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20 bcmZqmZuQ + @@ -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 - + @@ -477,7 +477,7 @@ interpolation. .. code-block:: none - + @@ -518,7 +518,7 @@ To illustrate, let's take a look at the connectivity matrix of the Xoxo grid. .. code-block:: none - + @@ -554,14 +554,14 @@ locality: .. code-block:: none - + .. rst-class:: sphx-glr-timing - **Total running time of the script:** (0 minutes 1.358 seconds) + **Total running time of the script:** (0 minutes 1.321 seconds) .. _sphx_glr_download_examples_connectivity.py: diff --git a/_sources/examples/overlap_regridder.rst.txt b/_sources/examples/overlap_regridder.rst.txt index 7ba3a51c1..96570f8b2 100644 --- a/_sources/examples/overlap_regridder.rst.txt +++ b/_sources/examples/overlap_regridder.rst.txt @@ -112,7 +112,7 @@ some bathymetry) of the Netherlands, and a coarser target grid. .. code-block:: none - + @@ -202,7 +202,7 @@ conservative methods, such as conductance: .. code-block:: none - + @@ -280,7 +280,7 @@ To use our custom method, we provide at initialization of the OverlapRegridder: .. code-block:: none - + @@ -320,7 +320,7 @@ function can deal with NaN values! -- hence ``nanpercentile`` rather than .. code-block:: none - + @@ -331,7 +331,7 @@ function can deal with NaN values! -- hence ``nanpercentile`` rather than .. rst-class:: sphx-glr-timing - **Total running time of the script:** (0 minutes 3.899 seconds) + **Total running time of the script:** (0 minutes 3.864 seconds) .. _sphx_glr_download_examples_overlap_regridder.py: diff --git a/_sources/examples/partitioning.rst.txt b/_sources/examples/partitioning.rst.txt index 5e508cbca..81c6c8a76 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

@@ -1066,9 +1066,9 @@ original topology. ``reindex_like`` looks at the coordinates of both 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

@@ -1470,9 +1470,9 @@ 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

@@ -1489,7 +1489,7 @@ partitions. .. rst-class:: sphx-glr-timing - **Total running time of the script:** (0 minutes 3.761 seconds) + **Total running time of the script:** (0 minutes 3.833 seconds) .. _sphx_glr_download_examples_partitioning.py: diff --git a/_sources/examples/plotting.rst.txt b/_sources/examples/plotting.rst.txt index c9b556ba3..3774177f0 100644 --- a/_sources/examples/plotting.rst.txt +++ b/_sources/examples/plotting.rst.txt @@ -450,13 +450,13 @@ faces. 
<xarray.Dataset>
     Dimensions:        (mesh2d_nNodes: 217, mesh2d_nFaces: 384, mesh2d_nEdges: 600)
     Coordinates:
+      * mesh2d_nEdges  (mesh2d_nEdges) int64 0 1 2 3 4 5 ... 594 595 596 597 598 599
       * mesh2d_nNodes  (mesh2d_nNodes) int64 0 1 2 3 4 5 ... 211 212 213 214 215 216
       * mesh2d_nFaces  (mesh2d_nFaces) int64 0 1 2 3 4 5 ... 378 379 380 381 382 383
-      * mesh2d_nEdges  (mesh2d_nEdges) int64 0 1 2 3 4 5 ... 594 595 596 597 598 599
     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'))


    • @@ -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 11.268 seconds) + **Total running time of the script:** (0 minutes 11.510 seconds) .. _sphx_glr_download_examples_plotting.py: diff --git a/_sources/examples/quick_overview.rst.txt b/_sources/examples/quick_overview.rst.txt index a26afe62a..263836b88 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 (node) int64 0 1 2 3 4 5 6 ... 9133 9134 9135 9136 9137 9138 9139 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_x (node) float64 ... node_y (node) float64 ... - * node (node) int64 0 1 2 3 4 5 6 7 ... 9133 9134 9135 9136 9137 9138 9139 + * node (node) int64 0 1 2 3 4 5 6 7 ... 9133 9134 9135 9136 9137 9138 9139

