda activate dsd_env And start Jupyter Notebook: jupyter notebook Open the demo.ipynb inside the demo folder Cheat sheet \u00b6 In HYDROLIB-core, there is a class called FileModel, which is used to represent an individual kernel file. This class has multiple derived implementations, with each one corresponding to a specific kernel file. Every FileModel, except for the root model, is referenced within another FileModel, following the same hierarchy as the kernel files themselves. The table below contains the models relevant for today's exercises. Kernel files vs HYDROLIB-core FileModels \u00b6 Kernel file FileModel File reference Model definition file (*.mdu) FMModel - Network file (*_net.nc) NetworkModel Model definition file > geometry > netFile Cross-section location file (crosloc.ini) CrossLocModel Model definition file > geometry > crossLocFile Cross-section definition file (crosdef.ini) CrossDefModel Model definition file > geometry > crossDefFile Roughness file (roughness-*.ini) FrictionModel Model definition file > geometry > frictFile New external forcing file (*_bnd.ext) ExtModel Model definition file > external forcing > extForceFileNew Boundary conditions file (*.bc) ForcingModel New external forcing file > boundary > forcingFile 1D initial conditions field file (*.ini) OneDFieldModel Initial field file > initial > dataFile Initial field file (*.ini) IniFieldModel Model definition file > geometry > iniFieldFile Structures file (structures.ini) StructureModel Model definition file > geometry > structureFile Commonly used functions of a FileModel \u00b6 Each FileModel offers a set of commonly used functions. init () --- Initialize a new file model instance Parameters (all optional): * filepath (Path) : The file path from which the file model should be loaded. Default to None. * resolve_casing (bool) : Whether or not to resolve the file name references so that they match the case with what is on disk. Defaults to False. * recurse (bool) : Whether or not to recursively load the model. Defaults to True. * path_style (str) : Which path style is used in the loaded files. Options: 'unix', 'windows'. Defaults to the path style that matches the current operating system. save() --- Export the file model data to a file Parameters (all optional): * filepath (Path) : The file path at which this model is saved. If None is specified it defaults to the filepath currently stored in the filemodel. Defaults to None. * recurse (bool) : Whether or not to recursively save all children of this file model, or only save this model. Defaults to False. * path_style (str) : With which file path style to save the model. File references will be written with the specified path style. Options: 'unix', 'windows'. Defaults to the path style used by the current operating system. show_tree() --- Print the file model tree","title":"HYDROLIB-core guide for the Delft Software Days 2023"},{"location":"tutorials/dsd_2023/instructions/#hydrolib-core-guide-for-the-delft-software-days-2023","text":"","title":"HYDROLIB-core guide for the Delft Software Days 2023"},{"location":"tutorials/dsd_2023/instructions/#contents","text":"HYDROLIB-core guide for the Delft Software Days 2023 Contents Introduction User guide Requirements Installation Run the demo notebook Cheat sheet Kernel files vs HYDROLIB-core FileModels Commonly used functions of a FileModel","title":"Contents"},{"location":"tutorials/dsd_2023/instructions/#introduction","text":"This document contains instructions about the installation and usage of HYDROLIB-core during the Delft Software Days 2023. HYDROLIB-core is a Python package that offers functionality to process D-HYDRO input files. It offers Python-wrapped classes that represent these files and their content. HYDROLIB-core serves as the basis for various pre- and postprocessing tools for a modelling workflow of hydrodynamic simulations in D-HYDRO.","title":"Introduction"},{"location":"tutorials/dsd_2023/instructions/#user-guide","text":"","title":"User guide"},{"location":"tutorials/dsd_2023/instructions/#requirements","text":"Before getting started with HYDROLIB-core, make sure you have the following software and tools installed: Anaconda : https://www.anaconda.com/download Anaconda is an open-source distribution for Python and contains the package manager \"conda\". (!) Make sure to add Anaconda to your PATH environment variable during installation.","title":"Requirements"},{"location":"tutorials/dsd_2023/instructions/#installation","text":"Once you've installed the required software, you can create a Python 3.11 environment with HYDROLIB-core 0.5.2, the latest release. Note that the environment that we are creating now contains not only HYDROLIB-core, but also the other packages that are needed today during the breakout sessions. Follow these steps: Open your command line interface Enter the following commands: conda create --name dsd_env python=3.11 git -c conda-forge -y conda activate dsd_env pip install hydromt_delft3dfm[examples] dfm_tools pyogrio openpyxl conda deactivate After executing these commands, an Anaconda environment with the latest HYDROLIB-core is created. After deactivation, you can reactivate this environment at any time by using the following command: conda activate dsd_env If you'd like to remove the environment entirely, call the following command: conda remove -n dsd_env --all This will remove all the packages in the environment and the environment folder itself.","title":"Installation"},{"location":"tutorials/dsd_2023/instructions/#run-the-demo-notebook","text":"We'd like to be able to run the provided demo notebook. We can set it up with the following steps: Open a command line in the HYDROLIB-core folder Activate the conda environment: conda activate dsd_env And start Jupyter Notebook: jupyter notebook Open the demo.ipynb inside the demo folder","title":"Run the demo notebook"},{"location":"tutorials/dsd_2023/instructions/#cheat-sheet","text":"In HYDROLIB-core, there is a class called FileModel, which is used to represent an individual kernel file. This class has multiple derived implementations, with each one corresponding to a specific kernel file. Every FileModel, except for the root model, is referenced within another FileModel, following the same hierarchy as the kernel files themselves. The table below contains the models relevant for today's exercises.","title":"Cheat sheet"},{"location":"tutorials/dsd_2023/instructions/#kernel-files-vs-hydrolib-core-filemodels","text":"Kernel file FileModel File reference Model definition file (*.mdu) FMModel - Network file (*_net.nc) NetworkModel Model definition file > geometry > netFile Cross-section location file (crosloc.ini) CrossLocModel Model definition file > geometry > crossLocFile Cross-section definition file (crosdef.ini) CrossDefModel Model definition file > geometry > crossDefFile Roughness file (roughness-*.ini) FrictionModel Model definition file > geometry > frictFile New external forcing file (*_bnd.ext) ExtModel Model definition file > external forcing > extForceFileNew Boundary conditions file (*.bc) ForcingModel New external forcing file > boundary > forcingFile 1D initial conditions field file (*.ini) OneDFieldModel Initial field file > initial > dataFile Initial field file (*.ini) IniFieldModel Model definition file > geometry > iniFieldFile Structures file (structures.ini) StructureModel Model definition file > geometry > structureFile","title":"Kernel files vs HYDROLIB-core FileModels"},{"location":"tutorials/dsd_2023/instructions/#commonly-used-functions-of-a-filemodel","text":"Each FileModel offers a set of commonly used functions. init () --- Initialize a new file model instance Parameters (all optional): * filepath (Path) : The file path from which the file model should be loaded. Default to None. * resolve_casing (bool) : Whether or not to resolve the file name references so that they match the case with what is on disk. Defaults to False. * recurse (bool) : Whether or not to recursively load the model. Defaults to True. * path_style (str) : Which path style is used in the loaded files. Options: 'unix', 'windows'. Defaults to the path style that matches the current operating system. save() --- Export the file model data to a file Parameters (all optional): * filepath (Path) : The file path at which this model is saved. If None is specified it defaults to the filepath currently stored in the filemodel. Defaults to None. * recurse (bool) : Whether or not to recursively save all children of this file model, or only save this model. Defaults to False. * path_style (str) : With which file path style to save the model. File references will be written with the specified path style. Options: 'unix', 'windows'. Defaults to the path style used by the current operating system. show_tree() --- Print the file model tree","title":"Commonly used functions of a FileModel"},{"location":"tutorials/dsd_2023/demo/demo/","text":"(function (global, factory) { typeof exports === 'object' && typeof module !== 'undefined' ? module.exports = factory() : typeof define === 'function' && define.amd ? define(factory) : (global = global || self, global.ClipboardCopyElement = factory()); }(this, function () { 'use strict'; function createNode(text) { const node = document.createElement('pre'); node.style.width = '1px'; node.style.height = '1px'; node.style.position = 'fixed'; node.style.top = '5px'; node.textContent = text; return node; } function copyNode(node) { if ('clipboard' in navigator) { // eslint-disable-next-line flowtype/no-flow-fix-me-comments // $FlowFixMe Clipboard is not defined in Flow yet. return navigator.clipboard.writeText(node.textContent); } const selection = getSelection(); if (selection == null) { return Promise.reject(new Error()); 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These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ --jp-shadow-base-lightness: 0; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-400); --jp-border-color1: var(--md-grey-400); --jp-border-color2: var(--md-grey-300); --jp-border-color3: var(--md-grey-200); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(0, 0, 0, 1); --jp-ui-font-color1: rgba(0, 0, 0, 0.87); --jp-ui-font-color2: rgba(0, 0, 0, 0.54); --jp-ui-font-color3: rgba(0, 0, 0, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color1: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color2: rgba(255, 255, 255, 0.7); --jp-ui-inverse-font-color3: rgba(255, 255, 255, 0.5); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(0, 0, 0, 1); --jp-content-font-color1: rgba(0, 0, 0, 0.87); --jp-content-font-color2: rgba(0, 0, 0, 0.54); --jp-content-font-color3: rgba(0, 0, 0, 0.38); --jp-content-link-color: var(--md-blue-700); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: white; --jp-layout-color1: white; --jp-layout-color2: var(--md-grey-200); --jp-layout-color3: var(--md-grey-400); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: #111111; --jp-inverse-layout-color1: var(--md-grey-900); --jp-inverse-layout-color2: var(--md-grey-800); --jp-inverse-layout-color3: var(--md-grey-700); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-900); --jp-brand-color1: var(--md-blue-700); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-900); --jp-accent-color1: var(--md-green-700); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-900); --jp-warn-color1: var(--md-orange-700); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-900); --jp-error-color1: var(--md-red-700); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-900); --jp-success-color1: var(--md-green-700); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-900); --jp-info-color1: var(--md-cyan-700); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--md-grey-100); --jp-cell-editor-border-color: var(--md-grey-300); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 0.5; --jp-cell-prompt-not-active-font-color: var(--md-grey-700); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: var(--md-blue-50); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: #fdd; --jp-rendermime-table-row-background: var(--md-grey-100); --jp-rendermime-table-row-hover-background: var(--md-light-blue-50); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.25); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color1); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.24); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--md-grey-300); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color1); --jp-input-hover-background: var(--jp-layout-color1); --jp-input-background: var(--md-grey-100); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: #d9d9d9; --jp-editor-selected-focused-background: #d7d4f0; --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: #008000; --jp-mirror-editor-atom-color: #88f; --jp-mirror-editor-number-color: #080; --jp-mirror-editor-def-color: #00f; --jp-mirror-editor-variable-color: var(--md-grey-900); --jp-mirror-editor-variable-2-color: #05a; --jp-mirror-editor-variable-3-color: #085; --jp-mirror-editor-punctuation-color: #05a; --jp-mirror-editor-property-color: #05a; --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ba2121; --jp-mirror-editor-string-2-color: #708; --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: #008000; --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: #170; --jp-mirror-editor-attribute-color: #00c; --jp-mirror-editor-header-color: blue; --jp-mirror-editor-quote-color: #090; --jp-mirror-editor-link-color: #00c; --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: white; /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.5; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(245, 200, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } [data-md-color-scheme=\"slate\"] .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ /* The dark theme shadows need a bit of work, but this will probably also require work on the core layout * colors used in the theme as well. */ --jp-shadow-base-lightness: 32; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-700); --jp-border-color1: var(--md-grey-700); --jp-border-color2: var(--md-grey-800); --jp-border-color3: var(--md-grey-900); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(255, 255, 255, 1); --jp-ui-font-color1: rgba(255, 255, 255, 0.87); --jp-ui-font-color2: rgba(255, 255, 255, 0.54); --jp-ui-font-color3: rgba(255, 255, 255, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(0, 0, 0, 1); --jp-ui-inverse-font-color1: rgba(0, 0, 0, 0.8); --jp-ui-inverse-font-color2: rgba(0, 0, 0, 0.5); --jp-ui-inverse-font-color3: rgba(0, 0, 0, 0.3); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(255, 255, 255, 1); --jp-content-font-color1: rgba(255, 255, 255, 1); --jp-content-font-color2: rgba(255, 255, 255, 0.7); --jp-content-font-color3: rgba(255, 255, 255, 0.5); --jp-content-link-color: var(--md-blue-300); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: #111111; --jp-layout-color1: var(--md-grey-900); --jp-layout-color2: var(--md-grey-800); --jp-layout-color3: var(--md-grey-700); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: white; --jp-inverse-layout-color1: white; --jp-inverse-layout-color2: var(--md-grey-200); --jp-inverse-layout-color3: var(--md-grey-400); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-700); --jp-brand-color1: var(--md-blue-500); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-700); --jp-accent-color1: var(--md-green-500); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-700); --jp-warn-color1: var(--md-orange-500); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-700); --jp-error-color1: var(--md-red-500); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-700); --jp-success-color1: var(--md-green-500); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-700); --jp-info-color1: var(--md-cyan-500); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--jp-layout-color1); --jp-cell-editor-border-color: var(--md-grey-700); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 1; --jp-cell-prompt-not-active-font-color: var(--md-grey-300); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: rgba(33, 150, 243, 0.24); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: rgba(244, 67, 54, 0.28); --jp-rendermime-table-row-background: var(--md-grey-900); --jp-rendermime-table-row-hover-background: rgba(3, 169, 244, 0.2); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.6); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color2); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.8); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--jp-layout-color0); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color0); --jp-input-hover-background: var(--jp-layout-color2); --jp-input-background: var(--md-grey-800); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: var(--jp-layout-color2); --jp-editor-selected-focused-background: rgba(33, 150, 243, 0.24); --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: var(--md-green-500); --jp-mirror-editor-atom-color: var(--md-blue-300); --jp-mirror-editor-number-color: var(--md-green-400); --jp-mirror-editor-def-color: var(--md-blue-600); --jp-mirror-editor-variable-color: var(--md-grey-300); --jp-mirror-editor-variable-2-color: var(--md-blue-400); --jp-mirror-editor-variable-3-color: var(--md-green-600); --jp-mirror-editor-punctuation-color: var(--md-blue-400); --jp-mirror-editor-property-color: var(--md-blue-400); --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ff7070; --jp-mirror-editor-string-2-color: var(--md-purple-300); --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: var(--md-green-600); --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: var(--md-green-700); --jp-mirror-editor-attribute-color: var(--md-blue-700); --jp-mirror-editor-header-color: var(--md-blue-500); --jp-mirror-editor-quote-color: var(--md-green-300); --jp-mirror-editor-link-color: var(--md-blue-700); --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: var(--md-grey-400); /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.6; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(255, 225, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* scrollbar related styles. Supports every browser except Edge. */ /* colors based on JetBrain's Darcula theme */ --jp-scrollbar-background-color: #3f4244; --jp-scrollbar-thumb-color: 88, 96, 97; /* need to specify thumb color as an RGB triplet */ --jp-scrollbar-endpad: 3px; /* the minimum gap between the thumb and the ends of a scrollbar */ /* hacks for setting the thumb shape. These do nothing in Firefox */ --jp-scrollbar-thumb-margin: 3.5px; /* the space in between the sides of the thumb and the track */ --jp-scrollbar-thumb-radius: 9px; /* set to a large-ish value for rounded endcaps on the thumb */ /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } :root{--md-red-50: #ffebee;--md-red-100: #ffcdd2;--md-red-200: #ef9a9a;--md-red-300: #e57373;--md-red-400: #ef5350;--md-red-500: #f44336;--md-red-600: #e53935;--md-red-700: #d32f2f;--md-red-800: #c62828;--md-red-900: #b71c1c;--md-red-A100: #ff8a80;--md-red-A200: #ff5252;--md-red-A400: #ff1744;--md-red-A700: #d50000;--md-pink-50: #fce4ec;--md-pink-100: #f8bbd0;--md-pink-200: #f48fb1;--md-pink-300: #f06292;--md-pink-400: #ec407a;--md-pink-500: #e91e63;--md-pink-600: #d81b60;--md-pink-700: #c2185b;--md-pink-800: 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#7986cb;--md-indigo-400: #5c6bc0;--md-indigo-500: #3f51b5;--md-indigo-600: #3949ab;--md-indigo-700: #303f9f;--md-indigo-800: #283593;--md-indigo-900: #1a237e;--md-indigo-A100: #8c9eff;--md-indigo-A200: #536dfe;--md-indigo-A400: #3d5afe;--md-indigo-A700: #304ffe;--md-blue-50: #e3f2fd;--md-blue-100: #bbdefb;--md-blue-200: #90caf9;--md-blue-300: #64b5f6;--md-blue-400: #42a5f5;--md-blue-500: #2196f3;--md-blue-600: #1e88e5;--md-blue-700: #1976d2;--md-blue-800: #1565c0;--md-blue-900: #0d47a1;--md-blue-A100: #82b1ff;--md-blue-A200: #448aff;--md-blue-A400: #2979ff;--md-blue-A700: #2962ff;--md-light-blue-50: #e1f5fe;--md-light-blue-100: #b3e5fc;--md-light-blue-200: #81d4fa;--md-light-blue-300: #4fc3f7;--md-light-blue-400: #29b6f6;--md-light-blue-500: #03a9f4;--md-light-blue-600: #039be5;--md-light-blue-700: #0288d1;--md-light-blue-800: #0277bd;--md-light-blue-900: #01579b;--md-light-blue-A100: #80d8ff;--md-light-blue-A200: #40c4ff;--md-light-blue-A400: #00b0ff;--md-light-blue-A700: #0091ea;--md-cyan-50: #e0f7fa;--md-cyan-100: #b2ebf2;--md-cyan-200: #80deea;--md-cyan-300: #4dd0e1;--md-cyan-400: #26c6da;--md-cyan-500: #00bcd4;--md-cyan-600: #00acc1;--md-cyan-700: #0097a7;--md-cyan-800: #00838f;--md-cyan-900: #006064;--md-cyan-A100: #84ffff;--md-cyan-A200: #18ffff;--md-cyan-A400: #00e5ff;--md-cyan-A700: #00b8d4;--md-teal-50: #e0f2f1;--md-teal-100: #b2dfdb;--md-teal-200: #80cbc4;--md-teal-300: #4db6ac;--md-teal-400: #26a69a;--md-teal-500: #009688;--md-teal-600: #00897b;--md-teal-700: #00796b;--md-teal-800: #00695c;--md-teal-900: #004d40;--md-teal-A100: #a7ffeb;--md-teal-A200: #64ffda;--md-teal-A400: #1de9b6;--md-teal-A700: #00bfa5;--md-green-50: #e8f5e9;--md-green-100: #c8e6c9;--md-green-200: #a5d6a7;--md-green-300: #81c784;--md-green-400: #66bb6a;--md-green-500: #4caf50;--md-green-600: #43a047;--md-green-700: #388e3c;--md-green-800: #2e7d32;--md-green-900: #1b5e20;--md-green-A100: #b9f6ca;--md-green-A200: #69f0ae;--md-green-A400: #00e676;--md-green-A700: #00c853;--md-light-green-50: #f1f8e9;--md-light-green-100: #dcedc8;--md-light-green-200: #c5e1a5;--md-light-green-300: #aed581;--md-light-green-400: #9ccc65;--md-light-green-500: #8bc34a;--md-light-green-600: #7cb342;--md-light-green-700: #689f38;--md-light-green-800: #558b2f;--md-light-green-900: #33691e;--md-light-green-A100: #ccff90;--md-light-green-A200: #b2ff59;--md-light-green-A400: #76ff03;--md-light-green-A700: #64dd17;--md-lime-50: #f9fbe7;--md-lime-100: #f0f4c3;--md-lime-200: #e6ee9c;--md-lime-300: #dce775;--md-lime-400: #d4e157;--md-lime-500: #cddc39;--md-lime-600: #c0ca33;--md-lime-700: #afb42b;--md-lime-800: #9e9d24;--md-lime-900: #827717;--md-lime-A100: #f4ff81;--md-lime-A200: #eeff41;--md-lime-A400: #c6ff00;--md-lime-A700: #aeea00;--md-yellow-50: #fffde7;--md-yellow-100: #fff9c4;--md-yellow-200: #fff59d;--md-yellow-300: #fff176;--md-yellow-400: #ffee58;--md-yellow-500: #ffeb3b;--md-yellow-600: #fdd835;--md-yellow-700: #fbc02d;--md-yellow-800: #f9a825;--md-yellow-900: #f57f17;--md-yellow-A100: #ffff8d;--md-yellow-A200: #ffff00;--md-yellow-A400: #ffea00;--md-yellow-A700: #ffd600;--md-amber-50: #fff8e1;--md-amber-100: #ffecb3;--md-amber-200: #ffe082;--md-amber-300: #ffd54f;--md-amber-400: #ffca28;--md-amber-500: #ffc107;--md-amber-600: #ffb300;--md-amber-700: #ffa000;--md-amber-800: #ff8f00;--md-amber-900: #ff6f00;--md-amber-A100: #ffe57f;--md-amber-A200: #ffd740;--md-amber-A400: #ffc400;--md-amber-A700: #ffab00;--md-orange-50: #fff3e0;--md-orange-100: #ffe0b2;--md-orange-200: #ffcc80;--md-orange-300: #ffb74d;--md-orange-400: #ffa726;--md-orange-500: #ff9800;--md-orange-600: #fb8c00;--md-orange-700: #f57c00;--md-orange-800: #ef6c00;--md-orange-900: #e65100;--md-orange-A100: #ffd180;--md-orange-A200: #ffab40;--md-orange-A400: #ff9100;--md-orange-A700: #ff6d00;--md-deep-orange-50: #fbe9e7;--md-deep-orange-100: #ffccbc;--md-deep-orange-200: #ffab91;--md-deep-orange-300: #ff8a65;--md-deep-orange-400: #ff7043;--md-deep-orange-500: 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sourceMappingURL=mkdocs-jupyter.css.map*/ init_mathjax = function() { if (window.MathJax) { // MathJax loaded MathJax.Hub.Config({ TeX: { equationNumbers: { autoNumber: \"AMS\", useLabelIds: true } }, tex2jax: { inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ], displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ], processEscapes: true, processEnvironments: true }, displayAlign: 'center', CommonHTML: { linebreaks: { automatic: