From 5ed7f0d03209379b049e38065e3047163dd031f1 Mon Sep 17 00:00:00 2001 From: Huite Date: Fri, 4 Aug 2023 13:15:05 +0000 Subject: [PATCH] deploy: 233712dc7dfebb9f469697082a86f462a14d55ae --- .buildinfo | 2 +- .../vector_conversion.py | 28 ++++++ .../vector_conversion.ipynb | 20 ++++- _images/sphx_glr_connectivity_001.png | Bin 55334 -> 55357 bytes _images/sphx_glr_connectivity_002.png | Bin 22864 -> 22860 bytes _images/sphx_glr_connectivity_003.png | Bin 51949 -> 51931 bytes _images/sphx_glr_connectivity_thumb.png | Bin 23321 -> 23310 bytes _images/sphx_glr_disk_001.png | Bin 240107 -> 240107 bytes _images/sphx_glr_disk_thumb.png | Bin 51589 -> 51617 bytes _images/sphx_glr_plotting_001.png | Bin 62521 -> 62472 bytes _images/sphx_glr_plotting_003.png | Bin 142067 -> 142112 bytes _images/sphx_glr_plotting_004.png | Bin 12185 -> 12197 bytes _images/sphx_glr_plotting_005.png | Bin 149188 -> 149180 bytes _images/sphx_glr_plotting_006.png | Bin 356061 -> 356078 bytes _images/sphx_glr_plotting_007.png | Bin 141209 -> 141202 bytes _images/sphx_glr_plotting_008.png | Bin 44427 -> 44395 bytes _images/sphx_glr_plotting_009.png | Bin 62521 -> 62472 bytes _images/sphx_glr_plotting_thumb.png | Bin 39656 -> 39667 bytes _images/sphx_glr_quick_overview_002.png | Bin 52516 -> 52505 bytes _images/sphx_glr_vector_conversion_011.png | Bin 0 -> 194690 bytes _images/sphx_glr_voronoi_001.png | Bin 101002 -> 101000 bytes _images/sphx_glr_voronoi_002.png | Bin 109951 -> 109947 bytes _images/sphx_glr_voronoi_003.png | Bin 105005 -> 105004 bytes _images/sphx_glr_voronoi_004.png | Bin 102758 -> 102753 bytes _images/sphx_glr_voronoi_005.png | Bin 69828 -> 69823 bytes _images/sphx_glr_voronoi_006.png | Bin 199109 -> 199107 bytes _images/sphx_glr_voronoi_007.png | Bin 93798 -> 93796 bytes _images/sphx_glr_voronoi_thumb.png | Bin 27801 -> 27801 bytes _modules/xugrid/ugrid/snapping.html | 44 ++++----- .../examples-dev/sg_execution_times.rst.txt | 4 +- _sources/examples-dev/voronoi.rst.txt | 2 +- _sources/examples/connectivity.rst.txt | 24 ++--- _sources/examples/index.rst.txt | 18 ++-- _sources/examples/overlap_regridder.rst.txt | 10 +-- _sources/examples/partitioning.rst.txt | 18 ++-- _sources/examples/plotting.rst.txt | 68 +++++++------- _sources/examples/quick_overview.rst.txt | 84 +++++++++--------- _sources/examples/regridder_overview.rst.txt | 34 +++---- _sources/examples/sg_execution_times.rst.txt | 16 ++-- _sources/examples/vector_conversion.rst.txt | 74 ++++++++++++--- _sources/sample_data/adh_san_diego.rst.txt | 4 +- _sources/sample_data/disk.rst.txt | 4 +- _sources/sample_data/elevation_nl.rst.txt | 4 +- _sources/sample_data/provinces_nl.rst.txt | 2 +- .../sample_data/sg_execution_times.rst.txt | 12 +-- _sources/sample_data/xoxo.rst.txt | 2 +- examples-dev/sg_execution_times.html | 4 +- examples-dev/voronoi.html | 2 +- examples/connectivity.html | 24 ++--- examples/index.html | 6 +- examples/overlap_regridder.html | 10 +-- examples/partitioning.html | 18 ++-- examples/plotting.html | 68 +++++++------- examples/quick_overview.html | 84 +++++++++--------- examples/regridder_overview.html | 34 +++---- examples/sg_execution_times.html | 20 ++--- examples/vector_conversion.html | 49 +++++++--- sample_data/adh_san_diego.html | 4 +- sample_data/disk.html | 4 +- sample_data/elevation_nl.html | 4 +- sample_data/provinces_nl.html | 2 +- sample_data/sg_execution_times.html | 12 +-- sample_data/xoxo.html | 2 +- searchindex.js | 2 +- user_guide.html | 1 + 65 files changed, 478 insertions(+), 346 deletions(-) create mode 100644 _images/sphx_glr_vector_conversion_011.png diff --git a/.buildinfo b/.buildinfo index 1d8686efa..4961b7f92 100644 --- a/.buildinfo +++ b/.buildinfo @@ -1,4 +1,4 @@ # 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: 61a9ea2d2d65b3270ba2662df8d746e4 +config: 50a0ddf5282098ceba6fbdc22ecf30c8 tags: 645f666f9bcd5a90fca523b33c5a78b7 diff --git a/_downloads/714f83d87afaca41fed5d7f2c5f887d4/vector_conversion.py b/_downloads/714f83d87afaca41fed5d7f2c5f887d4/vector_conversion.py index 7a8cc6d50..e5ca75dcb 100644 --- a/_downloads/714f83d87afaca41fed5d7f2c5f887d4/vector_conversion.py +++ b/_downloads/714f83d87afaca41fed5d7f2c5f887d4/vector_conversion.py @@ -207,3 +207,31 @@ # result will essentially be one polygon per face. In such cases, it is more # efficient to use ``xugrid.UgridDataArray.to_geodataframe``, which directly # converts every face to a polygon. +# +# Snap to grid +# ------------ +# +# The examples above deal with data on the faces of the grid. However, data can +# also be associated with the nodes or edges of the grid. For example, we can +# snap line data to exactly follow the edges (the face boundaries): + +linestrings = gpd.GeoDataFrame(geometry=utrecht.exterior) +snapped_uds, snapped_gdf = xu.snap_to_grid(linestrings, uda, max_snap_distance=1.0) + +fig, ax = plt.subplots() +snapped_gdf.plot(ax=ax) +snapped_uds.ugrid.grid.plot(ax=ax, edgecolor="gray", linewidth=0.5) +utrecht.plot(ax=ax, edgecolor="red", facecolor="none", linewidth=0.75) +ax.set_xlim(xmin, xmax) +ax.set_ylim(ymin, ymax) + +# %% +# There are (arguably) many ways in which a linestring could be snapped to +# edges. The function above uses the criterion the following criterion: if a +# part of the linestring is located between the centroid of a face and the +# centroid of an edge, it is snapped to that edge. +# +# This sometimes result in less (visually) pleasing results, such as the two +# triangles in the lower left corner which are surrounded by the snapped edges. +# In general, results are best when the line segments are relatively large +# compare to the grid faces. diff --git a/_downloads/be05b5a234b2a85e0ca223679f6e137e/vector_conversion.ipynb b/_downloads/be05b5a234b2a85e0ca223679f6e137e/vector_conversion.ipynb index f17b64991..2a22d25d5 100644 --- a/_downloads/be05b5a234b2a85e0ca223679f6e137e/vector_conversion.ipynb +++ b/_downloads/be05b5a234b2a85e0ca223679f6e137e/vector_conversion.ipynb @@ -256,7 +256,25 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "We see that the results consists of two large polygons, in which the\ntriangles of the triangular grid have been merged to form a single polygon,\nand many smaller polygons, some of which correspond one to one to the\ntriangles of the grid.\n\n