    @@ -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

    @@ -3116,13 +3116,13 @@ grid (nodes, faces, edges). 
    <xarray.Dataset>
     Dimensions:        (mesh2d_nNodes: 217, mesh2d_nFaces: 384, mesh2d_nEdges: 600)
     Coordinates:
+      * mesh2d_nEdges  (mesh2d_nEdges) int64 0 1 2 3 4 5 ... 594 595 596 597 598 599
       * mesh2d_nNodes  (mesh2d_nNodes) int64 0 1 2 3 4 5 ... 211 212 213 214 215 216
       * mesh2d_nFaces  (mesh2d_nFaces) int64 0 1 2 3 4 5 ... 378 379 380 381 382 383
-      * mesh2d_nEdges  (mesh2d_nEdges) int64 0 1 2 3 4 5 ... 594 595 596 597 598 599
     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_y (node) float64 ... * node (node) int64 0 1 2 3 4 5 6 ... 9133 9134 9135 9136 9137 9138 9139 Data variables: - elevation (node) float64 ... + elevation (node) float64 ...

    @@ -4434,7 +4434,7 @@ before writing. elevation (node) float64 ... depth (time, node) float64 ... Attributes: - Conventions: CF-1.9 UGRID-1.0
  • Conventions :
    CF-1.9 UGRID-1.0


    • @@ -4495,7 +4495,7 @@ before writing. .. rst-class:: sphx-glr-timing - **Total running time of the script:** (0 minutes 0.552 seconds) + **Total running time of the script:** (0 minutes 0.544 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 0819e14bd..d3b2e9fd2 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 - + @@ -151,7 +151,7 @@ the centroids of the new grid fall. .. code-block:: none - + @@ -182,7 +182,7 @@ Rexgrid provides the CentroidLocatorRegridder for this: .. code-block:: none - + @@ -217,7 +217,7 @@ so large. Let's try the OverlapOverregridder instead. .. code-block:: none - + @@ -249,7 +249,7 @@ Let's try again, now with the minimum: .. code-block:: none - + @@ -280,7 +280,7 @@ Or the maximum: .. code-block:: none - + @@ -709,7 +709,7 @@ result. mesh2d_face_x (mesh2d_nFaces) float64 ... mesh2d_face_y (mesh2d_nFaces) float64 ... * layer (layer) int64 1 2 3 4 5 - * mesh2d_nFaces (mesh2d_nFaces) int64 0 1 2 3 4 ... 5243 5244 5245 5246 5247
    • 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]
    • layer
      (layer)
      int64
      1 2 3 4 5
      array([1, 2, 3, 4, 5])
    • mesh2d_nFaces
      (mesh2d_nFaces)
      int64
      0 1 2 3 4 ... 5244 5245 5246 5247
      array([   0,    1,    2, ..., 5245, 5246, 5247])
    • layer
      PandasIndex
      PandasIndex(Index([1, 2, 3, 4, 5], dtype='int64', name='layer'))
    • mesh2d_nFaces
      PandasIndex
      PandasIndex(RangeIndex(start=0, stop=5248, step=1, name='mesh2d_nFaces'))


    • @@ -1151,7 +1151,7 @@ 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'))


    • @@ -1233,7 +1233,7 @@ and the aggregated mean. .. code-block:: none - [, , , , ] + [, , , , ] @@ -1270,7 +1270,7 @@ To illustrate, we will zoom in to a part of the Netherlands. .. code-block:: none - + @@ -1323,7 +1323,7 @@ the triangles. .. code-block:: none - + @@ -1364,7 +1364,7 @@ the regridders work for any collection of (convex) faces. .. code-block:: none - + @@ -1400,7 +1400,7 @@ is kept the same. .. code-block:: none - + @@ -1416,7 +1416,7 @@ is kept the same. .. rst-class:: sphx-glr-timing - **Total running time of the script:** (0 minutes 7.760 seconds) + **Total running time of the script:** (0 minutes 7.732 seconds) .. _sphx_glr_download_examples_regridder_overview.py: diff --git a/_sources/examples/selection.rst.txt b/_sources/examples/selection.rst.txt index 2b30fece3..b50b16534 100644 --- a/_sources/examples/selection.rst.txt +++ b/_sources/examples/selection.rst.txt @@ -85,7 +85,7 @@ elevation of the Netherlands. .. code-block:: none - + @@ -130,7 +130,7 @@ A subset of the unstructured grid is returned by using slices without a step: .. code-block:: none - + @@ -161,7 +161,7 @@ In such a case the entire grid is returned. .. code-block:: none - + @@ -196,7 +196,7 @@ This means we can easily select along a single dimension: .. code-block:: none - + @@ -226,7 +226,7 @@ Or, using ``None`` if we only care about the start: .. code-block:: none - + @@ -660,7 +660,7 @@ Two values will select a point: mesh2d_x (mesh2d_nFaces) float64 1.5e+05 mesh2d_y (mesh2d_nFaces) float64 4.63e+05 Attributes: - unit: m NAP + unit: m NAP