true } } }); MathJax.Hub.Queue([\"Typeset\", MathJax.Hub]); } } init_mathjax(); Deltares Software Days 2023: A simple hydrolib-core demo \u00b6 Hydrolib-core is a pip-installable python package. It consists of wrappers around the D-HYDRO model files. Classes in Hydrolib-core are hierarchically organized by file type, and can be accessed via hydrolib.core.io..models . File objects in Hydrolib-core reflect the same structure as the file contents. In this demo, we will load a Flow FM model, make some changes to the model and save it again. \ud83d\udca1 Tips for working in the Jupyter Notebook: Tab : Auto-complete on code Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell 0. Importing the modules and setting the path variables \u00b6 In [ ]: Copied! from hydrolib.core.dflowfm import ( FMModel , Lateral , Weir , FlowDirection ) from pathlib import Path root = Path . cwd () demo_data_folder = root / \"data\" export_folder = root / \"export\" from hydrolib.core.dflowfm import ( FMModel, Lateral, Weir, FlowDirection ) from pathlib import Path root = Path.cwd() demo_data_folder = root / \"data\" export_folder = root / \"export\" 1. Loading a Flow FM model \u00b6 In [ ]: Copied! mdu_file_path = demo_data_folder / \"FlowFM.mdu\" model = FMModel ( filepath = mdu_file_path ) print ( f \"Loaded the model from { model . filepath } \" ) mdu_file_path = demo_data_folder / \"FlowFM.mdu\" model = FMModel(filepath=mdu_file_path) print(f\"Loaded the model from {model.filepath}\") 2. Inspecting the model \u00b6 We can see the hierarchy tree of the model by calling the following function: In [ ]: Copied! model . show_tree () model.show_tree() We can also inspect sub-parts of the model, like the structures. Note that a model can have multiple structure files, but this model only has one, so we will get the first and only one. In [ ]: Copied! assert model . geometry . structurefile is not None structure_file = model . geometry . structurefile [ 0 ] # Show the list of all the structures print ( f \"Number of structures: { len ( structure_file . structure ) } \" ) print ( structure_file . structure ) assert model.geometry.structurefile is not None structure_file = model.geometry.structurefile[0] # Show the list of all the structures print(f\"Number of structures: {len(structure_file.structure)}\") print(structure_file.structure) 3. Adjusting the model \u00b6 a. Creating a new weir and adding it to the structures** \u00b6 In [ ]: Copied! # Create a new weir. weir = Weir ( id = \"DV_1471\" , branchId = \"458\" , chainage = 106.277467 , allowedFlowDir = FlowDirection . both , crestLevel = 0.400 , crestWidth = 40.000 , corrCoeff = 1.000 , useVelocityHeight = True ) # It is also possible to create objects with a dictionary. weir_data = { \"id\" : \"DV_1471\" , \"branchId\" : \"458\" , \"chainage\" : 106.277467 , \"allowedFlowDir\" : FlowDirection . both , \"crestLevel\" : 0.400 , \"crestWidth\" : 40.000 , \"corrCoeff\" : 1.000 , \"useVelocityHeight\" : True } weir = Weir ( ** weir_data ) # Add the weir to the model structure_file . structure . append ( weir ) print ( f \"Number of structures: { len ( structure_file . structure ) } \" ) # Create a new weir. weir = Weir( id=\"DV_1471\", branchId=\"458\", chainage=106.277467, allowedFlowDir=FlowDirection.both, crestLevel=0.400, crestWidth=40.000, corrCoeff=1.000, useVelocityHeight=True ) # It is also possible to create objects with a dictionary. weir_data = { \"id\": \"DV_1471\", \"branchId\": \"458\", \"chainage\": 106.277467, \"allowedFlowDir\": FlowDirection.both, \"crestLevel\": 0.400, \"crestWidth\": 40.000, \"corrCoeff\": 1.000, \"useVelocityHeight\": True } weir = Weir(**weir_data) # Add the weir to the model structure_file.structure.append(weir) print(f\"Number of structures: {len(structure_file.structure)}\") b. Adjusting some parameters of the model \u00b6 In [ ]: Copied! model . physics . backgroundsalinity = 30 # [ppt] model . physics . backgroundwatertemperature = 6 # [\u00b0C] model . time . dtuser = 900 # [s] model.physics.backgroundsalinity = 30 # [ppt] model.physics.backgroundwatertemperature = 6 # [\u00b0C] model.time.dtuser = 900 # [s] Hydrolib-core offers instant validation of objects that are created, either by loading them from file or by manually creating them. This makes it easier for users to create valid models. A lateral, like many other objects, should have a valid location specification, specified by: A node id, A branch id with a chainage, or Coordinates Let's create an invalid Lateral. We \"forget\" to specify a chainage. In [ ]: Copied! try : lateral = Lateral ( id = \"lateral_1\" , name = \"lateral_1\" , branchid = \"branch_a\" , discharge = \"realtime\" ) except ValueError as error : print ( error ) try: lateral = Lateral( id=\"lateral_1\", name=\"lateral_1\", branchid=\"branch_a\", discharge=\"realtime\" ) except ValueError as error: print(error) Now let's create a valid lateral. In [ ]: Copied! lateral = Lateral ( id = \"lateral_1\" , name = \"lateral_1\" , branchid = \"branch_a\" , chainage = 100 , discharge = \"realtime\" ) print ( \"Lateral with branch id and chainage is correct!\" ) lateral = Lateral( id=\"lateral_1\", name=\"lateral_1\", branchid=\"branch_a\", chainage=100, discharge=\"realtime\" ) print(\"Lateral with branch id and chainage is correct!\") 5. Saving the model \u00b6 If we save the model now, it will overwrite the current model files. So let's save it in a different location. In [ ]: Copied! print ( f \"The original model is located at { model . filepath } \" ) save_mdu_file_path = export_folder / \"save_model\" / \"FlowFM.mdu\" model . filepath = save_mdu_file_path # Set recurse to True. If it is False, only the MDU file will be saved. model . save ( recurse = True ) print ( f \"The saved model is located at { model . filepath } \" ) print(f\"The original model is located at {model.filepath}\") save_mdu_file_path = export_folder / \"save_model\" / \"FlowFM.mdu\" model.filepath = save_mdu_file_path # Set recurse to True. If it is False, only the MDU file will be saved. model.save(recurse=True) print(f\"The saved model is located at {model.filepath}\") 6. Saving only a sub-part of the model \u00b6 It is also possible to save individual child model files, such as the cross section definition file. In [ ]: Copied! crossdef_file = model . geometry . crossdeffile assert crossdef_file is not None crossdef_file . filepath = export_folder / \"save_crossdef\" / \"crsdef.ini\" crossdef_file . save () print ( f \"The saved cross section definition model is located at { crossdef_file . filepath } \" ) crossdef_file = model.geometry.crossdeffile assert crossdef_file is not None crossdef_file.filepath = export_folder / \"save_crossdef\" / \"crsdef.ini\" crossdef_file.save() print(f\"The saved cross section definition model is located at {crossdef_file.filepath}\")","title":"Deltares Software Days 2023: A simple hydrolib-core demo"},{"location":"tutorials/dsd_2023/demo/demo/#deltares-software-days-2023-a-simple-hydrolib-core-demo","text":"Hydrolib-core is a pip-installable python package. It consists of wrappers around the D-HYDRO model files. Classes in Hydrolib-core are hierarchically organized by file type, and can be accessed via hydrolib.core.io..models . File objects in Hydrolib-core reflect the same structure as the file contents. In this demo, we will load a Flow FM model, make some changes to the model and save it again. \ud83d\udca1 Tips for working in the Jupyter Notebook: Tab : Auto-complete on code Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell","title":"Deltares Software Days 2023: A simple hydrolib-core demo"},{"location":"tutorials/dsd_2023/demo/demo/#0-importing-the-modules-and-setting-the-path-variables","text":"In [ ]: Copied! from hydrolib.core.dflowfm import ( FMModel , Lateral , Weir , FlowDirection ) from pathlib import Path root = Path . cwd () demo_data_folder = root / \"data\" export_folder = root / \"export\" from hydrolib.core.dflowfm import ( FMModel, Lateral, Weir, FlowDirection ) from pathlib import Path root = Path.cwd() demo_data_folder = root / \"data\" export_folder = root / \"export\"","title":"0. Importing the modules and setting the path variables"},{"location":"tutorials/dsd_2023/demo/demo/#1-loading-a-flow-fm-model","text":"In [ ]: Copied! mdu_file_path = demo_data_folder / \"FlowFM.mdu\" model = FMModel ( filepath = mdu_file_path ) print ( f \"Loaded the model from { model . filepath } \" ) mdu_file_path = demo_data_folder / \"FlowFM.mdu\" model = FMModel(filepath=mdu_file_path) print(f\"Loaded the model from {model.filepath}\")","title":"1. Loading a Flow FM model"},{"location":"tutorials/dsd_2023/demo/demo/#2-inspecting-the-model","text":"We can see the hierarchy tree of the model by calling the following function: In [ ]: Copied! model . show_tree () model.show_tree() We can also inspect sub-parts of the model, like the structures. Note that a model can have multiple structure files, but this model only has one, so we will get the first and only one. In [ ]: Copied! assert model . geometry . structurefile is not None structure_file = model . geometry . structurefile [ 0 ] # Show the list of all the structures print ( f \"Number of structures: { len ( structure_file . structure ) } \" ) print ( structure_file . structure ) assert model.geometry.structurefile is not None structure_file = model.geometry.structurefile[0] # Show the list of all the structures print(f\"Number of structures: {len(structure_file.structure)}\") print(structure_file.structure)","title":"2. Inspecting the model"},{"location":"tutorials/dsd_2023/demo/demo/#3-adjusting-the-model","text":"","title":"3. Adjusting the model"},{"location":"tutorials/dsd_2023/demo/demo/#a-creating-a-new-weir-and-adding-it-to-the-structures","text":"In [ ]: Copied! # Create a new weir. weir = Weir ( id = \"DV_1471\" , branchId = \"458\" , chainage = 106.277467 , allowedFlowDir = FlowDirection . both , crestLevel = 0.400 , crestWidth = 40.000 , corrCoeff = 1.000 , useVelocityHeight = True ) # It is also possible to create objects with a dictionary. weir_data = { \"id\" : \"DV_1471\" , \"branchId\" : \"458\" , \"chainage\" : 106.277467 , \"allowedFlowDir\" : FlowDirection . both , \"crestLevel\" : 0.400 , \"crestWidth\" : 40.000 , \"corrCoeff\" : 1.000 , \"useVelocityHeight\" : True } weir = Weir ( ** weir_data ) # Add the weir to the model structure_file . structure . append ( weir ) print ( f \"Number of structures: { len ( structure_file . structure ) } \" ) # Create a new weir. weir = Weir( id=\"DV_1471\", branchId=\"458\", chainage=106.277467, allowedFlowDir=FlowDirection.both, crestLevel=0.400, crestWidth=40.000, corrCoeff=1.000, useVelocityHeight=True ) # It is also possible to create objects with a dictionary. weir_data = { \"id\": \"DV_1471\", \"branchId\": \"458\", \"chainage\": 106.277467, \"allowedFlowDir\": FlowDirection.both, \"crestLevel\": 0.400, \"crestWidth\": 40.000, \"corrCoeff\": 1.000, \"useVelocityHeight\": True } weir = Weir(**weir_data) # Add the weir to the model structure_file.structure.append(weir) print(f\"Number of structures: {len(structure_file.structure)}\")","title":"a. Creating a new weir and adding it to the structures**"},{"location":"tutorials/dsd_2023/demo/demo/#b-adjusting-some-parameters-of-the-model","text":"In [ ]: Copied! model . physics . backgroundsalinity = 30 # [ppt] model . physics . backgroundwatertemperature = 6 # [\u00b0C] model . time . dtuser = 900 # [s] model.physics.backgroundsalinity = 30 # [ppt] model.physics.backgroundwatertemperature = 6 # [\u00b0C] model.time.dtuser = 900 # [s] Hydrolib-core offers instant validation of objects that are created, either by loading them from file or by manually creating them. This makes it easier for users to create valid models. A lateral, like many other objects, should have a valid location specification, specified by: A node id, A branch id with a chainage, or Coordinates Let's create an invalid Lateral. We \"forget\" to specify a chainage. In [ ]: Copied! try : lateral = Lateral ( id = \"lateral_1\" , name = \"lateral_1\" , branchid = \"branch_a\" , discharge = \"realtime\" ) except ValueError as error : print ( error ) try: lateral = Lateral( id=\"lateral_1\", name=\"lateral_1\", branchid=\"branch_a\", discharge=\"realtime\" ) except ValueError as error: print(error) Now let's create a valid lateral. In [ ]: Copied! lateral = Lateral ( id = \"lateral_1\" , name = \"lateral_1\" , branchid = \"branch_a\" , chainage = 100 , discharge = \"realtime\" ) print ( \"Lateral with branch id and chainage is correct!\" ) lateral = Lateral( id=\"lateral_1\", name=\"lateral_1\", branchid=\"branch_a\", chainage=100, discharge=\"realtime\" ) print(\"Lateral with branch id and chainage is correct!\")","title":"b. Adjusting some parameters of the model"},{"location":"tutorials/dsd_2023/demo/demo/#5-saving-the-model","text":"If we save the model now, it will overwrite the current model files. So let's save it in a different location. In [ ]: Copied! print ( f \"The original model is located at { model . filepath } \" ) save_mdu_file_path = export_folder / \"save_model\" / \"FlowFM.mdu\" model . filepath = save_mdu_file_path # Set recurse to True. If it is False, only the MDU file will be saved. model . save ( recurse = True ) print ( f \"The saved model is located at { model . filepath } \" ) print(f\"The original model is located at {model.filepath}\") save_mdu_file_path = export_folder / \"save_model\" / \"FlowFM.mdu\" model.filepath = save_mdu_file_path # Set recurse to True. If it is False, only the MDU file will be saved. model.save(recurse=True) print(f\"The saved model is located at {model.filepath}\")","title":"5. Saving the model"},{"location":"tutorials/dsd_2023/demo/demo/#6-saving-only-a-sub-part-of-the-model","text":"It is also possible to save individual child model files, such as the cross section definition file. In [ ]: Copied! crossdef_file = model . geometry . crossdeffile assert crossdef_file is not None crossdef_file . filepath = export_folder / \"save_crossdef\" / \"crsdef.ini\" crossdef_file . save () print ( f \"The saved cross section definition model is located at { crossdef_file . filepath } \" ) crossdef_file = model.geometry.crossdeffile assert crossdef_file is not None crossdef_file.filepath = export_folder / \"save_crossdef\" / \"crsdef.ini\" crossdef_file.save() print(f\"The saved cross section definition model is located at {crossdef_file.filepath}\")","title":"6. 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When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(0, 0, 0, 1); --jp-content-font-color1: rgba(0, 0, 0, 0.87); --jp-content-font-color2: rgba(0, 0, 0, 0.54); --jp-content-font-color3: rgba(0, 0, 0, 0.38); --jp-content-link-color: var(--md-blue-700); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: white; --jp-layout-color1: white; --jp-layout-color2: var(--md-grey-200); --jp-layout-color3: var(--md-grey-400); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: #111111; --jp-inverse-layout-color1: var(--md-grey-900); --jp-inverse-layout-color2: var(--md-grey-800); --jp-inverse-layout-color3: var(--md-grey-700); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-900); --jp-brand-color1: var(--md-blue-700); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-900); --jp-accent-color1: var(--md-green-700); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-900); --jp-warn-color1: var(--md-orange-700); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-900); --jp-error-color1: var(--md-red-700); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-900); --jp-success-color1: var(--md-green-700); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-900); --jp-info-color1: var(--md-cyan-700); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--md-grey-100); --jp-cell-editor-border-color: var(--md-grey-300); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 0.5; --jp-cell-prompt-not-active-font-color: var(--md-grey-700); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: var(--md-blue-50); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: #fdd; --jp-rendermime-table-row-background: var(--md-grey-100); --jp-rendermime-table-row-hover-background: var(--md-light-blue-50); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.25); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color1); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.24); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--md-grey-300); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color1); --jp-input-hover-background: var(--jp-layout-color1); --jp-input-background: var(--md-grey-100); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: #d9d9d9; --jp-editor-selected-focused-background: #d7d4f0; --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: #008000; --jp-mirror-editor-atom-color: #88f; --jp-mirror-editor-number-color: #080; --jp-mirror-editor-def-color: #00f; --jp-mirror-editor-variable-color: var(--md-grey-900); --jp-mirror-editor-variable-2-color: #05a; --jp-mirror-editor-variable-3-color: #085; --jp-mirror-editor-punctuation-color: #05a; --jp-mirror-editor-property-color: #05a; --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ba2121; --jp-mirror-editor-string-2-color: #708; --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: #008000; --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: #170; --jp-mirror-editor-attribute-color: #00c; --jp-mirror-editor-header-color: blue; --jp-mirror-editor-quote-color: #090; --jp-mirror-editor-link-color: #00c; --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: white; /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.5; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(245, 200, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } [data-md-color-scheme=\"slate\"] .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ /* The dark theme shadows need a bit of work, but this will probably also require work on the core layout * colors used in the theme as well. */ --jp-shadow-base-lightness: 32; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-700); --jp-border-color1: var(--md-grey-700); --jp-border-color2: var(--md-grey-800); --jp-border-color3: var(--md-grey-900); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(255, 255, 255, 1); --jp-ui-font-color1: rgba(255, 255, 255, 0.87); --jp-ui-font-color2: rgba(255, 255, 255, 0.54); --jp-ui-font-color3: rgba(255, 255, 255, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(0, 0, 0, 1); --jp-ui-inverse-font-color1: rgba(0, 0, 0, 0.8); --jp-ui-inverse-font-color2: rgba(0, 0, 0, 0.5); --jp-ui-inverse-font-color3: rgba(0, 0, 0, 0.3); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(255, 255, 255, 1); --jp-content-font-color1: rgba(255, 255, 255, 1); --jp-content-font-color2: rgba(255, 255, 255, 0.7); --jp-content-font-color3: rgba(255, 255, 255, 0.5); --jp-content-link-color: var(--md-blue-300); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: #111111; --jp-layout-color1: var(--md-grey-900); --jp-layout-color2: var(--md-grey-800); --jp-layout-color3: var(--md-grey-700); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: white; --jp-inverse-layout-color1: white; --jp-inverse-layout-color2: var(--md-grey-200); --jp-inverse-layout-color3: var(--md-grey-400); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-700); --jp-brand-color1: var(--md-blue-500); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-700); --jp-accent-color1: var(--md-green-500); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-700); --jp-warn-color1: var(--md-orange-500); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-700); --jp-error-color1: var(--md-red-500); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-700); --jp-success-color1: var(--md-green-500); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-700); --jp-info-color1: var(--md-cyan-500); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--jp-layout-color1); --jp-cell-editor-border-color: var(--md-grey-700); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 1; --jp-cell-prompt-not-active-font-color: var(--md-grey-300); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: rgba(33, 150, 243, 0.24); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: rgba(244, 67, 54, 0.28); --jp-rendermime-table-row-background: var(--md-grey-900); --jp-rendermime-table-row-hover-background: rgba(3, 169, 244, 0.2); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.6); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color2); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.8); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--jp-layout-color0); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color0); --jp-input-hover-background: var(--jp-layout-color2); --jp-input-background: var(--md-grey-800); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: var(--jp-layout-color2); --jp-editor-selected-focused-background: rgba(33, 150, 243, 0.24); --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: var(--md-green-500); --jp-mirror-editor-atom-color: var(--md-blue-300); --jp-mirror-editor-number-color: var(--md-green-400); --jp-mirror-editor-def-color: var(--md-blue-600); --jp-mirror-editor-variable-color: var(--md-grey-300); --jp-mirror-editor-variable-2-color: var(--md-blue-400); --jp-mirror-editor-variable-3-color: var(--md-green-600); --jp-mirror-editor-punctuation-color: var(--md-blue-400); --jp-mirror-editor-property-color: var(--md-blue-400); --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ff7070; --jp-mirror-editor-string-2-color: var(--md-purple-300); --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: var(--md-green-600); --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: var(--md-green-700); --jp-mirror-editor-attribute-color: var(--md-blue-700); --jp-mirror-editor-header-color: var(--md-blue-500); --jp-mirror-editor-quote-color: var(--md-green-300); --jp-mirror-editor-link-color: var(--md-blue-700); --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: var(--md-grey-400); /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.6; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(255, 225, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* scrollbar related styles. Supports every browser except Edge. */ /* colors based on JetBrain's Darcula theme */ --jp-scrollbar-background-color: #3f4244; --jp-scrollbar-thumb-color: 88, 96, 97; /* need to specify thumb color as an RGB triplet */ --jp-scrollbar-endpad: 3px; /* the minimum gap between the thumb and the ends of a scrollbar */ /* hacks for setting the thumb shape. 