Note

The produced polygon edges will follow exactly the face boundaries. When\n the data consists of many unique values (e.g. unbinned elevation data), the\n result will essentially be one polygon per face. In such cases, it is more\n efficient to use ``xugrid.UgridDataArray.to_geodataframe``, which directly\n converts every face to a polygon.

\n\n" + "We see that the results consists of two large polygons, in which the\ntriangles of the triangular grid have been merged to form a single polygon,\nand many smaller polygons, some of which correspond one to one to the\ntriangles of the grid.\n\n

Note

The produced polygon edges will follow exactly the face boundaries. When\n the data consists of many unique values (e.g. unbinned elevation data), the\n result will essentially be one polygon per face. In such cases, it is more\n efficient to use ``xugrid.UgridDataArray.to_geodataframe``, which directly\n converts every face to a polygon.

\n\n## Snap to grid\n\nThe examples above deal with data on the faces of the grid. However, data can\nalso be associated with the nodes or edges of the grid. For example, we can\nsnap line data to exactly follow the edges (the face boundaries):\n\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": { + "collapsed": false + }, + "outputs": [], + "source": [ + "linestrings = gpd.GeoDataFrame(geometry=utrecht.exterior)\nsnapped_uds, snapped_gdf = xu.snap_to_grid(linestrings, uda, max_snap_distance=1.0)\n\nfig, ax = plt.subplots()\nsnapped_gdf.plot(ax=ax)\nsnapped_uds.ugrid.grid.plot(ax=ax, edgecolor=\"gray\", linewidth=0.5)\nutrecht.plot(ax=ax, edgecolor=\"red\", facecolor=\"none\", linewidth=0.75)\nax.set_xlim(xmin, xmax)\nax.set_ylim(ymin, ymax)" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "There are (arguably) many ways in which a linestring could be snapped to\nedges. The function above uses the criterion the following criterion: if a\npart of the linestring is located between the centroid of a face and the\ncentroid of an edge, it is snapped to that edge.\n\nThis sometimes result in less (visually) pleasing results, such as the two\ntriangles in the lower left corner which are surrounded by the snapped edges.\nIn general, results are best when the line segments are relatively large\ncompare to the grid faces.\n\n" ] } ], diff --git a/_images/sphx_glr_connectivity_001.png b/_images/sphx_glr_connectivity_001.png index cc060d5aaebb707c106bff5f7e371fb49b99b3f1..e8ee8cd9147cf40d733d58f3dbd4efff30b5594f 100644 GIT binary patch literal 55357 zcmeFY^;eYL7dAem2+|ClLx&)pk~4&Kg9=Eev@mo@mo!L&NJYvDN@H=iXzh)ZW_0n?i*BPm=79E3b(HRMi5u!=iw{Gx{a8>oJ8D|L-6EUzGm;PYqkM_8`n(hfTLCRc4B4{=Q<5cU3b! z+M3`@&y(j?Qzg%-sHmKGr!a%DsrVRlAdt$4-HpuH5`$*S{XahgYHRs-rpu!3n(wt9 z#b5f?WrT!8w7ge#H%90mG%+_{3nH^^iDy=Sb9cDb71{pzIsPltK7zgZI{e9E?QT8S 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zj*Yh%yM(-r5MPlta#XFwOZ3~;=MO)x%UcEoab1C`c< zHUa8UEl`8`&9W*Ep7_jQg*JYZ%?Wk?7v^6ghAMv=Y@QfaW?30s;j4yT>zYvJP_9*V ztpGmDB>TM&43dV^`y5d#{)VJGjM=v=n<~p0J?rH*I_OajzQ0cY){<{s;lqTxh+2Jz zFIqsD)+Y-}FQt-CzA>5l6mH>w$WO%g#S=#@`(nFWede00r zkG8ni(@>g&f$i5<^9mjkHMtL+z|JZgp~|E-p7~TiFZ7bAPK7G{3~Z6OlugspB%IQO zxtJcKh-+GbERO}0S8~h>B{ci1wfQ=hU<}@5TmzfTaS|LX4)p}b2sF7r53-IAO^E88%Mj>4|p1-~T`}==`Z8aCP0J!XaYsJq51M;Z1C^^rKh!Z8%+;)?Qs|c6ULF zkaePjRWk&fq$!=Z5`^A~o(%Ad1}

     import numpy as np
     import pandas as pd
     import xarray as xr
    -from numba_celltree import CellTree2d
     from scipy import sparse
     from scipy.sparse.csgraph import connected_components
     from scipy.spatial import cKDTree
    @@ -599,8 +598,8 @@ 

    Source code for xugrid.ugrid.snapping

     def coerce_geometry(lines: GeoDataFrameType) -> LineArray:
         geometry = lines.geometry.values
         geom_type = shapely.get_type_id(geometry)
    -    if not (geom_type == 1).all():
    -        raise ValueError("Geometry should contain only LineStrings")
    +    if not ((geom_type == 1) | (geom_type == 2)).all():
    +        raise ValueError("Geometry should contain only LineStrings and/or LinearRings")
         return geometry
     
     
    @@ -711,12 +710,12 @@ 

    Source code for xugrid.ugrid.snapping

         vertices,
         edge_node_connectivity,
         edges,
    -    line_index,
    +    shapely_index,
     ):
         edge_vertices = vertices[edge_node_connectivity[edges]]
         geometry = shapely.linestrings(edge_vertices)
         return gpd.GeoDataFrame(
    -        lines.drop(columns="geometry").iloc[line_index], geometry=geometry
    +        lines.drop(columns="geometry").iloc[shapely_index], geometry=geometry
         )
     