    @@ -1066,7 +1066,7 @@ of six points: mesh2d_x (mesh2d_nFaces) float64 1.25e+05 1.5e+05 ... 1.5e+05 1.75e+05 mesh2d_y (mesh2d_nFaces) float64 4e+05 4e+05 ... 4.65e+05 4.65e+05 Attributes: - unit: m NAP + unit: m NAP

    @@ -1472,7 +1472,7 @@ To select points without broadcasting, use ``.ugrid.sel_points`` instead: mesh2d_x (mesh2d_nFaces) float64 1.25e+05 1.5e+05 1.75e+05 mesh2d_y (mesh2d_nFaces) float64 4e+05 4.3e+05 4.65e+05 Attributes: - unit: m NAP + unit: m NAP

    @@ -1876,9 +1876,9 @@ We can sample points along a line as well by providing slices **with** a step: mesh2d_x (mesh2d_nFaces) float64 1e+05 1.1e+05 ... 1.8e+05 1.9e+05 mesh2d_y (mesh2d_nFaces) float64 4.65e+05 4.65e+05 ... 4.65e+05 Attributes: - unit: m NAP + unit: m NAP

    @@ -2284,7 +2284,7 @@ Two slices with a step results in broadcasting: mesh2d_x (mesh2d_nFaces) float64 1e+05 1.1e+05 ... 1.8e+05 1.9e+05 mesh2d_y (mesh2d_nFaces) float64 4e+05 4e+05 4e+05 ... 4.9e+05 4.9e+05 Attributes: - unit: m NAP
  • unit :
    m NAP


    • @@ -2738,15 +2738,15 @@ As well as a slice with a step and multiple values: mesh2d_x (mesh2d_nFaces) float64 1e+05 1.1e+05 ... 1.8e+05 1.9e+05 mesh2d_y (mesh2d_nFaces) float64 4e+05 4e+05 4e+05 ... 4.3e+05 4.3e+05 Attributes: - unit: m NAP
  • unit :
    m NAP