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sourceMappingURL=mkdocs-jupyter.css.map*/ init_mathjax = function() { if (window.MathJax) { // MathJax loaded MathJax.Hub.Config({ TeX: { equationNumbers: { autoNumber: \"AMS\", useLabelIds: true } }, tex2jax: { inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ], displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ], processEscapes: true, processEnvironments: true }, displayAlign: 'center', CommonHTML: { linebreaks: { automatic: true } } }); MathJax.Hub.Queue([\"Typeset\", MathJax.Hub]); } } init_mathjax(); Creating a Delft3D FM 1D2D fluvial flood model of Magdalena river \u00b6 The exercises in this notebook will serve as introduction on how to use HYDROLIB-core functionalities. We will create and adjust a Delft3D FM Suite 1D2D fluvial flood model of the Magdalena river in Columbia. First a 1D river model of the Magdalena river and Canal del Dique will be created, shown in the left figure. This model will be extended with a 2D Flexible Mesh, with a uniform roughness field. Adding a Digital Terrain Model (DTM) on that 2D mesh is currently not part of this tutorial, but in practice this is indispensible to mimic the fluvial flood patterns. Note that the model that will be created is for educational purposes and consists partially of fictive or unvalidated model data. Using HYDROLIB-core to build models \u00b6 HYDROLIB-core is a Python package that offers functionality to process D-HYDRO input files. It offers Python-wrapped classes that represent these files and their content. HYDROLIB-core serves as the basis for various pre- and postprocessing tools for a modelling workflow of hydrodynamic simulations in D-HYDRO. It can easily be used to build models and export the model files that can aftewards be run by dflowfm or other supported D-HYDRO kernels. Content of the tutorial \u00b6 The goal of this tutorial is to familiarize modelers with applying HYDROLIB-core functionalities in their modelling procedures for building new models or adjusting existing models. As mentioned above, you will create an 1D2D fluvial flood model from scratch using the D-Flow FM HYDROLIB-core functionalities and the underlying functions from mesh generation ( MeshKernelPy ). We will walk through the following steps to build the model: Selecting the data location Creating an empty D-Flow FM model Reading the branch data from a shape file Creating and assigning a 1D computational grid to the model Adding cross-sections to the branches Adding cross-section definitions Adding roughness to the model Adding boundary conditions to the model Adding initial water depths Adding a weir to a branch Finishing up and saving the model Creating a 2D flexible mesh Refining the 2D grid locally Saving the 1D2D model \ud83d\udca1 Tips for working in the Jupyter Notebook \u00b6 Tab : Auto-complete on code Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell Import the needed modules \u00b6 Several Python packages are required to run the notebook. These packages are imported below. Please consult the HYDROLIB-core documentation if you want to use additional HYDROLIB-core functionalities later. In [ ]: Copied! # General import geopandas as gpd import matplotlib.pyplot as plt import numpy as np import pandas as pd from pathlib import Path # MeshKernel import meshkernel as mk from meshkernel import GeometryList , MakeGridParameters # HYDROLIB-core from hydrolib.core.dflowfm.mdu import FMModel , AutoStartOption from hydrolib.core.dflowfm.net.models import * from hydrolib.core.dflowfm.crosssection.models import CrossLocModel , CrossDefModel , YZCrsDef from hydrolib.core.dflowfm.friction.models import * from hydrolib.core.dflowfm.bc.models import * from hydrolib.core.dflowfm.ext.models import * from hydrolib.core.dflowfm.inifield.models import * from hydrolib.core.dflowfm.onedfield.models import * from hydrolib.core.dflowfm.structure.models import Weir , FlowDirection , StructureModel print ( \"Imports were successful!\" ) # General import geopandas as gpd import matplotlib.pyplot as plt import numpy as np import pandas as pd from pathlib import Path # MeshKernel import meshkernel as mk from meshkernel import GeometryList, MakeGridParameters # HYDROLIB-core from hydrolib.core.dflowfm.mdu import FMModel, AutoStartOption from hydrolib.core.dflowfm.net.models import * from hydrolib.core.dflowfm.crosssection.models import CrossLocModel, CrossDefModel, YZCrsDef from hydrolib.core.dflowfm.friction.models import * from hydrolib.core.dflowfm.bc.models import * from hydrolib.core.dflowfm.ext.models import * from hydrolib.core.dflowfm.inifield.models import * from hydrolib.core.dflowfm.onedfield.models import * from hydrolib.core.dflowfm.structure.models import Weir, FlowDirection, StructureModel print(\"Imports were successful!\") Here starts the tutorial \u00b6 1. Selecting the data location \u00b6 Exercise \ud83e\udde9: Create a variable that contains the Path to the data folder. In [ ]: Copied! data_dir = ... print ( f \"Data location: { data_dir } \" ) data_dir = ... print(f\"Data location: {data_dir}\") 2. Creating an empty D-Flow FM model \u00b6 To start a model from scratch, you first need to create an empty model without data. In this tutorial we will create a D-Flow FM model. The MDU file (master definition file) is the main input file of the D-Flow FM model. A new D-Flow FM model is constructed with the FMModel initializer. Exercise \ud83e\udde9 Create a variable containing a new FMModel object. Create a variable containing the export directory Export the D-Flow FM model to an MDU file inside the export directory API references: FMModel FileModel.filepath FileModel.save() In [ ]: Copied! model = ... export_dir = ... model . filepath = ... # Save the MDU file ... print ( f \"MDU file saved: { model . filepath } \" ) model = ... export_dir = ... model.filepath = ... # Save the MDU file ... print(f\"MDU file saved: {model.filepath}\") Part 1: Setting up a 1D Delft3D FM model \u00b6 In this part we will build up the complete 1D model schematization step by step. At the end you should have a complete set of model input files for a 1D calculation. 3. Reading the branch data from a shape file \u00b6 The model will include the lower part of the Magadalena from Cordoba Teton to the river mouth Baranquilla and the Canal del Dique. Exercise \ud83e\udde9 Read the branch data from the branches_Branches.shp file Print the branch data, such that we can answer the following questions: How many river branches does the model have? What are their names? Which friction type and friction value is used for each branch? API references: gpd.read_file In [ ]: Copied! # Read the branches ... # Print the data ... # Answers: # * ... # * ... # * ... # Read the branches ... # Print the data ... # Answers: # * ... # * ... # * ... 4. Creating and assigning a 1D computational grid to the model \u00b6 In the previous step we read the geometry and attributes of the branches from the shape file. This branch data will become the network input for our D-Flow FM model. Since the model does not have a network yet, we need to create a new network object and assign it to the model. A network may contain a 1D network, a 2D mesh and 1D2D links. Exercise \ud83e\udde9 Create a new network Assign the network to the model and assign a (relative) file path for the net file The new network should contain the data that we read from the shape file: Three Branch objects will need to be added to the network. For each branch, the name, geometry and computational grid points should be provided. The computational points are not included in the data, we will need to generate those with a grid point distance as specified: Branch name dx [m] Channel_1D_1_A 1000 Channel_1D_1_B 1000 Channel_1D_1 500 Hint \ud83d\udca1: The MDU file contains a [Geometry] section which has the network file reference, e.g.: [Geometry] netFile = FlowFM_net.nc ... API references: Network NetworkModel Branch Branch.generate_nodes() Network.mesh1d_add_branch() (undocumented): Adds a branch to the 1D network. The function needs two arguments: Branch : the branch to be added str : The name of the branch that is added In [ ]: Copied! # Assign a new network to the D-Flow FM model and specify the file path network = ... # Specify 1D computational grid point distance per branch dx_per_branch = { \"Channel_1D_1_A\" : 1000 , \"Channel_1D_1_B\" : 1000 , \"Channel_1D_1\" : 500 , } # Assign geometry of the branches and generate the computational grid on top of the branches. # Add each branch to the network for index , branch_data in branches_gdf . iterrows (): branch_geometry = np . transpose ( branch_data . geometry . xy ) ... network . _mesh1d . _set_mesh1d () # Assign a new network to the D-Flow FM model and specify the file path network = ... # Specify 1D computational grid point distance per branch dx_per_branch = { \"Channel_1D_1_A\" : 1000, \"Channel_1D_1_B\" : 1000, \"Channel_1D_1\" : 500, } # Assign geometry of the branches and generate the computational grid on top of the branches. # Add each branch to the network for index, branch_data in branches_gdf.iterrows(): branch_geometry = np.transpose(branch_data.geometry.xy) ... network._mesh1d._set_mesh1d() We can plot the branches onto a background: In [ ]: Copied! # Create a figure with the 1D network figure , axis = plt . subplots ( ncols = 1 ) img = plt . imread ( data_dir / \"osm_background.png\" ) # Add branch names to the plot for branch_name , branch in network . _mesh1d . branches . items (): middle = int (( len ( branch . geometry ) - 1 ) / 2 ) xy = branch . geometry [ middle ] axis . text ( xy [ 0 ], xy [ 1 ], branch_name , ha = 'center' ) axis . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) network . _mesh1d . _get_mesh1d () . plot_edges ( ax = axis , color = 'blue' ) # Create a figure with the 1D network figure, axis = plt.subplots(ncols=1) img = plt.imread(data_dir / \"osm_background.png\") # Add branch names to the plot for branch_name, branch in network._mesh1d.branches.items(): middle = int((len(branch.geometry) - 1)/2) xy = branch.geometry[middle] axis.text(xy[0], xy[1], branch_name, ha='center') axis.imshow(img, extent=[440000, 531544.97964175534434617, 1057000, 1228644.01383191486820579]) network._mesh1d._get_mesh1d().plot_edges(ax=axis, color='blue') 5. Adding cross-sections to the branches \u00b6 In order to determine the flow area of the 1D model during the computation, you need cross-sections. These cross-sections are defined by two components: Cross-section locations Cross-section definitions The cross-section locations and cross-section definitions are exported to their own file. A cross-section location is defined by the following information: The cross-section ID A location, specified by a branch ID and a chainage. A shift, the vertical shift of the cross section profile. This is mainly used to create a good longitudinal slope over the 1D model (in case of shared cross-sections). A reference to the cross-section definition that is used at this location.

    A cross-section definition is defined by the following information: The cross-section definition ID The cross-section type: circle, rectangle, ZW river, ZW, YZ, XYZ Depending on the type of cross-section, a set of properties describing the properties of the profile shape

    In our data folder, there is a CSV file containing the cross-section locations. We want to convert this data to HYDROLIB-core cross-section location objects and add them to the D-Flow FM model. The columns in the CSV correspond exactly with the field names of a CrossSection class, making the conversion easy. Exercise \ud83e\udde9 Read the data from the CSV file Print the cross-section location data, to answer the following questions: How many cross-section does the model contain in total, and how many does each branch have? Do the cross-section have shared cross-section definitions? A shared cross-section definition is a definition used by more than one cross-section. Convert the CSV data (a pd.DataFrame) into HYDROLIB-core CrossSection objects Assign the cross section locations to the model Hint \ud83d\udca1: The MDU file contains a [Geometry] section which has the crossDefFile and crossLocFile reference, e.g.: [Geometry] crossDefFile = crsdef.ini crossLocFile = crsloc.ini ... API references: pd.read_csv() pd.to_dict() CrossLocModel CrossSection In [ ]: Copied! # Read the cross-sections from the CSV cross_section_data_file = ... cross_section_df = ... # Print the data ... # Answers: # * ... # * ... # Assign the data to the model ... # Read the cross-sections from the CSV cross_section_data_file = ... cross_section_df = ... # Print the data ... # Answers: # * ... # * ... # Assign the data to the model ... 6. Adding cross-section definitions \u00b6 In the following exercise we will add the cross-section definitions to the D-Flow FM model. These belong to the cross-sections we added in the previous step. These cross-sections all have YZ-profiles in order to define a natural shape of the river. Please finish the code below. Exercise \ud83e\udde9 Create a new cross-section definition model with the defined properties Create an YZ profile for each profile from the excel file Append each YZ profile to the cross-section definition model Make sure the data is assigned to the D-Flow FM model API references: CrossDefModel YZCrsDef In [ ]: Copied! profiles_file = data_dir / '1D_YZ_CrossSections.xlsx' profile_excel_data = pd . read_excel ( profiles_file , sheet_name = None ) profile_names = list ( profile_excel_data ) print ( f \"Profile names: { profile_names } \" ) # Create a new cross-section definition model and assign to the model ... # Properties for each YZ profile type_crs = 'yz' thalweg = 0.0 single_valued_z = 'yes' conveyance = 'segmented' sectionCount = 1 friction_ids = 'channels' # Create the YZ profiles and append them to the CrossDefModel for profile_name in profile_names : profile_data = profile_excel_data [ profile_name ] num_coords = len ( profile_data . values ) y_coords = profile_data . y . to_list () z_coords = profile_data . z . to_list () # Define friction positions at begin and end of profile friction_positions = [ profile_data . y [ 0 ], profile_data . y [ num_coords - 1 ]] # Create an YZ profile and add it to the cross-section definition model ... profiles_file = data_dir / '1D_YZ_CrossSections.xlsx' profile_excel_data = pd.read_excel(profiles_file, sheet_name=None) profile_names = list(profile_excel_data) print(f\"Profile names: {profile_names}\") # Create a new cross-section definition model and assign to the model ... # Properties for each YZ profile type_crs = 'yz' thalweg = 0.0 single_valued_z = 'yes' conveyance = 'segmented' sectionCount = 1 friction_ids = 'channels' # Create the YZ profiles and append them to the CrossDefModel for profile_name in profile_names: profile_data = profile_excel_data[profile_name] num_coords = len(profile_data.values) y_coords = profile_data.y.to_list() z_coords = profile_data.z.to_list() # Define friction positions at begin and end of profile friction_positions = [profile_data.y[0], profile_data.y[num_coords-1]] # Create an YZ profile and add it to the cross-section definition model ... 7. Adding roughness to the model \u00b6 Our 1D D-Flow FM model now has a network topology, computational grid points and cross-sections. Friction is a component that should be added to the model to get the proper bed roughness and channel conveyance. For each branch, we will add a friction type and value at the upstream location. We will also specify a global roughness section. This will be used when there is no friction defined for a branch. It also contains a friction ID. In the cross-section definitions we created above, a reference is made to this friction ID (='channels'). YZ profiles can refer to multiple friction IDs, since the friction can vary within the cross-section. This also means that multiple friction definition files can be added to one D-Flow FM model. In [ ]: Copied! channel_friction_id = 'channels' channel_global_type = FrictionType . manning channel_global_value = 0.023 channel_friction_model = FrictionModel () channel_friction_model . filepath = \"roughness-channels.ini\" # It is conventional to specify the file names as \"roughness-[friction ID].ini\" model . geometry . frictfile = [ channel_friction_model ] # Create global friction model and add it to frictionmodel channel_global_friction = FrictGlobal ( frictionId = channel_friction_id , frictionType = channel_global_type , frictionValue = channel_global_value ) channel_friction_model . global_ = channel_global_friction function_type = 'constant' # Create friction definition per branch for index , branch_data in branches_gdf . iterrows (): friction_per_branch = FrictBranch ( branchId = branch_data . Name , frictionType = branch_data . fric_type , frictionValues = [ branch_data . fric_value ], chainage = [ branch_data . chainage ], numLocations = 1 , functionType = function_type ) channel_friction_model . branch . append ( friction_per_branch ) channel_friction_id = 'channels' channel_global_type = FrictionType.manning channel_global_value = 0.023 channel_friction_model = FrictionModel() channel_friction_model.filepath = \"roughness-channels.ini\" # It is conventional to specify the file names as \"roughness-[friction ID].ini\" model.geometry.frictfile = [channel_friction_model] # Create global friction model and add it to frictionmodel channel_global_friction = FrictGlobal(frictionId=channel_friction_id, frictionType=channel_global_type, frictionValue=channel_global_value) channel_friction_model.global_ = channel_global_friction function_type = 'constant' # Create friction definition per branch for index, branch_data in branches_gdf.iterrows(): friction_per_branch = FrictBranch(branchId=branch_data.Name, frictionType=branch_data.fric_type, frictionValues=[branch_data.fric_value], chainage=[branch_data.chainage], numLocations=1, functionType=function_type) channel_friction_model.branch.append(friction_per_branch) We want to define another global friction definition for the Canal del Dique. This friction model assumes Chezy as global friction type and a friction value of 45.0. You can use the code above as an example. Exercise \ud83e\udde9 Create a new friction model for Canal del Dique Specify a global friction definition Make sure the new friction model is added to the D-Flow FM model API references: FrictionType FrictionModel FrictGlobal In [ ]: Copied! ... ... The cross-sections on the Canal del Dique (Channel_1D_1) do not refer to this new friction ID yet. Exercise \ud83e\udde9 Use the cross-section locations and definitions in the D-Flow FM model to find the cross-sections on the Channel_1D_1 branch Reassign the friction ID of the correct cross sections to the one used for the Canal del Dique In [ ]: Copied! ... ... 8. Adding boundary conditions to the model \u00b6 Fluvial floods occur when water levels in the river are too high. These high water levels in the rivers can result from several factors. One of those is the occurence of heavy rainfall in the upstream catchment. These heavy rainstorms can lead to a high discharge wave entering the upstream boundary of the river. In order to apply boundary conditions on a model you need data from two files: External forcing file (*.ext) : specifies the location and type of forcing. Boundary conditions file (*.bc) : contains the forcing values, e.g. a time series or a constant value In this tutorial you will model such a high discharge wave (time series) at the upstream 1D boundary. For the two downstream boundaries a constant water level of 0 m AD is assumed. Note that this are tidal boundaries in reality. Exercise \ud83e\udde9 Complete the code below by adding the boundary locations to the external forcing model. For each boundary location (3), the correct boundary object should be created with a quantity, node ID and forcing file. The quantity keys for discharge and water level are 'dischargebnd' and 'waterlevelbnd', respectively. API references: Boundary In [ ]: Copied! ext_model = ExtModel () # External forcing file (.ext) bc_model = ForcingModel () # Boundary conditions file (.bc) model . external_forcing . extforcefilenew = ext_model # Read the upstream boundary time series from excel discharge_file = data_dir / '1D_BoundaryConditions.xlsx' discharge_excel_df = pd . read_excel ( discharge_file , sheet_name = [ 0 ]) node_ids = model . geometry . netfile . network . _mesh1d . network1d_node_id print ( node_ids ) node_upstream = node_ids [ 0 ] # time series discharge node nodes_downstream = node_ids [ 2 :] # constant water level nodes # Create the discharge timeseries bc_upstream = TimeSeries ( name = node_upstream , nodeid = node_upstream , timeinterpolation = TimeInterpolation . linear , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2012-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], datablock = [[ time , dis ] for [ time , dis ] in discharge_excel_df [ 0 ] . values ]) bc_model . forcing . append ( bc_upstream ) # Create the constant water level for node_downstream in nodes_downstream : bc_downstream = Constant ( name = node_downstream , nodeid = node_downstream , quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], datablock = [[ \"0.0\" ]]) bc_model . forcing . append ( bc_downstream ) # Create the boundary locations for the discharge and the water level ... ext_model = ExtModel() # External forcing file (.ext) bc_model = ForcingModel() # Boundary conditions file (.bc) model.external_forcing.extforcefilenew = ext_model # Read the upstream boundary time series from excel discharge_file = data_dir / '1D_BoundaryConditions.xlsx' discharge_excel_df = pd.read_excel(discharge_file, sheet_name=[0]) node_ids = model.geometry.netfile.network._mesh1d.network1d_node_id print(node_ids) node_upstream = node_ids[0] # time series discharge node nodes_downstream = node_ids[2:] # constant water level nodes # Create the discharge timeseries bc_upstream = TimeSeries( name = node_upstream, nodeid = node_upstream, timeinterpolation = TimeInterpolation.linear, quantityunitpair = [QuantityUnitPair(quantity = 'time', unit = 'minutes since 2012-01-01 00:00:00'), QuantityUnitPair(quantity = 'dischargebnd', unit = 'm\u00b3/s')], datablock = [[time, dis] for [time,dis] in discharge_excel_df[0].values]) bc_model.forcing.append(bc_upstream) # Create the constant water level for node_downstream in nodes_downstream: bc_downstream = Constant( name = node_downstream, nodeid = node_downstream, quantityunitpair = [QuantityUnitPair(quantity = 'waterlevelbnd', unit = 'm')], datablock = [[\"0.0\"]]) bc_model.forcing.append(bc_downstream) # Create the boundary locations for the discharge and the water level ... 9. Adding initial water depths \u00b6 For this model an initial water depth of 1.0 meter is assumed in the 1D model. Below we add an initial water depth to the model with the following steps: Creating global 1D initial conditions field, containing an initial water depth of 1.0. Note that it is also possible to define the initial water depth per branch. Creating an initial field file containing the initial water depth data for our 1D network In [ ]: Copied! # Create 1D initial conditions field file ini_1d = OneDFieldModel () ini_1d . global_ = OneDFieldGlobal ( quantity = 'waterdepth' , unit = 'm' , value = 1.0 ) ini_1d . filepath = 'initialwaterdepth.ini' ini_1d . save ( export_dir / ini_1d . filepath ) # 1D field ini files needs to be saved seperately, because it is not completely supported yet) # Create initial field file ini_field_model = IniFieldModel () ini_field_model . filepath = 'inifield.ini' ini_field_model . initial = InitialField ( quantity = 'waterdepth' , datafile = ini_1d . filepath , datafiletype = DataFileType . onedfield ) # Assign data to the model model . geometry . inifieldfile = ini_field_model # Create 1D initial conditions field file ini_1d = OneDFieldModel() ini_1d.global_ = OneDFieldGlobal(quantity='waterdepth', unit='m', value=1.0) ini_1d.filepath = 'initialwaterdepth.ini' ini_1d.save(export_dir / ini_1d.filepath) # 1D field ini files needs to be saved seperately, because it is not completely supported yet) # Create initial field file ini_field_model = IniFieldModel() ini_field_model.filepath = 'inifield.ini' ini_field_model.initial = InitialField(quantity='waterdepth',datafile=ini_1d.filepath, datafiletype=DataFileType.onedfield) # Assign data to the model model.geometry.inifieldfile = ini_field_model 10. Adding a weir to a branch \u00b6 Many lakes occur close along Canal del Dique. See figure below. This tutorial assumes that these lakes can function as extra storage for the floods from the river. Hence a weir structure, functioning as a small dam, is added downstream of the lakes. This weir structure has the following conditions: It is located at 70 km from the upstream node of the branch (Channel_1D_1). The crest level is 4.0 m AD. The crest width is 105.0 m. The flow over the dam is in both directions.