     
    @@ -761,29 +760,28 @@ 

    Source code for xugrid.ugrid.snapping

             topology = grid.ugrid.grid
         else:
             raise TypeError(
    -            f"Expected xarray.DataArray or xugrid.UgridDataArray, received: {type(grid).__name__}"
    +            "Expected xarray.DataArray or xugrid.UgridDataArray, received: "
    +            f" {type(grid).__name__}"
             )
     
         vertices = topology.node_coordinates
    -    faces = topology.face_node_connectivity
    -
    -    # Derive connectivity
    -    edge_node_connectivity, face_edge_connectivity = connectivity.edge_connectivity(
    -        faces, -1
    -    )
    +    edge_centroids = topology.edge_coordinates
    +    edge_node_connectivity = topology.edge_node_connectivity
    +    face_edge_connectivity = topology.face_edge_connectivity
         A = connectivity.to_sparse(face_edge_connectivity, fill_value=-1)
         n, m = A.shape
         face_edge_connectivity = AdjacencyMatrix(A.indices, A.indptr, A.nnz, n, m)
     
         # Create geometric data
    -    edge_centroids = vertices[edge_node_connectivity].mean(axis=1)
         line_geometry = coerce_geometry(lines)
    -    line_coords, line_index = shapely.get_coordinates(line_geometry, return_index=True)
    +    line_coords, shapely_index = shapely.get_coordinates(
    +        line_geometry, return_index=True
    +    )
         # Snap line_coords to grid
         x, y = snap_to_nodes(
             *line_coords.T, *vertices.T, max_snap_distance, tiebreaker="nearest"
         )
    -    line_edges = lines_as_edges(np.column_stack([x, y]), line_index)
    +    line_edges = lines_as_edges(np.column_stack([x, y]), shapely_index)
     
         # Search for intersections. Every edge is potentially divided into smaller
         # segments: The segment_indices contain (repeated) values of the
    @@ -792,8 +790,9 @@ 

    Source code for xugrid.ugrid.snapping

         # * face_indices: for each segment, the index of the topology face.
         # * segment_edges: for each segment, start and end xy-coordinates.
         #
    -    celltree = CellTree2d(vertices, faces, -1)
    -    line_index, face_indices, segment_edges = celltree.intersect_edges(line_edges)
    +    line_index, face_indices, segment_edges = topology.celltree.intersect_edges(
    +        line_edges
    +    )
     
         # Create edges from the intersected lines a: line can only snap to N - 1
         # edges for N edges of a face. Pre-allocate the arrays here. For some
    @@ -801,8 +800,10 @@ 

    Source code for xugrid.ugrid.snapping

         # this module (!).
         # TODO: investigate...
         #
    -    # * edge_index: which
    -    max_n_new_edges = len(face_indices) * (faces.shape[1] - 1)
    +    # * edge_index: which edge of the topology (may contain duplicates)
    +    # * segment_index: which segment
    +
    +    max_n_new_edges = len(face_indices) * topology.n_max_node_per_face - 1
         edge_index = np.empty(max_n_new_edges, dtype=IntDType)
         segment_index = np.empty(max_n_new_edges, dtype=IntDType)
         edge_index, segment_index = snap_to_edges(
    @@ -820,9 +821,12 @@ 

    Source code for xugrid.ugrid.snapping

         # When multiple line parts are snapped to the same edge, use the ones with
         # the greatest length inside the cell.
         edges, line_index = _find_largest_edges(segment_edges, edge_index, line_index)
    +    shapely_index = shapely_index[line_index]
     