    • @@ -2930,7 +2930,7 @@ thousands faces: .. code-block:: none - + @@ -2952,7 +2952,7 @@ face dimension for 2D topologies. .. rst-class:: sphx-glr-timing - **Total running time of the script:** (0 minutes 3.443 seconds) + **Total running time of the script:** (0 minutes 3.625 seconds) .. _sphx_glr_download_examples_selection.py: diff --git a/_sources/examples/sg_execution_times.rst.txt b/_sources/examples/sg_execution_times.rst.txt index d9aee8a45..885773f2d 100644 --- a/_sources/examples/sg_execution_times.rst.txt +++ b/_sources/examples/sg_execution_times.rst.txt @@ -6,22 +6,22 @@ Computation times ================= -**00:47.785** total execution time for **examples** files: +**00:48.034** total execution time for **examples** files: +----------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_vector_conversion.py` (``vector_conversion.py``) | 00:15.744 | 0.0 MB | +| :ref:`sphx_glr_examples_vector_conversion.py` (``vector_conversion.py``) | 00:15.604 | 0.0 MB | +----------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_plotting.py` (``plotting.py``) | 00:11.268 | 0.0 MB | +| :ref:`sphx_glr_examples_plotting.py` (``plotting.py``) | 00:11.510 | 0.0 MB | +----------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_regridder_overview.py` (``regridder_overview.py``) | 00:07.760 | 0.0 MB | +| :ref:`sphx_glr_examples_regridder_overview.py` (``regridder_overview.py``) | 00:07.732 | 0.0 MB | +----------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_overlap_regridder.py` (``overlap_regridder.py``) | 00:03.899 | 0.0 MB | +| :ref:`sphx_glr_examples_overlap_regridder.py` (``overlap_regridder.py``) | 00:03.864 | 0.0 MB | +----------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_partitioning.py` (``partitioning.py``) | 00:03.761 | 0.0 MB | +| :ref:`sphx_glr_examples_partitioning.py` (``partitioning.py``) | 00:03.833 | 0.0 MB | +----------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_selection.py` (``selection.py``) | 00:03.443 | 0.0 MB | +| :ref:`sphx_glr_examples_selection.py` (``selection.py``) | 00:03.625 | 0.0 MB | +----------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_connectivity.py` (``connectivity.py``) | 00:01.358 | 0.0 MB | +| :ref:`sphx_glr_examples_connectivity.py` (``connectivity.py``) | 00:01.321 | 0.0 MB | +----------------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_examples_quick_overview.py` (``quick_overview.py``) | 00:00.552 | 0.0 MB | +| :ref:`sphx_glr_examples_quick_overview.py` (``quick_overview.py``) | 00:00.544 | 0.0 MB | +----------------------------------------------------------------------------+-----------+--------+ diff --git a/_sources/examples/vector_conversion.rst.txt b/_sources/examples/vector_conversion.rst.txt index d6ac0cdbf..b66b3ac18 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 - + @@ -1342,7 +1342,7 @@ compare to the grid faces. .. rst-class:: sphx-glr-timing - **Total running time of the script:** (0 minutes 15.744 seconds) + **Total running time of the script:** (0 minutes 15.604 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 3f5e96dae..3b41587f5 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 0.326 seconds) + **Total running time of the script:** (0 minutes 0.311 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 ee840a8e9..70889ed63 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 0.164 seconds) + **Total running time of the script:** (0 minutes 0.162 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 6009c000f..83dab9758 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 0.808 seconds) + **Total running time of the script:** (0 minutes 0.792 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 550fc36c0..de579e06a 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 0.086 seconds) + **Total running time of the script:** (0 minutes 0.084 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 4ded427ce..8b317a530 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 ================= -**00:01.453** total execution time for **sample_data** files: +**00:01.415** total execution time for **sample_data** files: +---------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_sample_data_elevation_nl.py` (``elevation_nl.py``) | 00:00.808 | 0.0 MB | +| :ref:`sphx_glr_sample_data_elevation_nl.py` (``elevation_nl.py``) | 00:00.792 | 0.0 MB | +---------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_sample_data_adh_san_diego.py` (``adh_san_diego.py``) | 00:00.326 | 0.0 MB | +| :ref:`sphx_glr_sample_data_adh_san_diego.py` (``adh_san_diego.py``) | 00:00.311 | 0.0 MB | +---------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_sample_data_disk.py` (``disk.py``) | 00:00.164 | 0.0 MB | +| :ref:`sphx_glr_sample_data_disk.py` (``disk.py``) | 00:00.162 | 0.0 MB | +---------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_sample_data_provinces_nl.py` (``provinces_nl.py``) | 00:00.086 | 0.0 MB | +| :ref:`sphx_glr_sample_data_provinces_nl.py` (``provinces_nl.py``) | 00:00.084 | 0.0 MB | +---------------------------------------------------------------------+-----------+--------+ -| :ref:`sphx_glr_sample_data_xoxo.py` (``xoxo.py``) | 00:00.068 | 0.0 MB | +| :ref:`sphx_glr_sample_data_xoxo.py` (``xoxo.py``) | 00:00.066 | 0.0 MB | +---------------------------------------------------------------------+-----------+--------+ diff --git a/_sources/sample_data/xoxo.rst.txt b/_sources/sample_data/xoxo.rst.txt index fe336d553..c5ae9468f 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 0.068 seconds) + **Total running time of the script:** (0 minutes 0.066 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 64611d671..4c791445b 100644 --- a/examples-dev/sg_execution_times.html +++ b/examples-dev/sg_execution_times.html @@ -393,11 +393,11 @@