    Exercise \ud83e\udde9 Create a new weir object with the described properties Create a new structure model and add the new weir to it Assign the data to the D-Flow FM model In [ ]: Copied! # Create weir structure weir = ... # Create structure model ... # Append weir to structure ... # Assign structure model to D-Flow FM model ... # Create weir structure weir = ... # Create structure model ... # Append weir to structure ... # Assign structure model to D-Flow FM model ... After creating the weir, you want to adjust some values. You found out that the dam should be significantly higher. Exercise \ud83e\udde9 Increase the crest level to 10.0 Change the flow direction to positive (from upstream to downstream) In [ ]: Copied! ... ... 11. Finishing up and saving the model \u00b6 The 1D model is almost finished now. We first change some time settings and then save the model. Exercise \ud83e\udde9 Export the full model to the export folder API references: FileModel.save() In [ ]: Copied! # Change some time settings model . time . refdate = '20120101' model . time . dtuser = 60. # seconds model . time . tstart = 43200. model . time . tstop = 561600. # Save the model ... # Change some time settings model.time.refdate = '20120101' model.time.dtuser = 60. # seconds model.time.tstart = 43200. model.time.tstop = 561600. # Save the model ... Part 2: Extending the 1D model to a 1D2D model \u00b6 We will now continue with the 1D model and add a 2D mesh to it. We won't add 1D2D coupling, but in practice they should be added to create a true 1D2D model. 12. Creating a 2D flexible mesh \u00b6 Here, we demonstrate how to create a 2D mesh using MeshKernel. \u26a0\ufe0f Network and mesh functionality in HYDROLIB-core is still in development. We use a shape file with the area of interest to define the extent of the new 2D mesh that is to be generated. First, a uniform rectilinear mesh with a grid cell size of 2500x2500m is generated. Second, we clip the generated mesh. API references: Mesh2d Mesh2d.clip() mk.MakeGridParameters In [ ]: Copied! # Read grid outline gdf_grid = gpd . read_file ( data_dir / 'outline_2D_grid.shp' ) # Determine the boundary box xmin , ymin , xmax , ymax = gdf_grid . geometry [ 0 ] . bounds mesh2d = Mesh2d () mesh_kernel = mesh2d . meshkernel # Define the grid generation parameters dx = 2500.0 dy = 2500.0 num_rows = int (( ymax - ymin ) / dy ) num_columns = int (( xmax - xmin ) / dx ) origin_x = xmin origin_y = ymin block_size_x = dx block_size_y = dy make_grid_parameters = MakeGridParameters () make_grid_parameters . num_columns = num_columns make_grid_parameters . num_rows = num_rows make_grid_parameters . origin_x = origin_x make_grid_parameters . origin_y = origin_y make_grid_parameters . block_size_x = dx make_grid_parameters . block_size_y = dy make_grid_parameters . upper_right_x = xmax make_grid_parameters . upper_right_y = ymax # Create uniform rectilinear mesh mesh_kernel . curvilinear_make_uniform ( make_grid_parameters ) mesh_kernel . curvilinear_convert_to_mesh2d () mesh2d . _process ( mesh2d . get_mesh2d ()) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np . array ( gdf_grid . geometry [ 0 ] . exterior . xy ) clip_geometry_list = GeometryList ( clip_polygon [ 0 ], clip_polygon [ 1 ]) mesh2d . clip ( clip_geometry_list ) model . geometry . netfile . network . _mesh2d = mesh2d model . geometry . netfile . filepath = \"FlowFM_1D2D_net.nc\" # Read grid outline gdf_grid = gpd.read_file(data_dir / 'outline_2D_grid.shp') # Determine the boundary box xmin, ymin, xmax, ymax = gdf_grid.geometry[0].bounds mesh2d = Mesh2d() mesh_kernel = mesh2d.meshkernel # Define the grid generation parameters dx=2500.0 dy=2500.0 num_rows = int((ymax - ymin) / dy) num_columns = int((xmax - xmin) / dx) origin_x = xmin origin_y = ymin block_size_x = dx block_size_y = dy make_grid_parameters = MakeGridParameters() make_grid_parameters.num_columns = num_columns make_grid_parameters.num_rows = num_rows make_grid_parameters.origin_x = origin_x make_grid_parameters.origin_y = origin_y make_grid_parameters.block_size_x = dx make_grid_parameters.block_size_y = dy make_grid_parameters.upper_right_x = xmax make_grid_parameters.upper_right_y = ymax # Create uniform rectilinear mesh mesh_kernel.curvilinear_make_uniform(make_grid_parameters) mesh_kernel.curvilinear_convert_to_mesh2d() mesh2d._process(mesh2d.get_mesh2d()) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np.array(gdf_grid.geometry[0].exterior.xy) clip_geometry_list = GeometryList(clip_polygon[0],clip_polygon[1]) mesh2d.clip(clip_geometry_list) model.geometry.netfile.network._mesh2d = mesh2d model.geometry.netfile.filepath = \"FlowFM_1D2D_net.nc\" The cell below produces a basic plot of the 1D2D network. In [ ]: Copied! # Create a plot mesh2d_mk = network . _mesh2d . get_mesh2d () mesh1d_mk = network . _mesh1d . _get_mesh1d () figure , axis = plt . subplots () axis . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) mesh2d_mk . plot_edges ( ax = axis , color = \"orange\" ) mesh1d_mk . plot_edges ( ax = axis , color = 'blue' ) # Create a plot mesh2d_mk = network._mesh2d.get_mesh2d() mesh1d_mk = network._mesh1d._get_mesh1d() figure, axis = plt.subplots() axis.imshow(img, extent=[440000, 531544.97964175534434617, 1057000, 1228644.01383191486820579]) mesh2d_mk.plot_edges(ax=axis, color=\"orange\") mesh1d_mk.plot_edges(ax=axis, color='blue') 13. Refining the 2D grid locally \u00b6 Here, we want to refine the 2D mesh around the river using MeshKernel functionality. We will do one refinement iteration. Exercise \ud83e\udde9 Refine the 2D mesh using MeshKernel with the provided refinment parameters (see code below) API references: mk.MeshRefinementParameters mk.mesh2d_refine_based_on_polygon() (not documented yet): First argument is a GeometryList containing the polygon geometry of the area to refine Second argument is a MeshRefinementParameters containing all the parameters for refining In [ ]: Copied! # Get the refinement polygon to refine around the river gdf_refine = gpd . read_file ( data_dir / 'buffer_around_river_proj.shp' ) refine_polygon = np . array ( gdf_refine . geometry [ 0 ] . exterior . xy ) refine_geom = GeometryList ( refine_polygon [ 0 ], refine_polygon [ 1 ]) # Set parameters refine_intersected = True use_mass_center_when_refining = False min_edge_size = 10.0 refinement_type = 1 connect_hanging_nodes = True account_for_samples_outside_face = False max_refinement_iterations = 1 # Refine the 2D mesh ... # Set 2D mesh on model mesh2d . _process ( mesh2d . get_mesh2d ()) model . geometry . netfile . network . _mesh2d = mesh2d model . geometry . netfile . filepath = \"FlowFM_1D2D_refined_net.nc\" # Get the refinement polygon to refine around the river gdf_refine = gpd.read_file(data_dir / 'buffer_around_river_proj.shp') refine_polygon = np.array(gdf_refine.geometry[0].exterior.xy) refine_geom = GeometryList(refine_polygon[0], refine_polygon[1]) # Set parameters refine_intersected = True use_mass_center_when_refining = False min_edge_size = 10.0 refinement_type = 1 connect_hanging_nodes = True account_for_samples_outside_face = False max_refinement_iterations = 1 # Refine the 2D mesh ... # Set 2D mesh on model mesh2d._process(mesh2d.get_mesh2d()) model.geometry.netfile.network._mesh2d = mesh2d model.geometry.netfile.filepath = \"FlowFM_1D2D_refined_net.nc\" In [ ]: Copied! # Create a plot mesh2d_mk = network . _mesh2d . get_mesh2d () mesh1d_mk = network . _mesh1d . _get_mesh1d () figure , axis = plt . subplots () axis . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) mesh2d_mk . plot_edges ( ax = axis , color = \"orange\" ) mesh1d_mk . plot_edges ( ax = axis , color = 'blue' ) # Create a plot mesh2d_mk = network._mesh2d.get_mesh2d() mesh1d_mk = network._mesh1d._get_mesh1d() figure, axis = plt.subplots() axis.imshow(img, extent=[440000, 531544.97964175534434617, 1057000, 1228644.01383191486820579]) mesh2d_mk.plot_edges(ax=axis, color=\"orange\") mesh1d_mk.plot_edges(ax=axis, color='blue') 14. Saving the 1D2D model \u00b6 The 1D2D model is now finished. Exercise \ud83e\udde9 Save the model wherever you like Import the D-Flow FM model in the Delft3D FM Suite 1D2D In [ ]: Copied! model . save ( recurse = True ) model.save(recurse=True)","title":"Creating a Delft3D FM 1D2D fluvial flood model of Magdalena river"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#creating-a-delft3d-fm-1d2d-fluvial-flood-model-of-magdalena-river","text":"The exercises in this notebook will serve as introduction on how to use HYDROLIB-core functionalities. We will create and adjust a Delft3D FM Suite 1D2D fluvial flood model of the Magdalena river in Columbia. First a 1D river model of the Magdalena river and Canal del Dique will be created, shown in the left figure. This model will be extended with a 2D Flexible Mesh, with a uniform roughness field. Adding a Digital Terrain Model (DTM) on that 2D mesh is currently not part of this tutorial, but in practice this is indispensible to mimic the fluvial flood patterns. Note that the model that will be created is for educational purposes and consists partially of fictive or unvalidated model data.","title":"Creating a Delft3D FM 1D2D fluvial flood model of Magdalena river"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#using-hydrolib-core-to-build-models","text":"HYDROLIB-core is a Python package that offers functionality to process D-HYDRO input files. It offers Python-wrapped classes that represent these files and their content. HYDROLIB-core serves as the basis for various pre- and postprocessing tools for a modelling workflow of hydrodynamic simulations in D-HYDRO. It can easily be used to build models and export the model files that can aftewards be run by dflowfm or other supported D-HYDRO kernels.","title":"Using HYDROLIB-core to build models"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#content-of-the-tutorial","text":"The goal of this tutorial is to familiarize modelers with applying HYDROLIB-core functionalities in their modelling procedures for building new models or adjusting existing models. As mentioned above, you will create an 1D2D fluvial flood model from scratch using the D-Flow FM HYDROLIB-core functionalities and the underlying functions from mesh generation ( MeshKernelPy ). We will walk through the following steps to build the model: Selecting the data location Creating an empty D-Flow FM model Reading the branch data from a shape file Creating and assigning a 1D computational grid to the model Adding cross-sections to the branches Adding cross-section definitions Adding roughness to the model Adding boundary conditions to the model Adding initial water depths Adding a weir to a branch Finishing up and saving the model Creating a 2D flexible mesh Refining the 2D grid locally Saving the 1D2D model","title":"Content of the tutorial"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#tips-for-working-in-the-jupyter-notebook","text":"Tab : Auto-complete on code Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell","title":"\ud83d\udca1 Tips for working in the Jupyter Notebook"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#import-the-needed-modules","text":"Several Python packages are required to run the notebook. These packages are imported below. Please consult the HYDROLIB-core documentation if you want to use additional HYDROLIB-core functionalities later. In [ ]: Copied! # General import geopandas as gpd import matplotlib.pyplot as plt import numpy as np import pandas as pd from pathlib import Path # MeshKernel import meshkernel as mk from meshkernel import GeometryList , MakeGridParameters # HYDROLIB-core from hydrolib.core.dflowfm.mdu import FMModel , AutoStartOption from hydrolib.core.dflowfm.net.models import * from hydrolib.core.dflowfm.crosssection.models import CrossLocModel , CrossDefModel , YZCrsDef from hydrolib.core.dflowfm.friction.models import * from hydrolib.core.dflowfm.bc.models import * from hydrolib.core.dflowfm.ext.models import * from hydrolib.core.dflowfm.inifield.models import * from hydrolib.core.dflowfm.onedfield.models import * from hydrolib.core.dflowfm.structure.models import Weir , FlowDirection , StructureModel print ( \"Imports were successful!\" ) # General import geopandas as gpd import matplotlib.pyplot as plt import numpy as np import pandas as pd from pathlib import Path # MeshKernel import meshkernel as mk from meshkernel import GeometryList, MakeGridParameters # HYDROLIB-core from hydrolib.core.dflowfm.mdu import FMModel, AutoStartOption from hydrolib.core.dflowfm.net.models import * from hydrolib.core.dflowfm.crosssection.models import CrossLocModel, CrossDefModel, YZCrsDef from hydrolib.core.dflowfm.friction.models import * from hydrolib.core.dflowfm.bc.models import * from hydrolib.core.dflowfm.ext.models import * from hydrolib.core.dflowfm.inifield.models import * from hydrolib.core.dflowfm.onedfield.models import * from hydrolib.core.dflowfm.structure.models import Weir, FlowDirection, StructureModel print(\"Imports were successful!\")","title":"Import the needed modules"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#here-starts-the-tutorial","text":"","title":"Here starts the tutorial"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#1-selecting-the-data-location","text":"Exercise \ud83e\udde9: Create a variable that contains the Path to the data folder. In [ ]: Copied! data_dir = ... print ( f \"Data location: { data_dir } \" ) data_dir = ... print(f\"Data location: {data_dir}\")","title":"1. Selecting the data location"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#2-creating-an-empty-d-flow-fm-model","text":"To start a model from scratch, you first need to create an empty model without data. In this tutorial we will create a D-Flow FM model. The MDU file (master definition file) is the main input file of the D-Flow FM model. A new D-Flow FM model is constructed with the FMModel initializer. Exercise \ud83e\udde9 Create a variable containing a new FMModel object. Create a variable containing the export directory Export the D-Flow FM model to an MDU file inside the export directory API references: FMModel FileModel.filepath FileModel.save() In [ ]: Copied! model = ... export_dir = ... model . filepath = ... # Save the MDU file ... print ( f \"MDU file saved: { model . filepath } \" ) model = ... export_dir = ... model.filepath = ... # Save the MDU file ... print(f\"MDU file saved: {model.filepath}\")","title":"2. Creating an empty D-Flow FM model"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#part-1-setting-up-a-1d-delft3d-fm-model","text":"In this part we will build up the complete 1D model schematization step by step. At the end you should have a complete set of model input files for a 1D calculation.","title":"Part 1: Setting up a 1D Delft3D FM model"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#3-reading-the-branch-data-from-a-shape-file","text":"The model will include the lower part of the Magadalena from Cordoba Teton to the river mouth Baranquilla and the Canal del Dique. Exercise \ud83e\udde9 Read the branch data from the branches_Branches.shp file Print the branch data, such that we can answer the following questions: How many river branches does the model have? What are their names? Which friction type and friction value is used for each branch? API references: gpd.read_file In [ ]: Copied! # Read the branches ... # Print the data ... # Answers: # * ... # * ... # * ... # Read the branches ... # Print the data ... # Answers: # * ... # * ... # * ...","title":"3. Reading the branch data from a shape file"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#4-creating-and-assigning-a-1d-computational-grid-to-the-model","text":"In the previous step we read the geometry and attributes of the branches from the shape file. This branch data will become the network input for our D-Flow FM model. Since the model does not have a network yet, we need to create a new network object and assign it to the model. A network may contain a 1D network, a 2D mesh and 1D2D links. Exercise \ud83e\udde9 Create a new network Assign the network to the model and assign a (relative) file path for the net file The new network should contain the data that we read from the shape file: Three Branch objects will need to be added to the network. For each branch, the name, geometry and computational grid points should be provided. The computational points are not included in the data, we will need to generate those with a grid point distance as specified: Branch name dx [m] Channel_1D_1_A 1000 Channel_1D_1_B 1000 Channel_1D_1 500 Hint \ud83d\udca1: The MDU file contains a [Geometry] section which has the network file reference, e.g.: [Geometry] netFile = FlowFM_net.nc ... API references: Network NetworkModel Branch Branch.generate_nodes() Network.mesh1d_add_branch() (undocumented): Adds a branch to the 1D network. The function needs two arguments: Branch : the branch to be added str : The name of the branch that is added In [ ]: Copied! # Assign a new network to the D-Flow FM model and specify the file path network = ... # Specify 1D computational grid point distance per branch dx_per_branch = { \"Channel_1D_1_A\" : 1000 , \"Channel_1D_1_B\" : 1000 , \"Channel_1D_1\" : 500 , } # Assign geometry of the branches and generate the computational grid on top of the branches. # Add each branch to the network for index , branch_data in branches_gdf . iterrows (): branch_geometry = np . transpose ( branch_data . geometry . xy ) ... network . _mesh1d . _set_mesh1d () # Assign a new network to the D-Flow FM model and specify the file path network = ... # Specify 1D computational grid point distance per branch dx_per_branch = { \"Channel_1D_1_A\" : 1000, \"Channel_1D_1_B\" : 1000, \"Channel_1D_1\" : 500, } # Assign geometry of the branches and generate the computational grid on top of the branches. # Add each branch to the network for index, branch_data in branches_gdf.iterrows(): branch_geometry = np.transpose(branch_data.geometry.xy) ... network._mesh1d._set_mesh1d() We can plot the branches onto a background: In [ ]: Copied! # Create a figure with the 1D network figure , axis = plt . subplots ( ncols = 1 ) img = plt . imread ( data_dir / \"osm_background.png\" ) # Add branch names to the plot for branch_name , branch in network . _mesh1d . branches . items (): middle = int (( len ( branch . geometry ) - 1 ) / 2 ) xy = branch . geometry [ middle ] axis . text ( xy [ 0 ], xy [ 1 ], branch_name , ha = 'center' ) axis . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) network . _mesh1d . _get_mesh1d () . plot_edges ( ax = axis , color = 'blue' ) # Create a figure with the 1D network figure, axis = plt.subplots(ncols=1) img = plt.imread(data_dir / \"osm_background.png\") # Add branch names to the plot for branch_name, branch in network._mesh1d.branches.items(): middle = int((len(branch.geometry) - 1)/2) xy = branch.geometry[middle] axis.text(xy[0], xy[1], branch_name, ha='center') axis.imshow(img, extent=[440000, 531544.97964175534434617, 1057000, 1228644.01383191486820579]) network._mesh1d._get_mesh1d().plot_edges(ax=axis, color='blue')","title":"4. Creating and assigning a 1D computational grid to the model"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workbook/#5-adding-cross-sections-to-the-branches","text":"In order to determine the flow area of the 1D model during the computation, you need cross-sections. These cross-sections are defined by two components: Cross-section locations Cross-section definitions The cross-section locations and cross-section definitions are exported to their own file. A cross-section location is defined by the following information: The cross-section ID A location, specified by a branch ID and a chainage. A shift, the vertical shift of the cross section profile. This is mainly used to create a good longitudinal slope over the 1D model (in case of shared cross-sections). A reference to the cross-section definition that is used at this location.