         uds = _create_output_dataset(lines, topology, edges, line_index)
    -    gdf = _create_output_gdf(lines, vertices, edge_node_connectivity, edges, line_index)
    +    gdf = _create_output_gdf(
    +        lines, vertices, edge_node_connectivity, edges, shapely_index
    +    )
         return uds, gdf
    diff --git a/_sources/examples-dev/sg_execution_times.rst.txt b/_sources/examples-dev/sg_execution_times.rst.txt index e06f92877..fdd966607 100644 --- a/_sources/examples-dev/sg_execution_times.rst.txt +++ b/_sources/examples-dev/sg_execution_times.rst.txt @@ -6,8 +6,8 @@ Computation times ================= -**00:02.310** total execution time for **examples-dev** files: +**00:01.578** total execution time for **examples-dev** files: +----------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples-dev_voronoi.py` (``voronoi.py``) | 00:02.310 | 0.0 MB | +| :ref:`sphx_glr_examples-dev_voronoi.py` (``voronoi.py``) | 00:01.578 | 0.0 MB | +----------------------------------------------------------+-----------+--------+ diff --git a/_sources/examples-dev/voronoi.rst.txt b/_sources/examples-dev/voronoi.rst.txt index db30f98f7..0d2fa703d 100644 --- a/_sources/examples-dev/voronoi.rst.txt +++ b/_sources/examples-dev/voronoi.rst.txt @@ -630,7 +630,7 @@ The figure shows: .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 2.310 seconds) + **Total running time of the script:** ( 0 minutes 1.578 seconds) .. _sphx_glr_download_examples-dev_voronoi.py: diff --git a/_sources/examples/connectivity.rst.txt b/_sources/examples/connectivity.rst.txt index 363eb2914..66ffd0554 100644 --- a/_sources/examples/connectivity.rst.txt +++ b/_sources/examples/connectivity.rst.txt @@ -129,7 +129,7 @@ By default, the border value for binary erosion is set to ``False`` (equal to .. code-block:: none - + @@ -165,7 +165,7 @@ start by setting a single value in the center of the grid to ``True``. .. code-block:: none - + @@ -200,7 +200,7 @@ alternative border value: .. code-block:: none - + @@ -238,7 +238,7 @@ analyse connected parts of the mesh. .. code-block:: none - + @@ -272,7 +272,7 @@ Tesselation. .. code-block:: none - + @@ -316,7 +316,7 @@ the original. .. code-block:: none - + @@ -355,7 +355,7 @@ We can break down one of the Voronoi tesselations from above into triangles: .. code-block:: none - + @@ -409,7 +409,7 @@ the upper and lower parts: .. code-block:: none - + @@ -439,7 +439,7 @@ We can now use Laplace interpolation to fill the gaps in the grid. .. code-block:: none - + @@ -480,7 +480,7 @@ To illustrate, let's take a look at the connectivity matrix of the Xoxo grid. .. code-block:: none - + @@ -516,14 +516,14 @@ locality: .. code-block:: none - + .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 2.363 seconds) + **Total running time of the script:** ( 0 minutes 1.613 seconds) .. _sphx_glr_download_examples_connectivity.py: diff --git a/_sources/examples/index.rst.txt b/_sources/examples/index.rst.txt index fa00ca14b..7f35beb1e 100644 --- a/_sources/examples/index.rst.txt +++ b/_sources/examples/index.rst.txt @@ -102,35 +102,35 @@ notebook for interactive exploration. .. raw:: html -
    +
    .. only:: html - .. image:: /examples/images/thumb/sphx_glr_vector_conversion_thumb.png + .. image:: /examples/images/thumb/sphx_glr_regridder_overview_thumb.png :alt: - :ref:`sphx_glr_examples_vector_conversion.py` + :ref:`sphx_glr_examples_regridder_overview.py` .. raw:: html -
    Vector geometry conversion
    +
    Regridding overview
    .. raw:: html -
    +
    .. only:: html - .. image:: /examples/images/thumb/sphx_glr_regridder_overview_thumb.png + .. image:: /examples/images/thumb/sphx_glr_vector_conversion_thumb.png :alt: - :ref:`sphx_glr_examples_regridder_overview.py` + :ref:`sphx_glr_examples_vector_conversion.py` .. raw:: html -
    Regridding overview
    +
    Vector geometry conversion
    @@ -147,8 +147,8 @@ notebook for interactive exploration. /examples/plotting /examples/overlap_regridder /examples/connectivity - /examples/vector_conversion /examples/regridder_overview + /examples/vector_conversion diff --git a/_sources/examples/overlap_regridder.rst.txt b/_sources/examples/overlap_regridder.rst.txt index 0e75c85fd..82f16aedf 100644 --- a/_sources/examples/overlap_regridder.rst.txt +++ b/_sources/examples/overlap_regridder.rst.txt @@ -114,7 +114,7 @@ some bathymetry) of the Netherlands, and a coarser target grid. .. code-block:: none - + @@ -204,7 +204,7 @@ conservative methods, such as conductance: .. code-block:: none - + @@ -282,7 +282,7 @@ To use our custom method, we provide at initialization of the OverlapRegridder: .. code-block:: none - + @@ -322,7 +322,7 @@ function can deal with NaN values! -- hence ``nanpercentile`` rather than .. code-block:: none - + @@ -333,7 +333,7 @@ function can deal with NaN values! -- hence ``nanpercentile`` rather than .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 6.988 seconds) + **Total running time of the script:** ( 0 minutes 5.197 seconds) .. _sphx_glr_download_examples_overlap_regridder.py: diff --git a/_sources/examples/partitioning.rst.txt b/_sources/examples/partitioning.rst.txt index c742e45d6..34f085924 100644 --- a/_sources/examples/partitioning.rst.txt +++ b/_sources/examples/partitioning.rst.txt @@ -76,7 +76,7 @@ into several parts. .. code-block:: none - + @@ -145,7 +145,7 @@ We can easily plot this data to visualize the partitions: .. code-block:: none - + @@ -213,7 +213,7 @@ merge these partitions back into one whole for post-processing: .. code-block:: none - + @@ -275,7 +275,7 @@ data: .. code-block:: none - + @@ -667,7 +667,7 @@ Note that partioning and merging does not preserve order!
    <xarray.DataArray 'elevation' (mesh2d_nFaces: 5248)>
         array([False, False, False, ..., False, False, False])
         Coordinates:
    -      * mesh2d_nFaces  (mesh2d_nFaces) int64 0 1 2 3 4 ... 5243 5244 5245 5246 5247
    + * mesh2d_nFaces (mesh2d_nFaces) int64 0 1 2 3 4 ... 5243 5244 5245 5246 5247


    @@ -1071,9 +1071,9 @@ reorder the data after merging. Coordinates: mesh2d_face_x (mesh2d_nFaces) float64 2.388e+04 1.86e+05 ... 3.03e+04 mesh2d_face_y (mesh2d_nFaces) float64 3.648e+05 4.171e+05 ... 3.964e+05 - * mesh2d_nFaces (mesh2d_nFaces) int64 0 1 2 3 4 ... 5243 5244 5245 5246 5247
    + * mesh2d_nFaces (mesh2d_nFaces) int64 0 1 2 3 4 ... 5243 5244 5245 5246 5247


    @@ -1090,7 +1090,7 @@ partitions. .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 7.265 seconds) + **Total running time of the script:** ( 0 minutes 4.838 seconds) .. _sphx_glr_download_examples_partitioning.py: diff --git a/_sources/examples/plotting.rst.txt b/_sources/examples/plotting.rst.txt index 047e8b31f..0e8fdc6e0 100644 --- a/_sources/examples/plotting.rst.txt +++ b/_sources/examples/plotting.rst.txt @@ -456,7 +456,7 @@ faces. Data variables: node_z (mesh2d_nNodes) float64 1.933 2.091 1.875 ... 5.688 7.491 face_z (mesh2d_nFaces) float64 1.737 1.918 2.269 ... 5.408 6.424 - edge_z (mesh2d_nEdges) float64 1.989 1.875 1.8 ... 3.929 4.909 6.544

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z

    • mesh2d_nEdges
      PandasIndex
      PandasIndex(RangeIndex(start=0, stop=600, step=1, name='mesh2d_nEdges'))
    • mesh2d_nNodes
      PandasIndex
      PandasIndex(RangeIndex(start=0, stop=217, step=1, name='mesh2d_nNodes'))
    • mesh2d_nFaces
      PandasIndex
      PandasIndex(RangeIndex(start=0, stop=384, step=1, name='mesh2d_nFaces'))


  • @@ -611,7 +611,7 @@ Dataset and calling the :py:meth:`UgridDataArray.ugrid.plot()` method. .. code-block:: none - + @@ -646,7 +646,7 @@ the edges results in a different kind of plot: .. code-block:: none - + @@ -688,7 +688,7 @@ We can put them side by side to illustrate the differences: .. code-block:: none - + @@ -718,7 +718,7 @@ filled contours for data associated with the face dimension: .. code-block:: none - + @@ -749,7 +749,7 @@ We can also overlay this data with the edges: .. code-block:: none - + @@ -824,7 +824,7 @@ All these (2D) plots are illustrated here for completeness' sake: .. code-block:: none - + @@ -857,7 +857,7 @@ The ``surface`` methods generate 3D surface plots: .. code-block:: none - + @@ -891,7 +891,7 @@ used: .. code-block:: none - + @@ -927,7 +927,7 @@ take an xarray DataArray and a xugrid grid as arguments. .. code-block:: none - + @@ -963,14 +963,14 @@ somewhere in the unstructured topology, and plot the resulting timeseries: .. code-block:: none - [] + [] .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 19.199 seconds) + **Total running time of the script:** ( 0 minutes 14.685 seconds) .. _sphx_glr_download_examples_plotting.py: diff --git a/_sources/examples/quick_overview.rst.txt b/_sources/examples/quick_overview.rst.txt index 89f3c19a8..1a3d5d442 100644 --- a/_sources/examples/quick_overview.rst.txt +++ b/_sources/examples/quick_overview.rst.txt @@ -464,7 +464,7 @@ We'll start by fetching a dataset: elevation (node) float64 ... depth (time, node) float64 ... mesh2d int32 ... - face_node_connectivity (face, nmax_face) float64 ...