    Computation times#

    -

    00:01.335 total execution time for examples-dev files:

    +

    00:01.248 total execution time for examples-dev files:

    - + diff --git a/examples-dev/voronoi.html b/examples-dev/voronoi.html index f073cac13..b214a38bd 100644 --- a/examples-dev/voronoi.html +++ b/examples-dev/voronoi.html @@ -798,7 +798,7 @@

    Infinite rays
    (-1.5, 1.5)
    -

    Total running time of the script: (0 minutes 1.335 seconds)

    +

    Total running time of the script: (0 minutes 1.248 seconds)

     -connectivity
    <matplotlib.collections.PolyCollection object at 0x7faae642a110>
+connectivity
    <matplotlib.collections.PolyCollection object at 0x7feed5c36250>
 
    
 
    
 
    By default, the border value for binary dilation is also set to
@@ -514,7 +514,7 @@ 
    Binary erosion and dilationuda.ugrid.plot()
    -connectivity
    <matplotlib.collections.PolyCollection object at 0x7faae7f3b750>
+connectivity
    <matplotlib.collections.PolyCollection object at 0x7feeca8040d0>
 
    
 
    
 
    Now let’s run two dilations: one with the default border, and one with the
@@ -527,7 +527,7 @@ 
    Binary erosion and dilationiter1_boundary.ugrid.plot(ax=ax1)
    -connectivity
    <matplotlib.collections.PolyCollection object at 0x7faae735c090>
+connectivity
    <matplotlib.collections.PolyCollection object at 0x7feec9f80710>
 
    
 
    
 
@@ -543,7 +543,7 @@ 
    Connected Componentslabeled.ugrid.plot(cmap="RdBu")
    -connectivity
    <matplotlib.collections.PolyCollection object at 0x7faae672b550>
+connectivity
    <matplotlib.collections.PolyCollection object at 0x7feeca829b90>
 
    
 
    
 
@@ -555,7 +555,7 @@ 
    Centroidal Voronoi Tesselationxugrid.plot.line(voronoi_grid, color="black")
    -connectivity
    <matplotlib.collections.LineCollection object at 0x7faae71419d0>
+connectivity
    <matplotlib.collections.LineCollection object at 0x7feed5c1eb90>
 
    
 
    
 
    There are two alternative flavors to consider. We can fully ignore the
@@ -576,7 +576,7 @@ 
    Centroidal Voronoi Tesselationxugrid.plot.line(convex_exterior, ax=ax1, color="black")
    -connectivity
    <matplotlib.collections.LineCollection object at 0x7faae71bd4d0>
+connectivity
    <matplotlib.collections.LineCollection object at 0x7feec9f05e90>
 
    
 
    
 
@@ -592,7 +592,7 @@ 
    Triangulationxugrid.plot.line(triangulation, ax=ax1, color="black")
    -connectivity
    <matplotlib.collections.LineCollection object at 0x7faae62b1950>
+connectivity
    <matplotlib.collections.LineCollection object at 0x7feeca52e1d0>
 
    
 
    
 
@@ -623,7 +623,7 @@ 
    Laplace interpolationuda.ugrid.plot.line(ax=ax, color="black")
    -connectivity
    <matplotlib.collections.LineCollection object at 0x7faae65d9210>
+connectivity
    <matplotlib.collections.LineCollection object at 0x7feeca0f60d0>
 
    
 
    
 
    We can now use Laplace interpolation to fill the gaps in the grid.
    