    A cross-section definition is defined by the following information: The cross-section definition ID The cross-section type: circle, rectangle, ZW river, ZW, YZ, XYZ Depending on the type of cross-section, a set of properties describing the properties of the profile shape

    In our data folder, there is a CSV file containing the cross-section locations. We want to convert this data to HYDROLIB-core cross-section location objects and add them to the D-Flow FM model. The columns in the CSV correspond exactly with the field names of a CrossSection class, making the conversion easy. Exercise \ud83e\udde9 Read the data from the CSV file Print the cross-section location data, to answer the following questions: How many cross-section does the model contain in total, and how many does each branch have? Do the cross-section have shared cross-section definitions? A shared cross-section definition is a definition used by more than one cross-section. Convert the CSV data (a pd.DataFrame) into HYDROLIB-core CrossSection objects Assign the cross section locations to the model Hint \ud83d\udca1: The MDU file contains a [Geometry] section which has the crossDefFile and crossLocFile reference, e.g.: [Geometry] crossDefFile = crsdef.ini crossLocFile = crsloc.ini ... API references: pd.read_csv() pd.to_dict() CrossLocModel CrossSection In [ ]: Copied! # Read the cross-sections from the CSV cross_section_data_file = ... cross_section_df = ... # Print the data ... # Answers: # * ... # * ... # Assign the data to the model ... # Read the cross-sections from the CSV cross_section_data_file = ... cross_section_df = ... # Print the data ... # Answers: # * ... # * ... # Assign the data to the model ...","title":"5. 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These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ --jp-shadow-base-lightness: 0; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-400); --jp-border-color1: var(--md-grey-400); --jp-border-color2: var(--md-grey-300); --jp-border-color3: var(--md-grey-200); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(0, 0, 0, 1); --jp-ui-font-color1: rgba(0, 0, 0, 0.87); --jp-ui-font-color2: rgba(0, 0, 0, 0.54); --jp-ui-font-color3: rgba(0, 0, 0, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color1: rgba(255, 255, 255, 1); --jp-ui-inverse-font-color2: rgba(255, 255, 255, 0.7); --jp-ui-inverse-font-color3: rgba(255, 255, 255, 0.5); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(0, 0, 0, 1); --jp-content-font-color1: rgba(0, 0, 0, 0.87); --jp-content-font-color2: rgba(0, 0, 0, 0.54); --jp-content-font-color3: rgba(0, 0, 0, 0.38); --jp-content-link-color: var(--md-blue-700); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: white; --jp-layout-color1: white; --jp-layout-color2: var(--md-grey-200); --jp-layout-color3: var(--md-grey-400); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: #111111; --jp-inverse-layout-color1: var(--md-grey-900); --jp-inverse-layout-color2: var(--md-grey-800); --jp-inverse-layout-color3: var(--md-grey-700); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-900); --jp-brand-color1: var(--md-blue-700); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-900); --jp-accent-color1: var(--md-green-700); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-900); --jp-warn-color1: var(--md-orange-700); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-900); --jp-error-color1: var(--md-red-700); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-900); --jp-success-color1: var(--md-green-700); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-900); --jp-info-color1: var(--md-cyan-700); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--md-grey-100); --jp-cell-editor-border-color: var(--md-grey-300); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 0.5; --jp-cell-prompt-not-active-font-color: var(--md-grey-700); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: var(--md-blue-50); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: #fdd; --jp-rendermime-table-row-background: var(--md-grey-100); --jp-rendermime-table-row-hover-background: var(--md-light-blue-50); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.25); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color1); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.24); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--md-grey-300); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color1); --jp-input-hover-background: var(--jp-layout-color1); --jp-input-background: var(--md-grey-100); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: #d9d9d9; --jp-editor-selected-focused-background: #d7d4f0; --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: #008000; --jp-mirror-editor-atom-color: #88f; --jp-mirror-editor-number-color: #080; --jp-mirror-editor-def-color: #00f; --jp-mirror-editor-variable-color: var(--md-grey-900); --jp-mirror-editor-variable-2-color: #05a; --jp-mirror-editor-variable-3-color: #085; --jp-mirror-editor-punctuation-color: #05a; --jp-mirror-editor-property-color: #05a; --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ba2121; --jp-mirror-editor-string-2-color: #708; --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: #008000; --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: #170; --jp-mirror-editor-attribute-color: #00c; --jp-mirror-editor-header-color: blue; --jp-mirror-editor-quote-color: #090; --jp-mirror-editor-link-color: #00c; --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: white; /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.5; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(245, 200, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } [data-md-color-scheme=\"slate\"] .jupyter-wrapper { /* Elevation * * We style box-shadows using Material Design's idea of elevation. These particular numbers are taken from here: * * https://github.com/material-components/material-components-web * https://material-components-web.appspot.com/elevation.html */ /* The dark theme shadows need a bit of work, but this will probably also require work on the core layout * colors used in the theme as well. */ --jp-shadow-base-lightness: 32; --jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.2 ); --jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.14 ); --jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), 0.12 ); --jp-elevation-z0: none; --jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color); --jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color); --jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color); --jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color); --jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color); --jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color); --jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color); --jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color); --jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color); /* Borders * * The following variables, specify the visual styling of borders in JupyterLab. */ --jp-border-width: 1px; --jp-border-color0: var(--md-grey-700); --jp-border-color1: var(--md-grey-700); --jp-border-color2: var(--md-grey-800); --jp-border-color3: var(--md-grey-900); --jp-border-radius: 2px; /* UI Fonts * * The UI font CSS variables are used for the typography all of the JupyterLab * user interface elements that are not directly user generated content. * * The font sizing here is done assuming that the body font size of --jp-ui-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-ui-font-scale-factor: 1.2; --jp-ui-font-size0: 0.83333em; --jp-ui-font-size1: 13px; /* Base font size */ --jp-ui-font-size2: 1.2em; --jp-ui-font-size3: 1.44em; --jp-ui-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Use these font colors against the corresponding main layout colors. * In a light theme, these go from dark to light. */ /* Defaults use Material Design specification */ --jp-ui-font-color0: rgba(255, 255, 255, 1); --jp-ui-font-color1: rgba(255, 255, 255, 0.87); --jp-ui-font-color2: rgba(255, 255, 255, 0.54); --jp-ui-font-color3: rgba(255, 255, 255, 0.38); /* * Use these against the brand/accent/warn/error colors. * These will typically go from light to darker, in both a dark and light theme. */ --jp-ui-inverse-font-color0: rgba(0, 0, 0, 1); --jp-ui-inverse-font-color1: rgba(0, 0, 0, 0.8); --jp-ui-inverse-font-color2: rgba(0, 0, 0, 0.5); --jp-ui-inverse-font-color3: rgba(0, 0, 0, 0.3); /* Content Fonts * * Content font variables are used for typography of user generated content. * * The font sizing here is done assuming that the body font size of --jp-content-font-size1 * is applied to a parent element. When children elements, such as headings, are sized * in em all things will be computed relative to that body size. */ --jp-content-line-height: 1.6; --jp-content-font-scale-factor: 1.2; --jp-content-font-size0: 0.83333em; --jp-content-font-size1: 14px; /* Base font size */ --jp-content-font-size2: 1.2em; --jp-content-font-size3: 1.44em; --jp-content-font-size4: 1.728em; --jp-content-font-size5: 2.0736em; /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-content-presentation-font-size1: 17px; --jp-content-heading-line-height: 1; --jp-content-heading-margin-top: 1.2em; --jp-content-heading-margin-bottom: 0.8em; --jp-content-heading-font-weight: 500; /* Defaults use Material Design specification */ --jp-content-font-color0: rgba(255, 255, 255, 1); --jp-content-font-color1: rgba(255, 255, 255, 1); --jp-content-font-color2: rgba(255, 255, 255, 0.7); --jp-content-font-color3: rgba(255, 255, 255, 0.5); --jp-content-link-color: var(--md-blue-300); --jp-content-font-family: -apple-system, BlinkMacSystemFont, \"Segoe UI\", Helvetica, Arial, sans-serif, \"Apple Color Emoji\", \"Segoe UI Emoji\", \"Segoe UI Symbol\"; /* * Code Fonts * * Code font variables are used for typography of code and other monospaces content. */ --jp-code-font-size: 13px; --jp-code-line-height: 1.3077; /* 17px for 13px base */ --jp-code-padding: 5px; /* 5px for 13px base, codemirror highlighting needs integer px value */ --jp-code-font-family-default: Menlo, Consolas, \"DejaVu Sans Mono\", monospace; --jp-code-font-family: var(--jp-code-font-family-default); /* This gives a magnification of about 125% in presentation mode over normal. */ --jp-code-presentation-font-size: 16px; /* may need to tweak cursor width if you change font size */ --jp-code-cursor-width0: 1.4px; --jp-code-cursor-width1: 2px; --jp-code-cursor-width2: 4px; /* Layout * * The following are the main layout colors use in JupyterLab. In a light * theme these would go from light to dark. */ --jp-layout-color0: #111111; --jp-layout-color1: var(--md-grey-900); --jp-layout-color2: var(--md-grey-800); --jp-layout-color3: var(--md-grey-700); --jp-layout-color4: var(--md-grey-600); /* Inverse Layout * * The following are the inverse layout colors use in JupyterLab. In a light * theme these would go from dark to light. */ --jp-inverse-layout-color0: white; --jp-inverse-layout-color1: white; --jp-inverse-layout-color2: var(--md-grey-200); --jp-inverse-layout-color3: var(--md-grey-400); --jp-inverse-layout-color4: var(--md-grey-600); /* Brand/accent */ --jp-brand-color0: var(--md-blue-700); --jp-brand-color1: var(--md-blue-500); --jp-brand-color2: var(--md-blue-300); --jp-brand-color3: var(--md-blue-100); --jp-brand-color4: var(--md-blue-50); --jp-accent-color0: var(--md-green-700); --jp-accent-color1: var(--md-green-500); --jp-accent-color2: var(--md-green-300); --jp-accent-color3: var(--md-green-100); /* State colors (warn, error, success, info) */ --jp-warn-color0: var(--md-orange-700); --jp-warn-color1: var(--md-orange-500); --jp-warn-color2: var(--md-orange-300); --jp-warn-color3: var(--md-orange-100); --jp-error-color0: var(--md-red-700); --jp-error-color1: var(--md-red-500); --jp-error-color2: var(--md-red-300); --jp-error-color3: var(--md-red-100); --jp-success-color0: var(--md-green-700); --jp-success-color1: var(--md-green-500); --jp-success-color2: var(--md-green-300); --jp-success-color3: var(--md-green-100); --jp-info-color0: var(--md-cyan-700); --jp-info-color1: var(--md-cyan-500); --jp-info-color2: var(--md-cyan-300); --jp-info-color3: var(--md-cyan-100); /* Cell specific styles */ --jp-cell-padding: 5px; --jp-cell-collapser-width: 8px; --jp-cell-collapser-min-height: 20px; --jp-cell-collapser-not-active-hover-opacity: 0.6; --jp-cell-editor-background: var(--jp-layout-color1); --jp-cell-editor-border-color: var(--md-grey-700); --jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-cell-editor-active-background: var(--jp-layout-color0); --jp-cell-editor-active-border-color: var(--jp-brand-color1); --jp-cell-prompt-width: 64px; --jp-cell-prompt-font-family: var(--jp-code-font-family-default); --jp-cell-prompt-letter-spacing: 0px; --jp-cell-prompt-opacity: 1; --jp-cell-prompt-not-active-opacity: 1; --jp-cell-prompt-not-active-font-color: var(--md-grey-300); /* A custom blend of MD grey and blue 600 * See https://meyerweb.com/eric/tools/color-blend/#546E7A:1E88E5:5:hex */ --jp-cell-inprompt-font-color: #307fc1; /* A custom blend of MD grey and orange 600 * https://meyerweb.com/eric/tools/color-blend/#546E7A:F4511E:5:hex */ --jp-cell-outprompt-font-color: #bf5b3d; /* Notebook specific styles */ --jp-notebook-padding: 10px; --jp-notebook-select-background: var(--jp-layout-color1); --jp-notebook-multiselected-color: rgba(33, 150, 243, 0.24); /* The scroll padding is calculated to fill enough space at the bottom of the notebook to show one single-line cell (with appropriate padding) at the top when the notebook is scrolled all the way to the bottom. We also subtract one pixel so that no scrollbar appears if we have just one single-line cell in the notebook. This padding is to enable a 'scroll past end' feature in a notebook. */ --jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px ); /* Rendermime styles */ --jp-rendermime-error-background: rgba(244, 67, 54, 0.28); --jp-rendermime-table-row-background: var(--md-grey-900); --jp-rendermime-table-row-hover-background: rgba(3, 169, 244, 0.2); /* Dialog specific styles */ --jp-dialog-background: rgba(0, 0, 0, 0.6); /* Console specific styles */ --jp-console-padding: 10px; /* Toolbar specific styles */ --jp-toolbar-border-color: var(--jp-border-color2); --jp-toolbar-micro-height: 8px; --jp-toolbar-background: var(--jp-layout-color1); --jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, 0.8); --jp-toolbar-header-margin: 4px 4px 0px 4px; --jp-toolbar-active-background: var(--jp-layout-color0); /* Statusbar specific styles */ --jp-statusbar-height: 24px; /* Input field styles */ --jp-input-box-shadow: inset 0 0 2px var(--md-blue-300); --jp-input-active-background: var(--jp-layout-color0); --jp-input-hover-background: var(--jp-layout-color2); --jp-input-background: var(--md-grey-800); --jp-input-border-color: var(--jp-border-color1); --jp-input-active-border-color: var(--jp-brand-color1); --jp-input-active-box-shadow-color: rgba(19, 124, 189, 0.3); /* General editor styles */ --jp-editor-selected-background: var(--jp-layout-color2); --jp-editor-selected-focused-background: rgba(33, 150, 243, 0.24); --jp-editor-cursor-color: var(--jp-ui-font-color0); /* Code mirror specific styles */ --jp-mirror-editor-keyword-color: var(--md-green-500); --jp-mirror-editor-atom-color: var(--md-blue-300); --jp-mirror-editor-number-color: var(--md-green-400); --jp-mirror-editor-def-color: var(--md-blue-600); --jp-mirror-editor-variable-color: var(--md-grey-300); --jp-mirror-editor-variable-2-color: var(--md-blue-400); --jp-mirror-editor-variable-3-color: var(--md-green-600); --jp-mirror-editor-punctuation-color: var(--md-blue-400); --jp-mirror-editor-property-color: var(--md-blue-400); --jp-mirror-editor-operator-color: #aa22ff; --jp-mirror-editor-comment-color: #408080; --jp-mirror-editor-string-color: #ff7070; --jp-mirror-editor-string-2-color: var(--md-purple-300); --jp-mirror-editor-meta-color: #aa22ff; --jp-mirror-editor-qualifier-color: #555; --jp-mirror-editor-builtin-color: var(--md-green-600); --jp-mirror-editor-bracket-color: #997; --jp-mirror-editor-tag-color: var(--md-green-700); --jp-mirror-editor-attribute-color: var(--md-blue-700); --jp-mirror-editor-header-color: var(--md-blue-500); --jp-mirror-editor-quote-color: var(--md-green-300); --jp-mirror-editor-link-color: var(--md-blue-700); --jp-mirror-editor-error-color: #f00; --jp-mirror-editor-hr-color: #999; /* Vega extension styles */ --jp-vega-background: var(--md-grey-400); /* Sidebar-related styles */ --jp-sidebar-min-width: 250px; /* Search-related styles */ --jp-search-toggle-off-opacity: 0.6; --jp-search-toggle-hover-opacity: 0.8; --jp-search-toggle-on-opacity: 1; --jp-search-selected-match-background-color: rgb(255, 225, 0); --jp-search-selected-match-color: black; --jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 ); --jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0); /* scrollbar related styles. Supports every browser except Edge. */ /* colors based on JetBrain's Darcula theme */ --jp-scrollbar-background-color: #3f4244; --jp-scrollbar-thumb-color: 88, 96, 97; /* need to specify thumb color as an RGB triplet */ --jp-scrollbar-endpad: 3px; /* the minimum gap between the