  • @@ -919,7 +919,7 @@ separate the variables: node_y (node) float64 ... Data variables: elevation (node) float64 ... - depth (time, node) float64 ...


  • @@ -1361,7 +1361,7 @@ We can then grab one of the data variables as usual for xarray: Coordinates: * node (node) int64 0 1 2 3 4 5 6 7 ... 9133 9134 9135 9136 9137 9138 9139 node_x (node) float64 ... - node_y (node) float64 ... + node_y (node) float64 ...

    @@ -1771,7 +1771,7 @@ some data by hand here:
    <xarray.DataArray (mesh2d_nFaces: 2)>
         array([1., 2.])
         Coordinates:
    -      * mesh2d_nFaces  (mesh2d_nFaces) int64 0 1
    + * mesh2d_nFaces (mesh2d_nFaces) int64 0 1

    @@ -1809,7 +1809,7 @@ Plotting .. code-block:: none - + @@ -1860,7 +1860,7 @@ To select based on the topology, use the ``.ugrid`` attribute: .. code-block:: none - + @@ -2258,7 +2258,7 @@ Computation on DataArrays is unchanged from xarray:
    <xarray.DataArray (mesh2d_nFaces: 2)>
         array([11., 12.])
         Coordinates:
    -      * mesh2d_nFaces  (mesh2d_nFaces) int64 0 1
    + * mesh2d_nFaces (mesh2d_nFaces) int64 0 1

    @@ -2720,7 +2720,7 @@ Conversion from Geopandas is easy too: Coordinates: * mesh2d_nFaces (mesh2d_nFaces) int64 0 1 Data variables: - test (mesh2d_nFaces) float64 1.0 2.0 + test (mesh2d_nFaces) float64 1.0 2.0

    @@ -3122,7 +3122,7 @@ grid (nodes, faces, edges). Data variables: node_z (mesh2d_nNodes) float64 1.933 2.091 1.875 ... 5.688 7.491 face_z (mesh2d_nFaces) float64 1.737 1.918 2.269 ... 5.408 6.424 - edge_z (mesh2d_nEdges) float64 1.989 1.875 1.8 ... 3.929 4.909 6.544
    • mesh2d_nEdges
      PandasIndex
      PandasIndex(RangeIndex(start=0, stop=600, step=1, name='mesh2d_nEdges'))
    • mesh2d_nNodes
      PandasIndex
      PandasIndex(RangeIndex(start=0, stop=217, step=1, name='mesh2d_nNodes'))
    • mesh2d_nFaces
      PandasIndex
      PandasIndex(RangeIndex(start=0, stop=384, step=1, name='mesh2d_nFaces'))


  • @@ -3634,7 +3634,7 @@ a grid object:
    <xarray.Dataset>
         Dimensions:  ()
         Data variables:
    -        *empty*
    + *empty*

    @@ -4029,7 +4029,7 @@ We can then add variables one-by-one, as we might with an xarray Dataset: node_x (node) float64 ... node_y (node) float64 ... Data variables: - elevation (node) float64 ... + elevation (node) float64 ...

    @@ -4434,7 +4434,7 @@ before writing. elevation (node) float64 ... depth (time, node) float64 ... Attributes: - Conventions: CF-1.8 UGRID-1.0
  • Conventions :
    CF-1.8 UGRID-1.0


  • @@ -4495,7 +4495,7 @@ before writing. .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 1.016 seconds) + **Total running time of the script:** ( 0 minutes 0.726 seconds) .. _sphx_glr_download_examples_quick_overview.py: diff --git a/_sources/examples/regridder_overview.rst.txt b/_sources/examples/regridder_overview.rst.txt index b1acf86e7..a062628be 100644 --- a/_sources/examples/regridder_overview.rst.txt +++ b/_sources/examples/regridder_overview.rst.txt @@ -79,7 +79,7 @@ elevation of the Netherlands. .. code-block:: none - + @@ -153,7 +153,7 @@ the centroids of the new grid fall. .. code-block:: none - + @@ -184,7 +184,7 @@ Rexgrid provides the CentroidLocatorRegridder for this: .. code-block:: none - + @@ -219,7 +219,7 @@ so large. Let's try the OverlapOverregridder instead. .. code-block:: none - + @@ -251,7 +251,7 @@ Let's try again, now with the minimum: .. code-block:: none - + @@ -282,7 +282,7 @@ Or the maximum: .. code-block:: none - + @@ -711,7 +711,7 @@ result. mesh2d_face_x (mesh2d_nFaces) float64 ... mesh2d_face_y (mesh2d_nFaces) float64 ... * mesh2d_nFaces (mesh2d_nFaces) int64 0 1 2 3 4 ... 5243 5244 5245 5246 5247 - * layer (layer) int64 1 2 3 4 5
    • mesh2d_face_x
      (mesh2d_nFaces)
      float64
      ...
      standard_name :
      projection_x_coordinate
      [5248 values with dtype=float64]
    • mesh2d_face_y
      (mesh2d_nFaces)
      float64
      ...
      standard_name :
      projection_y_coordinate
      [5248 values with dtype=float64]
    • mesh2d_nFaces
      (mesh2d_nFaces)
      int64
      0 1 2 3 4 ... 5244 5245 5246 5247
      array([   0,    1,    2, ..., 5245, 5246, 5247])
    • layer
      (layer)
      int64
      1 2 3 4 5
      array([1, 2, 3, 4, 5])
    • mesh2d_nFaces
      PandasIndex
      PandasIndex(RangeIndex(start=0, stop=5248, step=1, name='mesh2d_nFaces'))
    • layer
      PandasIndex
      PandasIndex(Index([1, 2, 3, 4, 5], dtype='int64', name='layer'))