@@ -631,7 +631,7 @@ 
    Laplace interpolationfilled.ugrid.plot(cmap="gist_rainbow", vmin=2.5, vmax=7.5)
    -connectivity
    <matplotlib.collections.PolyCollection object at 0x7faae75b0390>
+connectivity
    <matplotlib.collections.PolyCollection object at 0x7feeca338750>
 
    
 
    
 
    Laplace interpolation can also be used on the nodes of a grid.
@@ -647,7 +647,7 @@ 
    Laplace interpolationdisk_filled.ugrid.plot(ax=ax2)
    -connectivity
    <matplotlib.collections.PolyCollection object at 0x7faae616d410>
+connectivity
    <matplotlib.collections.PolyCollection object at 0x7feec9569410>
 
    
 
    
 
@@ -665,7 +665,7 @@ 
    Reverse-Cuthill McKeeax.imshow(connectivity, cmap="Greys")
    -connectivity
    <matplotlib.image.AxesImage object at 0x7faae72a8d10>
+connectivity
    <matplotlib.image.AxesImage object at 0x7feec9d5b910>
 
    
 
    
 
    The bandwidth of this matrix is poor. Connections are all over the place: low
@@ -679,10 +679,10 @@ 
    Reverse-Cuthill McKeeax.imshow(connectivity, cmap="Greys")
    -connectivity
    <matplotlib.image.AxesImage object at 0x7faae75e00d0>
+connectivity
    <matplotlib.image.AxesImage object at 0x7feeca0a0790>
 
    
 
    
-
    Total running time of the script: (0 minutes 1.358 seconds)
    
+
    Total running time of the script: (0 minutes 1.321 seconds)
    -overlap regridder
    <matplotlib.collections.LineCollection object at 0x7faae731f310>
+overlap regridder
    <matplotlib.collections.LineCollection object at 0x7feeca1d5d50>
 
    
 
    
 
    
@@ -523,7 +523,7 @@ 
    Relative overlapresult.ugrid.plot()
    -overlap regridder
    <matplotlib.collections.PolyCollection object at 0x7faae7f24950>
+overlap regridder
    <matplotlib.collections.PolyCollection object at 0x7feecaa4cb50>
 
    
 
    
 
@@ -565,7 +565,7 @@ 
    Custom reductionsresult.ugrid.plot(vmin=-20, vmax=90, cmap="terrain")
    -overlap regridder
    <matplotlib.collections.PolyCollection object at 0x7faae659f190>
+overlap regridder
    <matplotlib.collections.PolyCollection object at 0x7feeca9fb450>
 
    
 
    
 
    Not every reduction uses the weights argument. For example, computing an
@@ -582,10 +582,10 @@ 
    Custom reductionsresult.ugrid.plot(vmin=-20, vmax=90, cmap="terrain")
    -overlap regridder
    <matplotlib.collections.PolyCollection object at 0x7faae62b9250>
+overlap regridder
    <matplotlib.collections.PolyCollection object at 0x7feec952f610>
 
    
 
    
-
    Total running time of the script: (0 minutes 3.899 seconds)
    
+
    Total running time of the script: (0 minutes 3.864 seconds)
    -partitioning
    <matplotlib.collections.PolyCollection object at 0x7faaf1ffc110>
+partitioning
    <matplotlib.collections.PolyCollection object at 0x7feecb324f10>
 
    
 
    
 
    Let’s start by dividing the grid into four parts:
    
@@ -476,7 +476,7 @@ 
    Partition the gridlabels.ugrid.plot()
    -partitioning
    <matplotlib.collections.PolyCollection object at 0x7faae7637190>
+partitioning
    <matplotlib.collections.PolyCollection object at 0x7feeca4a0150>
 
    
 
    
 
    Not quite the twelve provinces of the Netherlands!
    
@@ -501,7 +501,7 @@ 
    Merging partitionsmerged.ugrid.plot(vmin=-20, vmax=90, cmap="terrain")
    -partitioning
    <matplotlib.collections.PolyCollection object at 0x7faaf238d750>
+partitioning
    <matplotlib.collections.PolyCollection object at 0x7feed5c6f2d0>
 
    
 
    
 
@@ -522,7 +522,7 @@ 
    Partitioning grids without datamerged_grid.plot()
    -partitioning
    <matplotlib.collections.LineCollection object at 0x7faae64519d0>
+partitioning
    <matplotlib.collections.LineCollection object at 0x7feec9578a90>
 
    
 
    
 
@@ -899,7 +899,7 @@ 
    Preserving orderTotal running time of the script: (0 minutes 3.761 seconds)
    
+
    Total running time of the script: (0 minutes 3.833 seconds)
    • 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'))