thumb and the ends of a scrollbar */ /* hacks for setting the thumb shape. These do nothing in Firefox */ --jp-scrollbar-thumb-margin: 3.5px; /* the space in between the sides of the thumb and the track */ --jp-scrollbar-thumb-radius: 9px; /* set to a large-ish value for rounded endcaps on the thumb */ /* Icon colors that work well with light or dark backgrounds */ --jp-icon-contrast-color0: var(--md-purple-600); --jp-icon-contrast-color1: var(--md-green-600); --jp-icon-contrast-color2: var(--md-pink-600); --jp-icon-contrast-color3: var(--md-blue-600); } :root{--md-red-50: #ffebee;--md-red-100: #ffcdd2;--md-red-200: #ef9a9a;--md-red-300: #e57373;--md-red-400: #ef5350;--md-red-500: #f44336;--md-red-600: #e53935;--md-red-700: #d32f2f;--md-red-800: #c62828;--md-red-900: #b71c1c;--md-red-A100: #ff8a80;--md-red-A200: #ff5252;--md-red-A400: #ff1744;--md-red-A700: #d50000;--md-pink-50: #fce4ec;--md-pink-100: #f8bbd0;--md-pink-200: #f48fb1;--md-pink-300: #f06292;--md-pink-400: #ec407a;--md-pink-500: #e91e63;--md-pink-600: #d81b60;--md-pink-700: #c2185b;--md-pink-800: 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#7986cb;--md-indigo-400: #5c6bc0;--md-indigo-500: #3f51b5;--md-indigo-600: #3949ab;--md-indigo-700: #303f9f;--md-indigo-800: #283593;--md-indigo-900: #1a237e;--md-indigo-A100: #8c9eff;--md-indigo-A200: #536dfe;--md-indigo-A400: #3d5afe;--md-indigo-A700: #304ffe;--md-blue-50: #e3f2fd;--md-blue-100: #bbdefb;--md-blue-200: #90caf9;--md-blue-300: #64b5f6;--md-blue-400: #42a5f5;--md-blue-500: #2196f3;--md-blue-600: #1e88e5;--md-blue-700: #1976d2;--md-blue-800: #1565c0;--md-blue-900: #0d47a1;--md-blue-A100: #82b1ff;--md-blue-A200: #448aff;--md-blue-A400: #2979ff;--md-blue-A700: #2962ff;--md-light-blue-50: #e1f5fe;--md-light-blue-100: #b3e5fc;--md-light-blue-200: #81d4fa;--md-light-blue-300: #4fc3f7;--md-light-blue-400: #29b6f6;--md-light-blue-500: #03a9f4;--md-light-blue-600: #039be5;--md-light-blue-700: #0288d1;--md-light-blue-800: #0277bd;--md-light-blue-900: #01579b;--md-light-blue-A100: #80d8ff;--md-light-blue-A200: #40c4ff;--md-light-blue-A400: #00b0ff;--md-light-blue-A700: #0091ea;--md-cyan-50: #e0f7fa;--md-cyan-100: #b2ebf2;--md-cyan-200: #80deea;--md-cyan-300: #4dd0e1;--md-cyan-400: #26c6da;--md-cyan-500: #00bcd4;--md-cyan-600: #00acc1;--md-cyan-700: #0097a7;--md-cyan-800: #00838f;--md-cyan-900: #006064;--md-cyan-A100: #84ffff;--md-cyan-A200: #18ffff;--md-cyan-A400: #00e5ff;--md-cyan-A700: #00b8d4;--md-teal-50: #e0f2f1;--md-teal-100: #b2dfdb;--md-teal-200: #80cbc4;--md-teal-300: #4db6ac;--md-teal-400: #26a69a;--md-teal-500: #009688;--md-teal-600: #00897b;--md-teal-700: #00796b;--md-teal-800: #00695c;--md-teal-900: #004d40;--md-teal-A100: #a7ffeb;--md-teal-A200: #64ffda;--md-teal-A400: #1de9b6;--md-teal-A700: #00bfa5;--md-green-50: #e8f5e9;--md-green-100: #c8e6c9;--md-green-200: #a5d6a7;--md-green-300: #81c784;--md-green-400: #66bb6a;--md-green-500: #4caf50;--md-green-600: #43a047;--md-green-700: #388e3c;--md-green-800: #2e7d32;--md-green-900: #1b5e20;--md-green-A100: #b9f6ca;--md-green-A200: #69f0ae;--md-green-A400: #00e676;--md-green-A700: #00c853;--md-light-green-50: #f1f8e9;--md-light-green-100: #dcedc8;--md-light-green-200: #c5e1a5;--md-light-green-300: #aed581;--md-light-green-400: #9ccc65;--md-light-green-500: #8bc34a;--md-light-green-600: #7cb342;--md-light-green-700: #689f38;--md-light-green-800: #558b2f;--md-light-green-900: #33691e;--md-light-green-A100: #ccff90;--md-light-green-A200: #b2ff59;--md-light-green-A400: #76ff03;--md-light-green-A700: #64dd17;--md-lime-50: #f9fbe7;--md-lime-100: #f0f4c3;--md-lime-200: #e6ee9c;--md-lime-300: #dce775;--md-lime-400: #d4e157;--md-lime-500: #cddc39;--md-lime-600: #c0ca33;--md-lime-700: #afb42b;--md-lime-800: #9e9d24;--md-lime-900: #827717;--md-lime-A100: #f4ff81;--md-lime-A200: #eeff41;--md-lime-A400: #c6ff00;--md-lime-A700: #aeea00;--md-yellow-50: #fffde7;--md-yellow-100: #fff9c4;--md-yellow-200: #fff59d;--md-yellow-300: #fff176;--md-yellow-400: #ffee58;--md-yellow-500: #ffeb3b;--md-yellow-600: #fdd835;--md-yellow-700: #fbc02d;--md-yellow-800: #f9a825;--md-yellow-900: #f57f17;--md-yellow-A100: #ffff8d;--md-yellow-A200: #ffff00;--md-yellow-A400: #ffea00;--md-yellow-A700: #ffd600;--md-amber-50: #fff8e1;--md-amber-100: #ffecb3;--md-amber-200: #ffe082;--md-amber-300: #ffd54f;--md-amber-400: #ffca28;--md-amber-500: #ffc107;--md-amber-600: #ffb300;--md-amber-700: #ffa000;--md-amber-800: #ff8f00;--md-amber-900: #ff6f00;--md-amber-A100: #ffe57f;--md-amber-A200: #ffd740;--md-amber-A400: #ffc400;--md-amber-A700: #ffab00;--md-orange-50: #fff3e0;--md-orange-100: #ffe0b2;--md-orange-200: #ffcc80;--md-orange-300: #ffb74d;--md-orange-400: #ffa726;--md-orange-500: #ff9800;--md-orange-600: #fb8c00;--md-orange-700: #f57c00;--md-orange-800: #ef6c00;--md-orange-900: #e65100;--md-orange-A100: #ffd180;--md-orange-A200: #ffab40;--md-orange-A400: #ff9100;--md-orange-A700: #ff6d00;--md-deep-orange-50: #fbe9e7;--md-deep-orange-100: #ffccbc;--md-deep-orange-200: #ffab91;--md-deep-orange-300: #ff8a65;--md-deep-orange-400: #ff7043;--md-deep-orange-500: 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sourceMappingURL=mkdocs-jupyter.css.map*/ init_mathjax = function() { if (window.MathJax) { // MathJax loaded MathJax.Hub.Config({ TeX: { equationNumbers: { autoNumber: \"AMS\", useLabelIds: true } }, tex2jax: { inlineMath: [ ['$','$'], [\"\\\\(\",\"\\\\)\"] ], displayMath: [ ['$$','$$'], [\"\\\\[\",\"\\\\]\"] ], processEscapes: true, processEnvironments: true }, displayAlign: 'center', CommonHTML: { linebreaks: { automatic: true } } }); MathJax.Hub.Queue([\"Typeset\", MathJax.Hub]); } } init_mathjax(); Creating a Delft3D FM 1D2D fluvial flood model of Magdalena river \u00b6 The exercises in this notebook will serve as introduction on how to use HYDROLIB-core functionalities. We will create and adjust a Delft3D FM Suite 1D2D fluvial flood model of the Magdalena river in Columbia. First a 1D river model of the Magdalena river and Canal del Dique will be created, shown in the left figure. This model will be extended with a 2D Flexible Mesh, with a uniform roughness field. Adding a Digital Terrain Model (DTM) on that 2D mesh is currently not part of this tutorial, but in practice this is indispensible to mimic the fluvial flood patterns. Note that the model that will be created is for educational purposes and consists partially of fictive or unvalidated model data. Using HYDROLIB-core to build models \u00b6 HYDROLIB-core is a Python package that offers functionality to process D-HYDRO input files. It offers Python-wrapped classes that represent these files and their content. HYDROLIB-core serves as the basis for various pre- and postprocessing tools for a modelling workflow of hydrodynamic simulations in D-HYDRO. It can easily be used to build models and export the model files that can aftewards be run by dflowfm or other supported D-HYDRO kernels. Content of the tutorial \u00b6 The goal of this tutorial is to familiarize modelers with applying HYDROLIB-core functionalities in their modelling procedures for building new models or adjusting existing models. As mentioned above, you will create an 1D2D fluvial flood model from scratch using the D-Flow FM HYDROLIB-core functionalities and the underlying functions from mesh generation ( MeshKernelPy ). We will walk through the following steps to build the model: Selecting the data location Creating an empty D-Flow FM model Reading the branch data from a shape file Creating and assigning a 1D computational grid to the model Adding cross-sections to the branches Adding cross-section definitions Adding roughness to the model Adding boundary conditions to the model Adding initial water depths Adding a weir to a branch Finishing up and saving the model Creating a 2D flexible mesh Refining the 2D grid locally Saving the 1D2D model \ud83d\udca1 Tips for working in the Jupyter Notebook \u00b6 Tab : Auto-complete on code Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell Import the needed modules \u00b6 Several Python packages are required to run the notebook. These packages are imported below. Please consult the HYDROLIB-core documentation if you want to use additional HYDROLIB-core functionalities later. In [ ]: Copied! # General import geopandas as gpd import matplotlib.pyplot as plt import numpy as np import pandas as pd from pathlib import Path # MeshKernel import meshkernel as mk from meshkernel import GeometryList , MakeGridParameters # HYDROLIB-core from hydrolib.core.dflowfm.mdu import FMModel , AutoStartOption from hydrolib.core.dflowfm.net.models import * from hydrolib.core.dflowfm.crosssection.models import CrossLocModel , CrossDefModel , YZCrsDef from hydrolib.core.dflowfm.friction.models import * from hydrolib.core.dflowfm.bc.models import * from hydrolib.core.dflowfm.ext.models import * from hydrolib.core.dflowfm.inifield.models import * from hydrolib.core.dflowfm.onedfield.models import * from hydrolib.core.dflowfm.structure.models import Weir , FlowDirection , StructureModel print ( \"Imports were successful!\" ) # General import geopandas as gpd import matplotlib.pyplot as plt import numpy as np import pandas as pd from pathlib import Path # MeshKernel import meshkernel as mk from meshkernel import GeometryList, MakeGridParameters # HYDROLIB-core from hydrolib.core.dflowfm.mdu import FMModel, AutoStartOption from hydrolib.core.dflowfm.net.models import * from hydrolib.core.dflowfm.crosssection.models import CrossLocModel, CrossDefModel, YZCrsDef from hydrolib.core.dflowfm.friction.models import * from hydrolib.core.dflowfm.bc.models import * from hydrolib.core.dflowfm.ext.models import * from hydrolib.core.dflowfm.inifield.models import * from hydrolib.core.dflowfm.onedfield.models import * from hydrolib.core.dflowfm.structure.models import Weir, FlowDirection, StructureModel print(\"Imports were successful!\") Here starts the tutorial \u00b6 1. Selecting the data location \u00b6 Exercise \ud83e\udde9: Create a variable that contains the Path to the data folder. In [ ]: Copied! root = Path . cwd () data_dir = root / 'data' print ( f \"Data location: { data_dir } \" ) root = Path.cwd() data_dir = root / 'data' print(f\"Data location: {data_dir}\") 2. Creating an empty D-Flow FM model \u00b6 To start a model from scratch, you first need to create an empty model without data. In this tutorial we will create a D-Flow FM model. The MDU file (master definition file) is the main input file of the D-Flow FM model. A new D-Flow FM model is constructed with the FMModel initializer. Exercise \ud83e\udde9 Create a variable containing a new FMModel object. Create a variable containing the export directory Export the D-Flow FM model to an MDU file inside the export directory API references: FMModel FileModel.filepath FileModel.save() In [ ]: Copied! model = FMModel () export_dir = root / 'export' model . filepath = export_dir / 'Magdalena_1D.mdu' # Save the MDU file model . save () print ( f \"MDU file saved: { model . filepath } \" ) model = FMModel() export_dir = root / 'export' model.filepath = export_dir / 'Magdalena_1D.mdu' # Save the MDU file model.save() print(f\"MDU file saved: {model.filepath}\") Part 1: Setting up a 1D Delft3D FM model \u00b6 In this part we will build up the complete 1D model schematization step by step. At the end you should have a complete set of model input files for a 1D calculation. 3. Reading the branch data from a shape file \u00b6 The model will include the lower part of the Magadalena from Cordoba Teton to the river mouth Baranquilla and the Canal del Dique. Exercise \ud83e\udde9 Read the branch data from the branches_Branches.shp file Print the branch data, such that we can answer the following questions: How many river branches does the model have? What are their names? Which friction type and friction value is used for each branch? API references: gpd.read_file In [ ]: Copied! # Read the branches branch_shp_file = data_dir / 'branches_Branches.shp' branches_gdf = gpd . read_file ( filename = branch_shp_file ) # Print the data print ( branches_gdf ) # Answers: # * 3 branches # * Channel_1D_1_A, Channel_1D_1_B and Channel_1D_1 # * Channel_1D_1_A: Manning, 0.03 # Channel_1D_1_B: Manning, 0.02 # Channel_1D_1 : Manning, 0.02 # Read the branches branch_shp_file = data_dir / 'branches_Branches.shp' branches_gdf = gpd.read_file(filename = branch_shp_file) # Print the data print(branches_gdf) # Answers: # * 3 branches # * Channel_1D_1_A, Channel_1D_1_B and Channel_1D_1 # * Channel_1D_1_A: Manning, 0.03 # Channel_1D_1_B: Manning, 0.02 # Channel_1D_1 : Manning, 0.02 4. Creating and assigning a 1D computational grid to the model \u00b6 In the previous step we read the geometry and attributes of the branches from the shape file. This branch data will become the network input for our D-Flow FM model. Since the model does not have a network yet, we need to create a new network object and assign it to the model. A network may contain a 1D network, a 2D mesh and 1D2D links. Exercise \ud83e\udde9 Create a new network Assign the network to the model and assign a (relative) file path for the net file The new network should contain the data that we read from the shape file: Three Branch objects will need to be added to the network. For each branch, the name, geometry and computational grid points should be provided. The computational points are not included in the data, we will need to generate those with a grid point distance as specified: Branch name dx [m] Channel_1D_1_A 1000 Channel_1D_1_B 1000 Channel_1D_1 500 Hint \ud83d\udca1: The MDU file contains a [Geometry] section which has the network file reference, e.g.: [Geometry] netFile = FlowFM_net.nc ... API references: Network NetworkModel Branch Branch.generate_nodes() Network.mesh1d_add_branch() (undocumented): Adds a branch to the 1D network. The function needs two arguments: Branch : the branch to be added str : The name of the branch that is added In [ ]: Copied! # Assign a new network to the D-Flow FM model and specify the file path network = Network () model . geometry . netfile . network = network model . geometry . netfile . filepath = \"FlowFM_net.nc\" # Specify 1D computational grid point distance per branch dx_per_branch = { \"Channel_1D_1_A\" : 1000 , \"Channel_1D_1_B\" : 1000 , \"Channel_1D_1\" : 500 , } # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch_data in branches_gdf . iterrows (): branch_geometry = np . transpose ( branch_data . geometry . xy ) branch = Branch ( geometry = branch_geometry ) branch . generate_nodes ( mesh1d_edge_length = dx_per_branch [ branch_data . Name ]) network . mesh1d_add_branch ( branch , name = branch_data . Name ) network . _mesh1d . _set_mesh1d () # Assign a new network to the D-Flow FM model and specify the file path network = Network() model.geometry.netfile.network = network model.geometry.netfile.filepath = \"FlowFM_net.nc\" # Specify 1D computational grid point distance per branch dx_per_branch = { \"Channel_1D_1_A\" : 1000, \"Channel_1D_1_B\" : 1000, \"Channel_1D_1\" : 500, } # Assign geometry of the branches and generate the computational grid on top of the branches. for index, branch_data in branches_gdf.iterrows(): branch_geometry = np.transpose(branch_data.geometry.xy) branch = Branch(geometry=branch_geometry) branch.generate_nodes(mesh1d_edge_length=dx_per_branch[branch_data.Name]) network.mesh1d_add_branch(branch, name=branch_data.Name) network._mesh1d._set_mesh1d() We can plot the branches onto a background: In [ ]: Copied! # Create a figure with the 1D network figure , axis = plt . subplots ( ncols = 1 ) img = plt . imread ( data_dir / \"osm_background.png\" ) # Add branch names to the plot for branch_name , branch in network . _mesh1d . branches . items (): middle = int (( len ( branch . geometry ) - 1 ) / 2 ) xy = branch . geometry [ middle ] axis . text ( xy [ 0 ], xy [ 1 ], branch_name , ha = 'center' ) axis . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) network . _mesh1d . _get_mesh1d () . plot_edges ( ax = axis , color = 'blue' ) # Create a figure with the 1D network figure, axis = plt.subplots(ncols=1) img = plt.imread(data_dir / \"osm_background.png\") # Add branch names to the plot for branch_name, branch in network._mesh1d.branches.items(): middle = int((len(branch.geometry) - 1)/2) xy = branch.geometry[middle] axis.text(xy[0], xy[1], branch_name, ha='center') axis.imshow(img, extent=[440000, 531544.97964175534434617, 1057000, 1228644.01383191486820579]) network._mesh1d._get_mesh1d().plot_edges(ax=axis, color='blue') 5. Adding cross-sections to the branches \u00b6 In order to determine the flow area of the 1D model during the computation, you need cross-sections. These cross-sections are defined by two components: Cross-section locations Cross-section definitions The cross-section locations and cross-section definitions are exported to their own file. A cross-section location is defined by the following information: The cross-section ID A location, specified by a branch ID and a chainage. A shift, the vertical shift of the cross section profile. This is mainly used to create a good longitudinal slope over the 1D model (in case of shared cross-sections). A reference to the cross-section definition that is used at this location.