  • @@ -1153,7 +1153,7 @@ all additional dimensions. -45.92794405, -39.50867478]]) Coordinates: * layer (layer) int64 1 2 3 4 5 - * mesh2d_nFaces (mesh2d_nFaces) int64 0 1 2 3 4 5 6 ... 91 92 93 94 95 96 97
    • layer
      PandasIndex
      PandasIndex(Index([1, 2, 3, 4, 5], dtype='int64', name='layer'))
    • mesh2d_nFaces
      PandasIndex
      PandasIndex(RangeIndex(start=0, stop=98, step=1, name='mesh2d_nFaces'))


  • @@ -1235,7 +1235,7 @@ and the aggregated mean. .. code-block:: none - [, , , , ] + [, , , , ] @@ -1272,7 +1272,7 @@ To illustrate, we will zoom in to a part of the Netherlands. .. code-block:: none - + @@ -1325,7 +1325,7 @@ the triangles. .. code-block:: none - + @@ -1366,7 +1366,7 @@ the regridders work for any collection of (convex) faces. .. code-block:: none - + @@ -1402,7 +1402,7 @@ is kept the same. .. code-block:: none - + @@ -1418,7 +1418,7 @@ is kept the same. .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 12.884 seconds) + **Total running time of the script:** ( 0 minutes 10.266 seconds) .. _sphx_glr_download_examples_regridder_overview.py: diff --git a/_sources/examples/sg_execution_times.rst.txt b/_sources/examples/sg_execution_times.rst.txt index 9466282b8..d2fece55e 100644 --- a/_sources/examples/sg_execution_times.rst.txt +++ b/_sources/examples/sg_execution_times.rst.txt @@ -6,20 +6,20 @@ Computation times ================= -**01:15.798** total execution time for **examples** files: +**00:58.456** total execution time for **examples** files: +----------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_vector_conversion.py` (``vector_conversion.py``) | 00:26.083 | 0.0 MB | +| :ref:`sphx_glr_examples_vector_conversion.py` (``vector_conversion.py``) | 00:21.131 | 0.0 MB | +----------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_plotting.py` (``plotting.py``) | 00:19.199 | 0.0 MB | +| :ref:`sphx_glr_examples_plotting.py` (``plotting.py``) | 00:14.685 | 0.0 MB | +----------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_regridder_overview.py` (``regridder_overview.py``) | 00:12.884 | 0.0 MB | +| :ref:`sphx_glr_examples_regridder_overview.py` (``regridder_overview.py``) | 00:10.266 | 0.0 MB | +----------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_partitioning.py` (``partitioning.py``) | 00:07.265 | 0.0 MB | +| :ref:`sphx_glr_examples_overlap_regridder.py` (``overlap_regridder.py``) | 00:05.197 | 0.0 MB | +----------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_overlap_regridder.py` (``overlap_regridder.py``) | 00:06.988 | 0.0 MB | +| :ref:`sphx_glr_examples_partitioning.py` (``partitioning.py``) | 00:04.838 | 0.0 MB | +----------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_connectivity.py` (``connectivity.py``) | 00:02.363 | 0.0 MB | +| :ref:`sphx_glr_examples_connectivity.py` (``connectivity.py``) | 00:01.613 | 0.0 MB | +----------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_quick_overview.py` (``quick_overview.py``) | 00:01.016 | 0.0 MB | +| :ref:`sphx_glr_examples_quick_overview.py` (``quick_overview.py``) | 00:00.726 | 0.0 MB | +----------------------------------------------------------------------------+-----------+--------+ diff --git a/_sources/examples/vector_conversion.rst.txt b/_sources/examples/vector_conversion.rst.txt index db48346ba..bad121499 100644 --- a/_sources/examples/vector_conversion.rst.txt +++ b/_sources/examples/vector_conversion.rst.txt @@ -73,7 +73,7 @@ We'll once again use the surface elevation data example. .. code-block:: none - + @@ -518,9 +518,9 @@ GeoDataFrame. Data variables: elevation (mesh2d_nFaces) float32 1.17 9.81 54.04 ... 0.28 -15.83 -0.45 mesh2d_face_x (mesh2d_nFaces) float64 2.388e+04 1.86e+05 ... 3.03e+04 - mesh2d_face_y (mesh2d_nFaces) float64 3.648e+05 4.171e+05 ... 3.964e+05 + mesh2d_face_y (mesh2d_nFaces) float64 3.648e+05 4.171e+05 ... 3.964e+05

    @@ -582,7 +582,7 @@ burn into the grid. .. code-block:: none - + @@ -978,9 +978,9 @@ we want to compute the average surface elevation per province: Coordinates: * id (id) float64 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 Attributes: - unit: m NAP
    • id
      (id)
      float64
      0.0 1.0 2.0 3.0 ... 9.0 10.0 11.0
      array([ 0.,  1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11.])
    • id
      PandasIndex
      PandasIndex(Index([0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0], dtype='float64', name='id'))
  • unit :
    m NAP


