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# Sphinx build info version 1 | ||
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. | ||
config: 343d47b1cca2da89436b36abcb430701 | ||
tags: 645f666f9bcd5a90fca523b33c5a78b7 |
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Code Coverage | ||
============= | ||
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For an in detail report on the code coverage `click here <_static/codecov/index.html>`_. |
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======== | ||
Examples | ||
======== |
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=========================================== | ||
Neural Operators for Helmholtz Equation | ||
=========================================== | ||
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Welcome to the documentation for the Neural Operators for Helmholtz Equation project! This project focuses on the application of advanced neural operator techniques to solve the Helmholtz equation in various parameterized geometries. The approach integrates deep learning with physical modeling of domains. | ||
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Contents | ||
======== | ||
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.. toctree:: | ||
:maxdepth: 2 | ||
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coverage | ||
modules | ||
examples | ||
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Introduction | ||
============ | ||
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The Helmholtz equation is a fundamental partial differential equation in physics, particularly in the fields of acoustics, electromagnetics, and quantum mechanics. In this project, we develop and utilize neural operators, a form of deep learning model, to solve the Helmholtz equation across different parameterized geometries. This approach aims to overcome the limitations of traditional numerical methods, offering speed and flexibility for complex geometries. | ||
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API Reference | ||
============= | ||
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The :doc:`modules` section offers detailed descriptions of the functions, classes, and methods available in this project. | ||
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Examples | ||
======== | ||
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Explore practical applications and see the neural operators in action in the :doc:`examples` section. |
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nos | ||
=== | ||
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.. toctree:: | ||
:maxdepth: 4 | ||
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nos |
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nos.benchmarks package | ||
====================== | ||
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Submodules | ||
---------- | ||
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nos.benchmarks.benchmark module | ||
------------------------------- | ||
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.. automodule:: nos.benchmarks.benchmark | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: | ||
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nos.benchmarks.transmission\_loss module | ||
---------------------------------------- | ||
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.. automodule:: nos.benchmarks.transmission_loss | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: | ||
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Module contents | ||
--------------- | ||
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.. automodule:: nos.benchmarks | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: |
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nos.data package | ||
================ | ||
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Submodules | ||
---------- | ||
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nos.data.transmssion\_loss module | ||
--------------------------------- | ||
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.. automodule:: nos.data.transmssion_loss | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: | ||
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Module contents | ||
--------------- | ||
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.. automodule:: nos.data | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: |
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nos.metrics package | ||
=================== | ||
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Submodules | ||
---------- | ||
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nos.metrics.error\_metrics module | ||
--------------------------------- | ||
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.. automodule:: nos.metrics.error_metrics | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: | ||
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nos.metrics.metric module | ||
------------------------- | ||
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.. automodule:: nos.metrics.metric | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: | ||
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nos.metrics.operator\_metrics module | ||
------------------------------------ | ||
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.. automodule:: nos.metrics.operator_metrics | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: | ||
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Module contents | ||
--------------- | ||
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.. automodule:: nos.metrics | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: |
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nos.networks package | ||
==================== | ||
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Submodules | ||
---------- | ||
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nos.networks.residual module | ||
---------------------------- | ||
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.. automodule:: nos.networks.residual | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: | ||
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Module contents | ||
--------------- | ||
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.. automodule:: nos.networks | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: |
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nos.operators package | ||
===================== | ||
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Submodules | ||
---------- | ||
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nos.operators.deep\_dot\_operator module | ||
---------------------------------------- | ||
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.. automodule:: nos.operators.deep_dot_operator | ||
:members: | ||
:undoc-members: | ||
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nos.operators.deep\_root\_operator module | ||
----------------------------------------- | ||
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.. automodule:: nos.operators.deep_root_operator | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: | ||
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nos.operators.mean\_stack\_neural\_operator module | ||
-------------------------------------------------- | ||
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.. automodule:: nos.operators.mean_stack_neural_operator | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: | ||
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Module contents | ||
--------------- | ||
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.. automodule:: nos.operators | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: |
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nos package | ||
=========== | ||
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Subpackages | ||
----------- | ||
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.. toctree:: | ||
:maxdepth: 4 | ||
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nos.benchmarks | ||
nos.data | ||
nos.metrics | ||
nos.networks | ||
nos.operators | ||
nos.trainers | ||
nos.transforms | ||
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Module contents | ||
--------------- | ||
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.. automodule:: nos | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: |
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nos.trainers package | ||
==================== | ||
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Submodules | ||
---------- | ||
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nos.trainers.average\_metric module | ||
----------------------------------- | ||
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.. automodule:: nos.trainers.average_metric | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: | ||
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nos.trainers.trainer module | ||
--------------------------- | ||
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.. automodule:: nos.trainers.trainer | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: | ||
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Module contents | ||
--------------- | ||
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.. automodule:: nos.trainers | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: |
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nos.transforms package | ||
====================== | ||
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Submodules | ||
---------- | ||
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nos.transforms.scaling module | ||
----------------------------- | ||
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.. automodule:: nos.transforms.scaling | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: | ||
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Module contents | ||
--------------- | ||
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.. automodule:: nos.transforms | ||
:members: | ||
:undoc-members: | ||
:show-inheritance: |
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