    A cross-section definition is defined by the following information: The cross-section definition ID The cross-section type: circle, rectangle, ZW river, ZW, YZ, XYZ Depending on the type of cross-section, a set of properties describing the properties of the profile shape

    In our data folder, there is a CSV file containing the cross-section locations. We want to convert this data to HYDROLIB-core cross-section location objects and add them to the D-Flow FM model. The columns in the CSV correspond exactly with the field names of a CrossSection class, making the conversion easy. Exercise \ud83e\udde9 Read the data from the CSV file Print the cross-section location data, to answer the following questions: How many cross-section does the model contain in total, and how many does each branch have? Do the cross-section have shared cross-section definitions? A shared cross-section definition is a definition used by more than one cross-section. Convert the CSV data (a pd.DataFrame) into HYDROLIB-core CrossSection objects Assign the cross section locations to the model Hint \ud83d\udca1: The MDU file contains a [Geometry] section which has the crossDefFile and crossLocFile reference, e.g.: [Geometry] crossDefFile = crsdef.ini crossLocFile = crsloc.ini ... API references: pd.read_csv() pd.to_dict() CrossLocModel CrossSection In [ ]: Copied! # Read the cross-sections from the CSV cross_section_data_file = data_dir / 'cross_section_locations.csv' cross_section_df = pd . read_csv ( cross_section_data_file , index_col = False ) # Print the data print ( cross_section_df ) # Answers: # * There are 6 cross-sections in the model and each branch has two cross-sections # * There are no shared cross-section definitions; each cross-section has a unique definition ID. # Assign the data to the model cross_loc_model = CrossLocModel () model . geometry . crosslocfile = cross_loc_model cross_loc_model . crosssection = cross_section_df . to_dict ( \"records\" ) # Read the cross-sections from the CSV cross_section_data_file = data_dir / 'cross_section_locations.csv' cross_section_df = pd.read_csv(cross_section_data_file, index_col=False) # Print the data print(cross_section_df) # Answers: # * There are 6 cross-sections in the model and each branch has two cross-sections # * There are no shared cross-section definitions; each cross-section has a unique definition ID. # Assign the data to the model cross_loc_model = CrossLocModel() model.geometry.crosslocfile = cross_loc_model cross_loc_model.crosssection = cross_section_df.to_dict(\"records\") 6. Adding cross-section definitions \u00b6 In the following exercise we will add the cross-section definitions to the D-Flow FM model. These belong to the cross-sections we added in the previous step. These cross-sections all have YZ-profiles in order to define a natural shape of the river. Please finish the code below. Exercise \ud83e\udde9 Create a new cross-section definition model with the defined properties Create an YZ profile for each profile from the excel file Append each YZ profile to the cross-section definition model Make sure the data is assigned to the D-Flow FM model API references: CrossDefModel YZCrsDef In [ ]: Copied! profiles_file = data_dir / '1D_YZ_CrossSections.xlsx' profile_excel_data = pd . read_excel ( profiles_file , sheet_name = None ) profile_names = list ( profile_excel_data ) print ( f \"Profile names: { profile_names } \" ) # Create a new cross-section definition model and assign to the model cross_def_model = CrossDefModel () model . geometry . crossdeffile = cross_def_model # Properties for each YZ profile type_crs = 'yz' thalweg = 0.0 single_valued_z = 'yes' conveyance = 'segmented' sectionCount = 1 friction_ids = 'channels' # Create the YZ profiles and append them to the CrossDefModel for profile_name in profile_names : profile_data = profile_excel_data [ profile_name ] num_coords = len ( profile_data . values ) y_coords = profile_data . y . to_list () z_coords = profile_data . z . to_list () # Define friction positions at begin and end of profile friction_positions = [ profile_data . y [ 0 ], profile_data . y [ num_coords - 1 ]] # Create an YZ profile and add it to the cross-section definition model cross_section = YZCrsDef ( id = profile_name , type = type_crs , thalweg = thalweg , singleValuedZ = single_valued_z , conveyance = conveyance , yzCount = num_coords , yCoordinates = y_coords , zCoordinates = z_coords , sectionCount = sectionCount , frictionIds = friction_ids , frictionPositions = friction_positions ) cross_def_model . definition . append ( cross_section ) profiles_file = data_dir / '1D_YZ_CrossSections.xlsx' profile_excel_data = pd.read_excel(profiles_file, sheet_name=None) profile_names = list(profile_excel_data) print(f\"Profile names: {profile_names}\") # Create a new cross-section definition model and assign to the model cross_def_model = CrossDefModel() model.geometry.crossdeffile = cross_def_model # Properties for each YZ profile type_crs = 'yz' thalweg = 0.0 single_valued_z = 'yes' conveyance = 'segmented' sectionCount = 1 friction_ids = 'channels' # Create the YZ profiles and append them to the CrossDefModel for profile_name in profile_names: profile_data = profile_excel_data[profile_name] num_coords = len(profile_data.values) y_coords = profile_data.y.to_list() z_coords = profile_data.z.to_list() # Define friction positions at begin and end of profile friction_positions = [profile_data.y[0], profile_data.y[num_coords-1]] # Create an YZ profile and add it to the cross-section definition model cross_section = YZCrsDef(id=profile_name, type=type_crs, thalweg=thalweg, singleValuedZ=single_valued_z, conveyance=conveyance, yzCount=num_coords, yCoordinates=y_coords, zCoordinates = z_coords, sectionCount = sectionCount, frictionIds = friction_ids, frictionPositions=friction_positions) cross_def_model.definition.append(cross_section) 7. Adding roughness to the model \u00b6 Our 1D D-Flow FM model now has a network topology, computational grid points and cross-sections. Friction is a component that should be added to the model to get the proper bed roughness and channel conveyance. For each branch, we will add a friction type and value at the upstream location. We will also specify a global roughness section. This will be used when there is no friction defined for a branch. It also contains a friction ID. In the cross-section definitions we created above, a reference is made to this friction ID (='channels'). YZ profiles can refer to multiple friction IDs, since the friction can vary within the cross-section. This also means that multiple friction definition files can be added to one D-Flow FM model. In [ ]: Copied! channel_friction_id = 'channels' channel_global_type = FrictionType . manning channel_global_value = 0.023 channel_friction_model = FrictionModel () channel_friction_model . filepath = \"roughness-channels.ini\" # It is conventional to specify the file names as \"roughness-[friction ID].ini\" model . geometry . frictfile = [ channel_friction_model ] # Create global friction model and add it to frictionmodel channel_global_friction = FrictGlobal ( frictionId = channel_friction_id , frictionType = channel_global_type , frictionValue = channel_global_value ) channel_friction_model . global_ = channel_global_friction function_type = 'constant' # Create friction definition per branch for index , branch_data in branches_gdf . iterrows (): friction_per_branch = FrictBranch ( branchId = branch_data . Name , frictionType = branch_data . fric_type , frictionValues = [ branch_data . fric_value ], chainage = [ branch_data . chainage ], numLocations = 1 , functionType = function_type ) channel_friction_model . branch . append ( friction_per_branch ) channel_friction_id = 'channels' channel_global_type = FrictionType.manning channel_global_value = 0.023 channel_friction_model = FrictionModel() channel_friction_model.filepath = \"roughness-channels.ini\" # It is conventional to specify the file names as \"roughness-[friction ID].ini\" model.geometry.frictfile = [channel_friction_model] # Create global friction model and add it to frictionmodel channel_global_friction = FrictGlobal(frictionId=channel_friction_id, frictionType=channel_global_type, frictionValue=channel_global_value) channel_friction_model.global_ = channel_global_friction function_type = 'constant' # Create friction definition per branch for index, branch_data in branches_gdf.iterrows(): friction_per_branch = FrictBranch(branchId=branch_data.Name, frictionType=branch_data.fric_type, frictionValues=[branch_data.fric_value], chainage=[branch_data.chainage], numLocations=1, functionType=function_type) channel_friction_model.branch.append(friction_per_branch) We want to define another global friction definition for the Canal del Dique. This friction model assumes Chezy as global friction type and a friction value of 45.0. You can use the code above as an example. Exercise \ud83e\udde9 Create a new friction model for Canal del Dique Specify a global friction definition Make sure the new friction model is added to the D-Flow FM model API references: FrictionType FrictionModel FrictGlobal In [ ]: Copied! dique_friction_id = 'dique' dique_global_type = FrictionType . chezy dique_global_value = 45.0 dique_friction_model = FrictionModel () dique_friction_model . filepath = 'roughness-dique.ini' model . geometry . frictfile . append ( dique_friction_model ) dique_global_friction = FrictGlobal ( frictionId = dique_friction_id , frictionType = dique_global_type , frictionValue = dique_global_value ) dique_friction_model . global_ = dique_global_friction dique_friction_id = 'dique' dique_global_type = FrictionType.chezy dique_global_value = 45.0 dique_friction_model = FrictionModel() dique_friction_model.filepath = 'roughness-dique.ini' model.geometry.frictfile.append(dique_friction_model) dique_global_friction = FrictGlobal(frictionId=dique_friction_id, frictionType=dique_global_type, frictionValue=dique_global_value) dique_friction_model.global_ = dique_global_friction The cross-sections on the Canal del Dique (Channel_1D_1) do not refer to this new friction ID yet. Exercise \ud83e\udde9 Use the cross-section locations and definitions in the D-Flow FM model to find the cross-sections on the Channel_1D_1 branch Reassign the friction ID of the correct cross sections to the one used for the Canal del Dique In [ ]: Copied! cross_section_definitions = model . geometry . crossdeffile . definition cross_section_locations = model . geometry . crosslocfile . crosssection # Create a dictionary with the definition IDs, for easily finding the correct definition definition_dict = { definition . id : definition for definition in cross_section_definitions } for cross_section in cross_section_locations : if cross_section . branchid == \"Channel_1D_1\" : cross_section_definition = definition_dict [ cross_section . definitionid ] cross_section_definition . frictionids = [ dique_friction_id ] cross_section_definitions = model.geometry.crossdeffile.definition cross_section_locations = model.geometry.crosslocfile.crosssection # Create a dictionary with the definition IDs, for easily finding the correct definition definition_dict = {definition.id: definition for definition in cross_section_definitions} for cross_section in cross_section_locations: if cross_section.branchid == \"Channel_1D_1\": cross_section_definition = definition_dict[cross_section.definitionid] cross_section_definition.frictionids = [dique_friction_id] 8. Adding boundary conditions to the model \u00b6 Fluvial floods occur when water levels in the river are too high. These high water levels in the rivers can result from several factors. One of those is the occurence of heavy rainfall in the upstream catchment. These heavy rainstorms can lead to a high discharge wave entering the upstream boundary of the river. In order to apply boundary conditions on a model you need data from two files: External forcing file (*.ext) : specifies the location and type of forcing. Boundary conditions file (*.bc) : contains the forcing values, e.g. a time series or a constant value In this tutorial you will model such a high discharge wave (time series) at the upstream 1D boundary. For the two downstream boundaries a constant water level of 0 m AD is assumed. Note that this are tidal boundaries in reality. Exercise \ud83e\udde9 Complete the code below by adding the boundary locations to the external forcing model. For each boundary location (3), the correct boundary object should be created with a quantity, node ID and forcing file. The quantity keys for discharge and water level are 'dischargebnd' and 'waterlevelbnd', respectively. API references: Boundary In [ ]: Copied! ext_model = ExtModel () # External forcing file (.ext) bc_model = ForcingModel () # Boundary conditions file (.bc) model . external_forcing . extforcefilenew = ext_model # Read the upstream boundary time series from excel discharge_file = data_dir / '1D_BoundaryConditions.xlsx' discharge_excel_df = pd . read_excel ( discharge_file , sheet_name = [ 0 ]) node_ids = model . geometry . netfile . network . _mesh1d . network1d_node_id print ( node_ids ) node_upstream = node_ids [ 0 ] # time series discharge node nodes_downstream = node_ids [ 2 :] # constant water level nodes # Create the discharge timeseries bc_upstream = TimeSeries ( name = node_upstream , nodeid = node_upstream , timeinterpolation = TimeInterpolation . linear , quantityunitpair = [ QuantityUnitPair ( quantity = 'time' , unit = 'minutes since 2012-01-01 00:00:00' ), QuantityUnitPair ( quantity = 'dischargebnd' , unit = 'm\u00b3/s' )], datablock = [[ time , dis ] for [ time , dis ] in discharge_excel_df [ 0 ] . values ]) bc_model . forcing . append ( bc_upstream ) # Create the constant water level for node_downstream in nodes_downstream : bc_downstream = Constant ( name = node_downstream , nodeid = node_downstream , quantityunitpair = [ QuantityUnitPair ( quantity = 'waterlevelbnd' , unit = 'm' )], datablock = [[ \"0.0\" ]]) bc_model . forcing . append ( bc_downstream ) # Create the boundary locations for the discharge and the water level ext_upstream = Boundary ( quantity = 'dischargebnd' , nodeid = node_upstream , forcingfile = bc_model ) ext_model . boundary . append ( ext_upstream ) for node_downstream in nodes_downstream : ext_downstream = Boundary ( quantity = 'waterlevelbnd' , nodeid = node_downstream , forcingfile = bc_model ) ext_model . boundary . append ( ext_downstream ) ext_model = ExtModel() # External forcing file (.ext) bc_model = ForcingModel() # Boundary conditions file (.bc) model.external_forcing.extforcefilenew = ext_model # Read the upstream boundary time series from excel discharge_file = data_dir / '1D_BoundaryConditions.xlsx' discharge_excel_df = pd.read_excel(discharge_file, sheet_name=[0]) node_ids = model.geometry.netfile.network._mesh1d.network1d_node_id print(node_ids) node_upstream = node_ids[0] # time series discharge node nodes_downstream = node_ids[2:] # constant water level nodes # Create the discharge timeseries bc_upstream = TimeSeries( name = node_upstream, nodeid = node_upstream, timeinterpolation = TimeInterpolation.linear, quantityunitpair = [QuantityUnitPair(quantity = 'time', unit = 'minutes since 2012-01-01 00:00:00'), QuantityUnitPair(quantity = 'dischargebnd', unit = 'm\u00b3/s')], datablock = [[time, dis] for [time,dis] in discharge_excel_df[0].values]) bc_model.forcing.append(bc_upstream) # Create the constant water level for node_downstream in nodes_downstream: bc_downstream = Constant( name = node_downstream, nodeid = node_downstream, quantityunitpair = [QuantityUnitPair(quantity = 'waterlevelbnd', unit = 'm')], datablock = [[\"0.0\"]]) bc_model.forcing.append(bc_downstream) # Create the boundary locations for the discharge and the water level ext_upstream = Boundary( quantity = 'dischargebnd', nodeid = node_upstream, forcingfile = bc_model) ext_model.boundary.append(ext_upstream) for node_downstream in nodes_downstream: ext_downstream = Boundary( quantity = 'waterlevelbnd', nodeid = node_downstream, forcingfile = bc_model ) ext_model.boundary.append(ext_downstream) 9. Adding initial water depths \u00b6 For this model an initial water depth of 1.0 meter is assumed in the 1D model. Below we add an initial water depth to the model with the following steps: Creating global 1D initial conditions field, containing an initial water depth of 1.0. Note that it is also possible to define the initial water depth per branch. Creating an initial field file containing the initial water depth data for our 1D network In [ ]: Copied! # Create 1D initial conditions field file ini_1d = OneDFieldModel () ini_1d . global_ = OneDFieldGlobal ( quantity = 'waterdepth' , unit = 'm' , value = 1.0 ) ini_1d . filepath = 'initialwaterdepth.ini' ini_1d . save ( export_dir / ini_1d . filepath ) # 1D field ini files needs to be saved seperately, because it is not completely supported yet) # Create initial field file ini_field_model = IniFieldModel () ini_field_model . filepath = 'inifield.ini' ini_field_model . initial = InitialField ( quantity = 'waterdepth' , datafile = ini_1d . filepath , datafiletype = DataFileType . onedfield ) # Assign data to the model model . geometry . inifieldfile = ini_field_model # Create 1D initial conditions field file ini_1d = OneDFieldModel() ini_1d.global_ = OneDFieldGlobal(quantity='waterdepth', unit='m', value=1.0) ini_1d.filepath = 'initialwaterdepth.ini' ini_1d.save(export_dir / ini_1d.filepath) # 1D field ini files needs to be saved seperately, because it is not completely supported yet) # Create initial field file ini_field_model = IniFieldModel() ini_field_model.filepath = 'inifield.ini' ini_field_model.initial = InitialField(quantity='waterdepth',datafile=ini_1d.filepath, datafiletype=DataFileType.onedfield) # Assign data to the model model.geometry.inifieldfile = ini_field_model 10. Adding a weir to a branch \u00b6 Many lakes occur close along Canal del Dique. See figure below. This tutorial assumes that these lakes can function as extra storage for the floods from the river. Hence a weir structure, functioning as a small dam, is added downstream of the lakes. This weir structure has the following conditions: It is located at 70 km from the upstream node of the branch (Channel_1D_1). The crest level is 4.0 m AD. The crest width is 105.0 m. The flow over the dam is in both directions.