  • @@ -1087,7 +1087,7 @@ We can also use such "masks" to e.g. modify specific parts of the grid data: .. code-block:: none - + @@ -1233,7 +1233,7 @@ burn operation. .. code-block:: none - + @@ -1273,7 +1273,7 @@ above the boundary of 5 m above mean sea level: -.. GENERATED FROM PYTHON SOURCE LINES 199-210 +.. GENERATED FROM PYTHON SOURCE LINES 199-217 We see that the results consists of two large polygons, in which the triangles of the triangular grid have been merged to form a single polygon, @@ -1287,10 +1287,62 @@ triangles of the grid. efficient to use ``xugrid.UgridDataArray.to_geodataframe``, which directly converts every face to a polygon. +Snap to grid +------------ + +The examples above deal with data on the faces of the grid. However, data can +also be associated with the nodes or edges of the grid. For example, we can +snap line data to exactly follow the edges (the face boundaries): + +.. GENERATED FROM PYTHON SOURCE LINES 217-228 + +.. code-block:: default + + + linestrings = gpd.GeoDataFrame(geometry=utrecht.exterior) + snapped_uds, snapped_gdf = xu.snap_to_grid(linestrings, uda, max_snap_distance=1.0) + + fig, ax = plt.subplots() + snapped_gdf.plot(ax=ax) + snapped_uds.ugrid.grid.plot(ax=ax, edgecolor="gray", linewidth=0.5) + utrecht.plot(ax=ax, edgecolor="red", facecolor="none", linewidth=0.75) + ax.set_xlim(xmin, xmax) + ax.set_ylim(ymin, ymax) + + + + +.. image-sg:: /examples/images/sphx_glr_vector_conversion_011.png + :alt: vector conversion + :srcset: /examples/images/sphx_glr_vector_conversion_011.png + :class: sphx-glr-single-img + + +.. rst-class:: sphx-glr-script-out + + .. code-block:: none + + + (428343.70545104187, 489587.5779869387) + + + +.. GENERATED FROM PYTHON SOURCE LINES 229-238 + +There are (arguably) many ways in which a linestring could be snapped to +edges. The function above uses the criterion the following criterion: if a +part of the linestring is located between the centroid of a face and the +centroid of an edge, it is snapped to that edge. + +This sometimes result in less (visually) pleasing results, such as the two +triangles in the lower left corner which are surrounded by the snapped edges. +In general, results are best when the line segments are relatively large +compare to the grid faces. + .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 26.083 seconds) + **Total running time of the script:** ( 0 minutes 21.131 seconds) .. _sphx_glr_download_examples_vector_conversion.py: diff --git a/_sources/sample_data/adh_san_diego.rst.txt b/_sources/sample_data/adh_san_diego.rst.txt index 0bd87c31b..17511694e 100644 --- a/_sources/sample_data/adh_san_diego.rst.txt +++ b/_sources/sample_data/adh_san_diego.rst.txt @@ -41,7 +41,7 @@ It contains a static dataset (bed elevation) and a time varying dataset .. code-block:: none - + @@ -71,7 +71,7 @@ It contains a static dataset (bed elevation) and a time varying dataset .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 0.515 seconds) + **Total running time of the script:** ( 0 minutes 0.434 seconds) .. _sphx_glr_download_sample_data_adh_san_diego.py: diff --git a/_sources/sample_data/disk.rst.txt b/_sources/sample_data/disk.rst.txt index 0d4339ddf..02eff4021 100644 --- a/_sources/sample_data/disk.rst.txt +++ b/_sources/sample_data/disk.rst.txt @@ -39,7 +39,7 @@ of a disk. It contains data on the nodes, faces, and edges. .. code-block:: none - + @@ -68,7 +68,7 @@ of a disk. It contains data on the nodes, faces, and edges. .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 0.273 seconds) + **Total running time of the script:** ( 0 minutes 0.199 seconds) .. _sphx_glr_download_sample_data_disk.py: diff --git a/_sources/sample_data/elevation_nl.rst.txt b/_sources/sample_data/elevation_nl.rst.txt index 37ce90627..5868ca090 100644 --- a/_sources/sample_data/elevation_nl.rst.txt +++ b/_sources/sample_data/elevation_nl.rst.txt @@ -39,7 +39,7 @@ of the Netherlands. .. code-block:: none - [] + [] @@ -67,7 +67,7 @@ of the Netherlands. .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 1.113 seconds) + **Total running time of the script:** ( 0 minutes 0.985 seconds) .. _sphx_glr_download_sample_data_elevation_nl.py: diff --git a/_sources/sample_data/provinces_nl.rst.txt b/_sources/sample_data/provinces_nl.rst.txt index 128be3d59..48910d13b 100644 --- a/_sources/sample_data/provinces_nl.rst.txt +++ b/_sources/sample_data/provinces_nl.rst.txt @@ -58,7 +58,7 @@ Netherlands, including water, presented as geopandas GeoDataFrame. .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 0.142 seconds) + **Total running time of the script:** ( 0 minutes 0.103 seconds) .. _sphx_glr_download_sample_data_provinces_nl.py: diff --git a/_sources/sample_data/sg_execution_times.rst.txt b/_sources/sample_data/sg_execution_times.rst.txt index b0015322e..04aed9a11 100644 --- a/_sources/sample_data/sg_execution_times.rst.txt +++ b/_sources/sample_data/sg_execution_times.rst.txt @@ -6,16 +6,16 @@ Computation times ================= -**00:02.151** total execution time for **sample_data** files: +**00:01.798** total execution time for **sample_data** files: +---------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_sample_data_elevation_nl.py` (``elevation_nl.py``) | 00:01.113 | 0.0 MB | +| :ref:`sphx_glr_sample_data_elevation_nl.py` (``elevation_nl.py``) | 00:00.985 | 0.0 MB | +---------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_sample_data_adh_san_diego.py` (``adh_san_diego.py``) | 00:00.515 | 0.0 MB | +| :ref:`sphx_glr_sample_data_adh_san_diego.py` (``adh_san_diego.py``) | 00:00.434 | 0.0 MB | +---------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_sample_data_disk.py` (``disk.py``) | 00:00.273 | 0.0 MB | +| :ref:`sphx_glr_sample_data_disk.py` (``disk.py``) | 00:00.199 | 0.0 MB | +---------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_sample_data_provinces_nl.py` (``provinces_nl.py``) | 00:00.142 | 0.0 MB | +| :ref:`sphx_glr_sample_data_provinces_nl.py` (``provinces_nl.py``) | 00:00.103 | 0.0 MB | +---------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_sample_data_xoxo.py` (``xoxo.py``) | 00:00.108 | 0.0 MB | +| :ref:`sphx_glr_sample_data_xoxo.py` (``xoxo.py``) | 00:00.078 | 0.0 MB | +---------------------------------------------------------------------+-----------+--------+ diff --git a/_sources/sample_data/xoxo.rst.txt b/_sources/sample_data/xoxo.rst.txt index ea72dbbc7..7dd2bfa01 100644 --- a/_sources/sample_data/xoxo.rst.txt +++ b/_sources/sample_data/xoxo.rst.txt @@ -55,7 +55,7 @@ directory if it's not there already. .. rst-class:: sphx-glr-timing - **Total running time of the script:** ( 0 minutes 0.108 seconds) + **Total running time of the script:** ( 0 minutes 0.078 seconds) .. _sphx_glr_download_sample_data_xoxo.py: diff --git a/examples-dev/sg_execution_times.html b/examples-dev/sg_execution_times.html index d22b1cc28..8e61eca86 100644 --- a/examples-dev/sg_execution_times.html +++ b/examples-dev/sg_execution_times.html @@ -378,11 +378,11 @@

    Computation times#

    -

    00:02.310 total execution time for examples-dev files:

    +

    00:01.578 total execution time for examples-dev files:

    - + diff --git a/examples-dev/voronoi.html b/examples-dev/voronoi.html index f0bd23cea..250ae793f 100644 --- a/examples-dev/voronoi.html +++ b/examples-dev/voronoi.html @@ -783,7 +783,7 @@

    Infinite rays
    (-1.5, 1.5)
     
    -

    Total running time of the script: ( 0 minutes 2.310 seconds)

    +

    Total running time of the script: ( 0 minutes 1.578 seconds)