    • @@ -968,7 +968,7 @@

    UgridDataArrayuda.ugrid.plot() -plotting
    <matplotlib.collections.PolyCollection object at 0x7faae6327190>
+plotting
    <matplotlib.collections.PolyCollection object at 0x7feec957a050>
 
    
 
    
 
    Like Xarray, the axes and the colorbar are labeled automatically using the
@@ -980,7 +980,7 @@ 
    UgridDataArray
    ds["edge_z"].ugrid.plot()
    -plotting
    <matplotlib.collections.LineCollection object at 0x7faae70b24d0>
+plotting
    <matplotlib.collections.LineCollection object at 0x7feed5cb4690>
 
    
 
    
 
    The method called by default depends on the type of the data:
    
@@ -1009,7 +1009,7 @@ 
    UgridDataArrayds["node_z"].ugrid.plot(ax=ax2)
    -plotting
    <matplotlib.collections.PolyCollection object at 0x7faae70d1710>
+plotting
    <matplotlib.collections.PolyCollection object at 0x7feec94f1ad0>
 
    
 
    
 
    We can also exactly control the type of plot we want. For example, to plot
@@ -1017,7 +1017,7 @@ 
    UgridDataArray
    ds["face_z"].ugrid.plot.contourf()
    -plotting
    <matplotlib.tri._tricontour.TriContourSet object at 0x7faae70814d0>
+plotting
    <matplotlib.tri._tricontour.TriContourSet object at 0x7feec9f4ce10>
 
    
 
    
 
    We can also overlay this data with the edges:
    
@@ -1026,7 +1026,7 @@ 
    UgridDataArrayds["face_z"].ugrid.plot.line(color="black")
    -plotting
    <matplotlib.collections.LineCollection object at 0x7faae72fdc10>
+plotting
    <matplotlib.collections.LineCollection object at 0x7feeca04ce10>
 
    
 
    
 
    In general, there has to be data associated with the mesh topology before a
@@ -1077,7 +1077,7 @@ 
    Other types of plotds["node_z"].ugrid.plot.scatter(ax=axes[4, 2])
    -plotting
    <matplotlib.collections.PathCollection object at 0x7faae7f2f050>
+plotting
    <matplotlib.collections.PathCollection object at 0x7feed6af4050>
 
    
 
    
 
    The surface methods generate 3D surface plots:
    
@@ -1088,7 +1088,7 @@ 
    Other types of plotds["node_z"].ugrid.plot.surface(ax=ax1)
    -plotting
    <mpl_toolkits.mplot3d.art3d.Poly3DCollection object at 0x7faae65eda50>
+plotting
    <mpl_toolkits.mplot3d.art3d.Poly3DCollection object at 0x7feed57c81d0>
 
    
 
    
 
@@ -1100,7 +1100,7 @@ 
    Additional Arguments
    ds["face_z"].ugrid.plot(cmap="RdBu", levels=8, yincrease=False)
    -plotting
    <matplotlib.collections.PolyCollection object at 0x7faaf360d750>
+plotting
    <matplotlib.collections.PolyCollection object at 0x7feeca045990>
 
    
 
    
 
@@ -1114,7 +1114,7 @@ 
    As a functionxugrid.plot.pcolormesh(grid, da)
    -plotting
    <matplotlib.collections.PolyCollection object at 0x7faae7355190>
+plotting
    <matplotlib.collections.PolyCollection object at 0x7feec9f6e2d0>
 
    
 
    
 
@@ -1128,10 +1128,10 @@ 
    Xarray DataArray plotsdepth.isel(node=1000).plot()
    -node_x = 4.84e+05, node_y = 3.614e+06, node = 1000
    [<matplotlib.lines.Line2D object at 0x7faaf3576390>]
+node_x = 4.84e+05, node_y = 3.614e+06, node = 1000
    [<matplotlib.lines.Line2D object at 0x7feec9ff92d0>]
 
    
 
    
-
    Total running time of the script: (0 minutes 11.268 seconds)
    
+
    Total running time of the script: (0 minutes 11.510 seconds)

    Centroid Voronoi Tesselation (CVT) (voronoi.py)