    Exercise \ud83e\udde9 Create a new weir object with the described properties Create a new structure model and add the new weir to it Assign the data to the D-Flow FM model In [ ]: Copied! # Create weir structure weir = Weir ( id = 'fictive_dam' , name = 'fictive_dam' , branchId = 'Channel_1D_1' , chainage = 70000.0 , allowedFlowDir = FlowDirection . both , crestLevel = 4.0 , crestWidth = 105.0 , corrCoeff = 1.000 , useVelocityHeight = True ) # Create structure model structure_model = StructureModel () structure_model . filepath = 'structure.ini' # Append weir to structure structure_model . structure . append ( weir ) # Assign structure model to D-Flow FM model model . geometry . structurefile = [ structure_model ] # Create weir structure weir = Weir( id='fictive_dam', name = 'fictive_dam', branchId='Channel_1D_1', chainage=70000.0, allowedFlowDir=FlowDirection.both, crestLevel=4.0, crestWidth=105.0, corrCoeff=1.000, useVelocityHeight=True ) # Create structure model structure_model = StructureModel() structure_model.filepath = 'structure.ini' # Append weir to structure structure_model.structure.append(weir) # Assign structure model to D-Flow FM model model.geometry.structurefile = [structure_model] After creating the weir, you want to adjust some values. You found out that the dam should be significantly higher. Exercise \ud83e\udde9 Increase the crest level to 10.0 Change the flow direction to positive (from upstream to downstream) In [ ]: Copied! weir . crestlevel = 10.0 weir . allowedflowdir = FlowDirection . positive weir.crestlevel = 10.0 weir.allowedflowdir = FlowDirection.positive 11. Finishing up and saving the model \u00b6 The 1D model is almost finished now. We first change some time settings and then save the model. Exercise \ud83e\udde9 Export the full model to the export folder API references: FileModel.save() In [ ]: Copied! # Change some time settings model . time . refdate = '20120101' model . time . dtuser = 60. # seconds model . time . tstart = 43200. model . time . tstop = 561600. # Save the model model . save ( recurse = True ) # Change some time settings model.time.refdate = '20120101' model.time.dtuser = 60. # seconds model.time.tstart = 43200. model.time.tstop = 561600. # Save the model model.save(recurse=True) Part 2: Extending the 1D model to a 1D2D model \u00b6 We will now continue with the 1D model and add a 2D mesh to it. We won't add 1D2D coupling, but in practice they should be added to create a true 1D2D model. 12. Creating a 2D flexible mesh \u00b6 Here, we demonstrate how to create a 2D mesh using MeshKernel. \u26a0\ufe0f Network and mesh functionality in HYDROLIB-core is still in development. We use a shape file with the area of interest to define the extent of the new 2D mesh that is to be generated. First, a uniform rectilinear mesh with a grid cell size of 2500x2500m is generated. Second, we clip the generated mesh. API references: Mesh2d Mesh2d.clip() mk.MakeGridParameters In [ ]: Copied! # Read grid outline gdf_grid = gpd . read_file ( data_dir / 'outline_2D_grid.shp' ) # Determine the boundary box xmin , ymin , xmax , ymax = gdf_grid . geometry [ 0 ] . bounds mesh2d = Mesh2d () mesh_kernel = mesh2d . meshkernel # Define the grid generation parameters dx = 2500.0 dy = 2500.0 num_rows = int (( ymax - ymin ) / dy ) num_columns = int (( xmax - xmin ) / dx ) origin_x = xmin origin_y = ymin block_size_x = dx block_size_y = dy make_grid_parameters = MakeGridParameters () make_grid_parameters . num_columns = num_columns make_grid_parameters . num_rows = num_rows make_grid_parameters . origin_x = origin_x make_grid_parameters . origin_y = origin_y make_grid_parameters . block_size_x = dx make_grid_parameters . block_size_y = dy make_grid_parameters . upper_right_x = xmax make_grid_parameters . upper_right_y = ymax # Create uniform rectilinear mesh mesh_kernel . curvilinear_make_uniform ( make_grid_parameters ) mesh_kernel . curvilinear_convert_to_mesh2d () mesh2d . _process ( mesh2d . get_mesh2d ()) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np . array ( gdf_grid . geometry [ 0 ] . exterior . xy ) clip_geometry_list = GeometryList ( clip_polygon [ 0 ], clip_polygon [ 1 ]) mesh2d . clip ( clip_geometry_list ) model . geometry . netfile . network . _mesh2d = mesh2d model . geometry . netfile . filepath = \"FlowFM_1D2D_net.nc\" # Read grid outline gdf_grid = gpd.read_file(data_dir / 'outline_2D_grid.shp') # Determine the boundary box xmin, ymin, xmax, ymax = gdf_grid.geometry[0].bounds mesh2d = Mesh2d() mesh_kernel = mesh2d.meshkernel # Define the grid generation parameters dx=2500.0 dy=2500.0 num_rows = int((ymax - ymin) / dy) num_columns = int((xmax - xmin) / dx) origin_x = xmin origin_y = ymin block_size_x = dx block_size_y = dy make_grid_parameters = MakeGridParameters() make_grid_parameters.num_columns = num_columns make_grid_parameters.num_rows = num_rows make_grid_parameters.origin_x = origin_x make_grid_parameters.origin_y = origin_y make_grid_parameters.block_size_x = dx make_grid_parameters.block_size_y = dy make_grid_parameters.upper_right_x = xmax make_grid_parameters.upper_right_y = ymax # Create uniform rectilinear mesh mesh_kernel.curvilinear_make_uniform(make_grid_parameters) mesh_kernel.curvilinear_convert_to_mesh2d() mesh2d._process(mesh2d.get_mesh2d()) # Clip resulting mesh within polygon area of interest # Prepare a clipping polygon for MeshKernel input: clip_polygon = np.array(gdf_grid.geometry[0].exterior.xy) clip_geometry_list = GeometryList(clip_polygon[0],clip_polygon[1]) mesh2d.clip(clip_geometry_list) model.geometry.netfile.network._mesh2d = mesh2d model.geometry.netfile.filepath = \"FlowFM_1D2D_net.nc\" The cell below produces a basic plot of the 1D2D network. In [ ]: Copied! # Create a plot mesh2d_mk = network . _mesh2d . get_mesh2d () mesh1d_mk = network . _mesh1d . _get_mesh1d () figure , axis = plt . subplots () axis . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) mesh2d_mk . plot_edges ( ax = axis , color = \"orange\" ) mesh1d_mk . plot_edges ( ax = axis , color = 'blue' ) # Create a plot mesh2d_mk = network._mesh2d.get_mesh2d() mesh1d_mk = network._mesh1d._get_mesh1d() figure, axis = plt.subplots() axis.imshow(img, extent=[440000, 531544.97964175534434617, 1057000, 1228644.01383191486820579]) mesh2d_mk.plot_edges(ax=axis, color=\"orange\") mesh1d_mk.plot_edges(ax=axis, color='blue') 13. Refining the 2D grid locally \u00b6 Here, we want to refine the 2D mesh around the river using MeshKernel functionality. We will do one refinement iteration. Exercise \ud83e\udde9 Refine the 2D mesh using MeshKernel with the provided refinment parameters (see code below) API references: mk.MeshRefinementParameters mk.mesh2d_refine_based_on_polygon() (not documented yet): First argument is a GeometryList containing the polygon geometry of the area to refine Second argument is a MeshRefinementParameters containing all the parameters for refining In [ ]: Copied! # Get the refinement polygon to refine around the river gdf_refine = gpd . read_file ( data_dir / 'buffer_around_river_proj.shp' ) refine_polygon = np . array ( gdf_refine . geometry [ 0 ] . exterior . xy ) refine_geom = GeometryList ( refine_polygon [ 0 ], refine_polygon [ 1 ]) # Set parameters refine_intersected = True use_mass_center_when_refining = False min_edge_size = 10.0 refinement_type = 1 connect_hanging_nodes = True account_for_samples_outside_face = False max_refinement_iterations = 1 # Refine the 2D mesh parameters = mk . MeshRefinementParameters ( refine_intersected = refine_intersected , use_mass_center_when_refining = use_mass_center_when_refining , min_edge_size = min_edge_size , refinement_type = refinement_type , connect_hanging_nodes = connect_hanging_nodes , account_for_samples_outside_face = account_for_samples_outside_face , max_refinement_iterations = max_refinement_iterations , ) mesh_kernel . mesh2d_refine_based_on_polygon ( refine_geom , parameters ) # Set 2D mesh on model mesh2d . _process ( mesh2d . get_mesh2d ()) model . geometry . netfile . network . _mesh2d = mesh2d model . geometry . netfile . filepath = \"FlowFM_1D2D_refined_net.nc\" # Get the refinement polygon to refine around the river gdf_refine = gpd.read_file(data_dir / 'buffer_around_river_proj.shp') refine_polygon = np.array(gdf_refine.geometry[0].exterior.xy) refine_geom = GeometryList(refine_polygon[0], refine_polygon[1]) # Set parameters refine_intersected = True use_mass_center_when_refining = False min_edge_size = 10.0 refinement_type = 1 connect_hanging_nodes = True account_for_samples_outside_face = False max_refinement_iterations = 1 # Refine the 2D mesh parameters = mk.MeshRefinementParameters( refine_intersected=refine_intersected, use_mass_center_when_refining=use_mass_center_when_refining, min_edge_size=min_edge_size, refinement_type=refinement_type, connect_hanging_nodes=connect_hanging_nodes, account_for_samples_outside_face=account_for_samples_outside_face, max_refinement_iterations=max_refinement_iterations, ) mesh_kernel.mesh2d_refine_based_on_polygon(refine_geom, parameters) # Set 2D mesh on model mesh2d._process(mesh2d.get_mesh2d()) model.geometry.netfile.network._mesh2d = mesh2d model.geometry.netfile.filepath = \"FlowFM_1D2D_refined_net.nc\" In [ ]: Copied! # Create a plot mesh2d_mk = network . _mesh2d . get_mesh2d () mesh1d_mk = network . _mesh1d . _get_mesh1d () figure , axis = plt . subplots () axis . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) mesh2d_mk . plot_edges ( ax = axis , color = \"orange\" ) mesh1d_mk . plot_edges ( ax = axis , color = 'blue' ) # Create a plot mesh2d_mk = network._mesh2d.get_mesh2d() mesh1d_mk = network._mesh1d._get_mesh1d() figure, axis = plt.subplots() axis.imshow(img, extent=[440000, 531544.97964175534434617, 1057000, 1228644.01383191486820579]) mesh2d_mk.plot_edges(ax=axis, color=\"orange\") mesh1d_mk.plot_edges(ax=axis, color='blue') 14. Saving the 1D2D model \u00b6 The 1D2D model is now finished. Exercise \ud83e\udde9 Save the model wherever you like Import the D-Flow FM model in the Delft3D FM Suite 1D2D In [ ]: Copied! model . save ( recurse = True ) model.save(recurse=True)","title":"Creating a Delft3D FM 1D2D fluvial flood model of Magdalena river"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#creating-a-delft3d-fm-1d2d-fluvial-flood-model-of-magdalena-river","text":"The exercises in this notebook will serve as introduction on how to use HYDROLIB-core functionalities. We will create and adjust a Delft3D FM Suite 1D2D fluvial flood model of the Magdalena river in Columbia. First a 1D river model of the Magdalena river and Canal del Dique will be created, shown in the left figure. This model will be extended with a 2D Flexible Mesh, with a uniform roughness field. Adding a Digital Terrain Model (DTM) on that 2D mesh is currently not part of this tutorial, but in practice this is indispensible to mimic the fluvial flood patterns. Note that the model that will be created is for educational purposes and consists partially of fictive or unvalidated model data.","title":"Creating a Delft3D FM 1D2D fluvial flood model of Magdalena river"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#using-hydrolib-core-to-build-models","text":"HYDROLIB-core is a Python package that offers functionality to process D-HYDRO input files. It offers Python-wrapped classes that represent these files and their content. HYDROLIB-core serves as the basis for various pre- and postprocessing tools for a modelling workflow of hydrodynamic simulations in D-HYDRO. It can easily be used to build models and export the model files that can aftewards be run by dflowfm or other supported D-HYDRO kernels.","title":"Using HYDROLIB-core to build models"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#content-of-the-tutorial","text":"The goal of this tutorial is to familiarize modelers with applying HYDROLIB-core functionalities in their modelling procedures for building new models or adjusting existing models. As mentioned above, you will create an 1D2D fluvial flood model from scratch using the D-Flow FM HYDROLIB-core functionalities and the underlying functions from mesh generation ( MeshKernelPy ). We will walk through the following steps to build the model: Selecting the data location Creating an empty D-Flow FM model Reading the branch data from a shape file Creating and assigning a 1D computational grid to the model Adding cross-sections to the branches Adding cross-section definitions Adding roughness to the model Adding boundary conditions to the model Adding initial water depths Adding a weir to a branch Finishing up and saving the model Creating a 2D flexible mesh Refining the 2D grid locally Saving the 1D2D model","title":"Content of the tutorial"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#tips-for-working-in-the-jupyter-notebook","text":"Tab : Auto-complete on code Ctrl + Enter : Run cell Shift + Enter : Run cell and move to next cell","title":"\ud83d\udca1 Tips for working in the Jupyter Notebook"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#import-the-needed-modules","text":"Several Python packages are required to run the notebook. These packages are imported below. Please consult the HYDROLIB-core documentation if you want to use additional HYDROLIB-core functionalities later. In [ ]: Copied! # General import geopandas as gpd import matplotlib.pyplot as plt import numpy as np import pandas as pd from pathlib import Path # MeshKernel import meshkernel as mk from meshkernel import GeometryList , MakeGridParameters # HYDROLIB-core from hydrolib.core.dflowfm.mdu import FMModel , AutoStartOption from hydrolib.core.dflowfm.net.models import * from hydrolib.core.dflowfm.crosssection.models import CrossLocModel , CrossDefModel , YZCrsDef from hydrolib.core.dflowfm.friction.models import * from hydrolib.core.dflowfm.bc.models import * from hydrolib.core.dflowfm.ext.models import * from hydrolib.core.dflowfm.inifield.models import * from hydrolib.core.dflowfm.onedfield.models import * from hydrolib.core.dflowfm.structure.models import Weir , FlowDirection , StructureModel print ( \"Imports were successful!\" ) # General import geopandas as gpd import matplotlib.pyplot as plt import numpy as np import pandas as pd from pathlib import Path # MeshKernel import meshkernel as mk from meshkernel import GeometryList, MakeGridParameters # HYDROLIB-core from hydrolib.core.dflowfm.mdu import FMModel, AutoStartOption from hydrolib.core.dflowfm.net.models import * from hydrolib.core.dflowfm.crosssection.models import CrossLocModel, CrossDefModel, YZCrsDef from hydrolib.core.dflowfm.friction.models import * from hydrolib.core.dflowfm.bc.models import * from hydrolib.core.dflowfm.ext.models import * from hydrolib.core.dflowfm.inifield.models import * from hydrolib.core.dflowfm.onedfield.models import * from hydrolib.core.dflowfm.structure.models import Weir, FlowDirection, StructureModel print(\"Imports were successful!\")","title":"Import the needed modules"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#here-starts-the-tutorial","text":"","title":"Here starts the tutorial"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#1-selecting-the-data-location","text":"Exercise \ud83e\udde9: Create a variable that contains the Path to the data folder. In [ ]: Copied! root = Path . cwd () data_dir = root / 'data' print ( f \"Data location: { data_dir } \" ) root = Path.cwd() data_dir = root / 'data' print(f\"Data location: {data_dir}\")","title":"1. Selecting the data location"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#2-creating-an-empty-d-flow-fm-model","text":"To start a model from scratch, you first need to create an empty model without data. In this tutorial we will create a D-Flow FM model. The MDU file (master definition file) is the main input file of the D-Flow FM model. A new D-Flow FM model is constructed with the FMModel initializer. Exercise \ud83e\udde9 Create a variable containing a new FMModel object. Create a variable containing the export directory Export the D-Flow FM model to an MDU file inside the export directory API references: FMModel FileModel.filepath FileModel.save() In [ ]: Copied! model = FMModel () export_dir = root / 'export' model . filepath = export_dir / 'Magdalena_1D.mdu' # Save the MDU file model . save () print ( f \"MDU file saved: { model . filepath } \" ) model = FMModel() export_dir = root / 'export' model.filepath = export_dir / 'Magdalena_1D.mdu' # Save the MDU file model.save() print(f\"MDU file saved: {model.filepath}\")","title":"2. Creating an empty D-Flow FM model"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#part-1-setting-up-a-1d-delft3d-fm-model","text":"In this part we will build up the complete 1D model schematization step by step. At the end you should have a complete set of model input files for a 1D calculation.","title":"Part 1: Setting up a 1D Delft3D FM model"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#3-reading-the-branch-data-from-a-shape-file","text":"The model will include the lower part of the Magadalena from Cordoba Teton to the river mouth Baranquilla and the Canal del Dique. Exercise \ud83e\udde9 Read the branch data from the branches_Branches.shp file Print the branch data, such that we can answer the following questions: How many river branches does the model have? What are their names? Which friction type and friction value is used for each branch? API references: gpd.read_file In [ ]: Copied! # Read the branches branch_shp_file = data_dir / 'branches_Branches.shp' branches_gdf = gpd . read_file ( filename = branch_shp_file ) # Print the data print ( branches_gdf ) # Answers: # * 3 branches # * Channel_1D_1_A, Channel_1D_1_B and Channel_1D_1 # * Channel_1D_1_A: Manning, 0.03 # Channel_1D_1_B: Manning, 0.02 # Channel_1D_1 : Manning, 0.02 # Read the branches branch_shp_file = data_dir / 'branches_Branches.shp' branches_gdf = gpd.read_file(filename = branch_shp_file) # Print the data print(branches_gdf) # Answers: # * 3 branches # * Channel_1D_1_A, Channel_1D_1_B and Channel_1D_1 # * Channel_1D_1_A: Manning, 0.03 # Channel_1D_1_B: Manning, 0.02 # Channel_1D_1 : Manning, 0.02","title":"3. Reading the branch data from a shape file"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#4-creating-and-assigning-a-1d-computational-grid-to-the-model","text":"In the previous step we read the geometry and attributes of the branches from the shape file. This branch data will become the network input for our D-Flow FM model. Since the model does not have a network yet, we need to create a new network object and assign it to the model. A network may contain a 1D network, a 2D mesh and 1D2D links. Exercise \ud83e\udde9 Create a new network Assign the network to the model and assign a (relative) file path for the net file The new network should contain the data that we read from the shape file: Three Branch objects will need to be added to the network. For each branch, the name, geometry and computational grid points should be provided. The computational points are not included in the data, we will need to generate those with a grid point distance as specified: Branch name dx [m] Channel_1D_1_A 1000 Channel_1D_1_B 1000 Channel_1D_1 500 Hint \ud83d\udca1: The MDU file contains a [Geometry] section which has the network file reference, e.g.: [Geometry] netFile = FlowFM_net.nc ... API references: Network NetworkModel Branch Branch.generate_nodes() Network.mesh1d_add_branch() (undocumented): Adds a branch to the 1D network. The function needs two arguments: Branch : the branch to be added str : The name of the branch that is added In [ ]: Copied! # Assign a new network to the D-Flow FM model and specify the file path network = Network () model . geometry . netfile . network = network model . geometry . netfile . filepath = \"FlowFM_net.nc\" # Specify 1D computational grid point distance per branch dx_per_branch = { \"Channel_1D_1_A\" : 1000 , \"Channel_1D_1_B\" : 1000 , \"Channel_1D_1\" : 500 , } # Assign geometry of the branches and generate the computational grid on top of the branches. for index , branch_data in branches_gdf . iterrows (): branch_geometry = np . transpose ( branch_data . geometry . xy ) branch = Branch ( geometry = branch_geometry ) branch . generate_nodes ( mesh1d_edge_length = dx_per_branch [ branch_data . Name ]) network . mesh1d_add_branch ( branch , name = branch_data . Name ) network . _mesh1d . _set_mesh1d () # Assign a new network to the D-Flow FM model and specify the file path network = Network() model.geometry.netfile.network = network model.geometry.netfile.filepath = \"FlowFM_net.nc\" # Specify 1D computational grid point distance per branch dx_per_branch = { \"Channel_1D_1_A\" : 1000, \"Channel_1D_1_B\" : 1000, \"Channel_1D_1\" : 500, } # Assign geometry of the branches and generate the computational grid on top of the branches. for index, branch_data in branches_gdf.iterrows(): branch_geometry = np.transpose(branch_data.geometry.xy) branch = Branch(geometry=branch_geometry) branch.generate_nodes(mesh1d_edge_length=dx_per_branch[branch_data.Name]) network.mesh1d_add_branch(branch, name=branch_data.Name) network._mesh1d._set_mesh1d() We can plot the branches onto a background: In [ ]: Copied! # Create a figure with the 1D network figure , axis = plt . subplots ( ncols = 1 ) img = plt . imread ( data_dir / \"osm_background.png\" ) # Add branch names to the plot for branch_name , branch in network . _mesh1d . branches . items (): middle = int (( len ( branch . geometry ) - 1 ) / 2 ) xy = branch . geometry [ middle ] axis . text ( xy [ 0 ], xy [ 1 ], branch_name , ha = 'center' ) axis . imshow ( img , extent = [ 440000 , 531544.97964175534434617 , 1057000 , 1228644.01383191486820579 ]) network . _mesh1d . _get_mesh1d () . plot_edges ( ax = axis , color = 'blue' ) # Create a figure with the 1D network figure, axis = plt.subplots(ncols=1) img = plt.imread(data_dir / \"osm_background.png\") # Add branch names to the plot for branch_name, branch in network._mesh1d.branches.items(): middle = int((len(branch.geometry) - 1)/2) xy = branch.geometry[middle] axis.text(xy[0], xy[1], branch_name, ha='center') axis.imshow(img, extent=[440000, 531544.97964175534434617, 1057000, 1228644.01383191486820579]) network._mesh1d._get_mesh1d().plot_edges(ax=axis, color='blue')","title":"4. Creating and assigning a 1D computational grid to the model"},{"location":"tutorials/dsd_2023/magdalena_workflow/magdalena_workedout/#5-adding-cross-sections-to-the-branches","text":"In order to determine the flow area of the 1D model during the computation, you need cross-sections. These cross-sections are defined by two components: Cross-section locations Cross-section definitions The cross-section locations and cross-section definitions are exported to their own file. A cross-section location is defined by the following information: The cross-section ID A location, specified by a branch ID and a chainage. A shift, the vertical shift of the cross section profile. This is mainly used to create a good longitudinal slope over the 1D model (in case of shared cross-sections). A reference to the cross-section definition that is used at this location.

    A cross-section definition is defined by the following information: The cross-section definition ID The cross-section type: circle, rectangle, ZW river, ZW, YZ, XYZ Depending on the type of cross-section, a set of properties describing the properties of the profile shape

    In our data folder, there is a CSV file containing the cross-section locations. We want to convert this data to HYDROLIB-core cross-section location objects and add them to the D-Flow FM model. The columns in the CSV correspond exactly with the field names of a CrossSection class, making the conversion easy. Exercise \ud83e\udde9 Read the data from the CSV file Print the cross-section location data, to answer the following questions: How many cross-section does the model contain in total, and how many does each branch have? Do the cross-section have shared cross-section definitions? A shared cross-section definition is a definition used by more than one cross-section. Convert the CSV data (a pd.DataFrame) into HYDROLIB-core CrossSection objects Assign the cross section locations to the model Hint \ud83d\udca1: The MDU file contains a [Geometry] section which has the crossDefFile and crossLocFile reference, e.g.: [Geometry] crossDefFile = crsdef.ini crossLocFile = crsloc.ini ... API references: pd.read_csv() pd.to_dict() CrossLocModel CrossSection In [ ]: Copied! # Read the cross-sections from the CSV cross_section_data_file = data_dir / 'cross_section_locations.csv' cross_section_df = pd . read_csv ( cross_section_data_file , index_col = False ) # Print the data print ( cross_section_df ) # Answers: # * There are 6 cross-sections in the model and each branch has two cross-sections # * There are no shared cross-section definitions; each cross-section has a unique definition ID. # Assign the data to the model cross_loc_model = CrossLocModel () model . geometry . crosslocfile = cross_loc_model cross_loc_model . crosssection = cross_section_df . to_dict ( \"records\" ) # Read the cross-sections from the CSV cross_section_data_file = data_dir / 'cross_section_locations.csv' cross_section_df = pd.read_csv(cross_section_data_file, index_col=False) # Print the data print(cross_section_df) # Answers: # * There are 6 cross-sections in the model and each branch has two cross-sections # * There are no shared cross-section definitions; each cross-section has a unique definition ID. # Assign the data to the model cross_loc_model = CrossLocModel() model.geometry.crosslocfile = cross_loc_model cross_loc_model.crosssection = cross_section_df.to_dict(\"records\")","title":"5. Adding cross-sections to the branches"}]} \ No newline at end of file diff --git a/develop/sitemap.xml.gz b/develop/sitemap.xml.gz index 7cfd3e1a5..4eed9a5e2 100644 Binary files a/develop/sitemap.xml.gz and b/develop/sitemap.xml.gz differ