    -connectivity -connectivity -connectivity -connectivity -connectivity -connectivity -connectivity -connectivity -connectivity -connectivity -connectivity
    <matplotlib.image.AxesImage object at 0x7f0db47ce6d0>
    +connectivity
    <matplotlib.image.AxesImage object at 0x7f8698111b20>
     
    -

    Total running time of the script: ( 0 minutes 2.363 seconds)

    +

    Total running time of the script: ( 0 minutes 1.613 seconds)

    Gallery generated by Sphinx-Gallery

    diff --git a/examples/overlap_regridder.html b/examples/overlap_regridder.html index 23d5d18be..0d36c2056 100644 --- a/examples/overlap_regridder.html +++ b/examples/overlap_regridder.html @@ -460,7 +460,7 @@ grid.plot(ax=ax, color="red")
    -overlap regridder
    <matplotlib.collections.LineCollection object at 0x7f0da7f56250>
    +overlap regridder
    <matplotlib.collections.LineCollection object at 0x7f868b8954c0>
     
    @@ -509,7 +509,7 @@

    Relative overlapresult.ugrid.plot()

    -overlap regridder -overlap regridder -overlap regridder -partitioning -partitioning -partitioning -partitioning -plotting
    -plotting -plotting
    -plotting -plotting -plotting -plotting
    -plotting -plotting -node = 1000, node_x = 4.84e+05, node_y = 3.614e+06
    [<matplotlib.lines.Line2D object at 0x7f0da7f7cfa0>]
    +node = 1000, node_x = 4.84e+05, node_y = 3.614e+06
    [<matplotlib.lines.Line2D object at 0x7f868b89f430>]
     
    -

    Total running time of the script: ( 0 minutes 19.199 seconds)

    +

    Total running time of the script: ( 0 minutes 14.685 seconds)

    Centroid Voronoi Tesselation (CVT) (voronoi.py)

    00:02.310

    00:01.578

    0.0 MB

    - + - + - + - - + + - - + + - + - + diff --git a/examples/vector_conversion.html b/examples/vector_conversion.html index 075553853..03973fd60 100644 --- a/examples/vector_conversion.html +++ b/examples/vector_conversion.html @@ -432,7 +432,7 @@ uda.ugrid.plot(vmin=-20,vmax=90,cmap="terrain") -vector conversion
    <matplotlib.collections.PolyCollection object at 0x7f0db47aee20>
    +vector conversion
    <matplotlib.collections.PolyCollection object at 0x7f868bc87d00>
     
    @@ -843,9 +843,9 @@

    Conversion from GeoDataFrame @@ -881,7 +881,7 @@

    “Rasterizing”, or “burning” vector geometriesburned.ugrid.plot()

    -vector conversion
    • id
      (id)
      float64
      0.0 1.0 2.0 3.0 ... 9.0 10.0 11.0
      array([ 0.,  1.,  2.,  3.,  4.,  5.,  6.,  7.,  8.,  9., 10., 11.])
    • id
      PandasIndex
      PandasIndex(Index([0.0, 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0, 10.0, 11.0], dtype='float64', name='id'))
  • unit :
    m NAP


  • This is a convenient way to create masks for specific regions:

    @@ -1303,7 +1303,7 @@

    “Rasterizing”, or “burning” vector geometriesmodified.ugrid.plot(vmin=-20, vmax=90, cmap="terrain") -vector conversion -vector conversion
    -

    Total running time of the script: ( 0 minutes 26.083 seconds)

    + +
    +

    Snap to grid#

    +

    The examples above deal with data on the faces of the grid. However, data can +also be associated with the nodes or edges of the grid. For example, we can +snap line data to exactly follow the edges (the face boundaries):

    +
    linestrings = gpd.GeoDataFrame(geometry=utrecht.exterior)
    +snapped_uds, snapped_gdf = xu.snap_to_grid(linestrings, uda, max_snap_distance=1.0)
    +
    +fig, ax = plt.subplots()
    +snapped_gdf.plot(ax=ax)
    +snapped_uds.ugrid.grid.plot(ax=ax, edgecolor="gray", linewidth=0.5)
    +utrecht.plot(ax=ax, edgecolor="red", facecolor="none", linewidth=0.75)
    +ax.set_xlim(xmin, xmax)
    +ax.set_ylim(ymin, ymax)
    +
    +
    +vector conversion
    (428343.70545104187, 489587.5779869387)
    +
    +
    +

    There are (arguably) many ways in which a linestring could be snapped to +edges. The function above uses the criterion the following criterion: if a +part of the linestring is located between the centroid of a face and the +centroid of an edge, it is snapped to that edge.

    +

    This sometimes result in less (visually) pleasing results, such as the two +triangles in the lower left corner which are surrounded by the snapped edges. +In general, results are best when the line segments are relatively large +compare to the grid faces.

    +

    Total running time of the script: ( 0 minutes 21.131 seconds)

    Vector geometry conversion (vector_conversion.py)

    00:26.083

    00:21.131

    0.0 MB

    Plot unstructured mesh data (plotting.py)

    00:19.199

    00:14.685

    0.0 MB

    Regridding overview (regridder_overview.py)

    00:12.884

    00:10.266

    0.0 MB

    Partitioning (partitioning.py)

    00:07.265

    OverlapRegridder (overlap_regridder.py)

    00:05.197

    0.0 MB

    OverlapRegridder (overlap_regridder.py)

    00:06.988

    Partitioning (partitioning.py)

    00:04.838

    0.0 MB

    Connectivity (connectivity.py)

    00:02.363

    00:01.613

    0.0 MB

    Quick overview (quick_overview.py)

    00:01.016

    00:00.726

    0.0 MB

    - + - + - + - + - + diff --git a/sample_data/xoxo.html b/sample_data/xoxo.html index 46c05fefa..81b7633ee 100644 --- a/sample_data/xoxo.html +++ b/sample_data/xoxo.html @@ -433,7 +433,7 @@ ax.set_aspect(1) -

    Total running time of the script: ( 0 minutes 0.108 seconds)

    +

    Total running time of the script: ( 0 minutes 0.078 seconds)

    Elevation NL (elevation_nl.py)

    00:01.113

    00:00.985

    0.0 MB

    ADH San Diego (adh_san_diego.py)

    00:00.515

    00:00.434

    0.0 MB

    Disk (disk.py)

    00:00.273

    00:00.199

    0.0 MB

    Pronvinces NL (provinces_nl.py)

    00:00.142

    00:00.103

    0.0 MB

    Xoxo (xoxo.py)

    00:00.108

    00:00.078

    0.0 MB

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