    00:01.335

    00:01.248

    0.0 MB
    - + - + - + - + - + - + - + - + diff --git a/examples/vector_conversion.html b/examples/vector_conversion.html index c5207c806..e9fe0d1a5 100644 --- a/examples/vector_conversion.html +++ b/examples/vector_conversion.html @@ -448,7 +448,7 @@ uda.ugrid.plot(vmin=-20,vmax=90,cmap="terrain") -vector conversion
    <matplotlib.collections.PolyCollection object at 0x7faae7f05010>
+vector conversion
    <matplotlib.collections.PolyCollection object at 0x7feec94f0b10>
 
    
 
    
 
    
@@ -859,9 +859,9 @@ 
    Conversion from GeoDataFrame
@@ -897,7 +897,7 @@ 
    “Rasterizing”, or “burning” vector geometriesburned.ugrid.plot()
    -vector conversion
    <matplotlib.collections.PolyCollection object at 0x7faaf1f95750>
+vector conversion
    <matplotlib.collections.PolyCollection object at 0x7feecabf2b90>
 
    
 
    
 
    This makes it very easy to classify and group data. Let’s say
@@ -1277,9 +1277,9 @@ 
    “Rasterizing”, or “burning” vector geometries
    • 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:

    @@ -1319,7 +1319,7 @@

    “Rasterizing”, or “burning” vector geometriesmodified.ugrid.plot(vmin=-20, vmax=90, cmap="terrain") -vector conversion
    <matplotlib.collections.PolyCollection object at 0x7faae652d750>
+vector conversion
    <matplotlib.collections.PolyCollection object at 0x7feeca1a4f90>
 
    
 
    
 
    Note that all_touched=True is less suitable when differently valued
@@ -1379,7 +1379,7 @@ 
    “Rasterizing”, or “burning” vector geometriesburned.ugrid.plot()
    -vector conversion
    <matplotlib.collections.PolyCollection object at 0x7faaf35a3c10>
+vector conversion
    <matplotlib.collections.PolyCollection object at 0x7feeca0780d0>
 
    
 
    
 
@@ -1436,7 +1436,7 @@ 
    Snap to gridTotal running time of the script: (0 minutes 15.744 seconds)
    
+
    Total running time of the script: (0 minutes 15.604 seconds)
    -

    Total running time of the script: (0 minutes 0.086 seconds)

    +

    Total running time of the script: (0 minutes 0.084 seconds)

    Vector geometry conversion (vector_conversion.py)

    00:15.744

    00:15.604

    0.0 MB

    Plot unstructured mesh data (plotting.py)

    00:11.268

    00:11.510

    0.0 MB

    Regridding overview (regridder_overview.py)

    00:07.760

    00:07.732

    0.0 MB

    OverlapRegridder (overlap_regridder.py)

    00:03.899

    00:03.864

    0.0 MB

    Partitioning (partitioning.py)

    00:03.761

    00:03.833

    0.0 MB

    Select unstructured data (selection.py)

    00:03.443

    00:03.625

    0.0 MB

    Connectivity (connectivity.py)

    00:01.358

    00:01.321

    0.0 MB

    Quick overview (quick_overview.py)

    00:00.552

    00:00.544

    0.0 MB
    - + - + - + - + - + diff --git a/sample_data/xoxo.html b/sample_data/xoxo.html index b60b111b4..2a76de1ad 100644 --- a/sample_data/xoxo.html +++ b/sample_data/xoxo.html @@ -449,7 +449,7 @@ ax.set_aspect(1) -

    Total running time of the script: (0 minutes 0.068 seconds)

    +

    Total running time of the script: (0 minutes 0.066 seconds)

    Elevation NL (elevation_nl.py)

    00:00.808

    00:00.792

    0.0 MB

    ADH San Diego (adh_san_diego.py)

    00:00.326

    00:00.311

    0.0 MB

    Disk (disk.py)

    00:00.164

    00:00.162

    0.0 MB

    Pronvinces NL (provinces_nl.py)

    00:00.086

    00:00.084

    0.0 MB

    Xoxo (xoxo.py)

    00:00.068

    00:00.066

    0.0 MB