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diff --git a/.doctrees/environment.pickle b/.doctrees/environment.pickle
diff --git a/.doctrees/examples-dev/sg_execution_times.doctree b/.doctrees/examples-dev/sg_execution_times.doctree
diff --git a/.doctrees/examples-dev/voronoi.doctree b/.doctrees/examples-dev/voronoi.doctree
diff --git a/.doctrees/examples/connectivity.doctree b/.doctrees/examples/connectivity.doctree
diff --git a/.doctrees/examples/index.doctree b/.doctrees/examples/index.doctree
diff --git a/.doctrees/examples/overlap_regridder.doctree b/.doctrees/examples/overlap_regridder.doctree
diff --git a/.doctrees/examples/partitioning.doctree b/.doctrees/examples/partitioning.doctree
diff --git a/.doctrees/examples/plotting.doctree b/.doctrees/examples/plotting.doctree
diff --git a/.doctrees/examples/quick_overview.doctree b/.doctrees/examples/quick_overview.doctree
diff --git a/.doctrees/examples/regridder_overview.doctree b/.doctrees/examples/regridder_overview.doctree
diff --git a/.doctrees/examples/selection.doctree b/.doctrees/examples/selection.doctree
diff --git a/.doctrees/examples/sg_execution_times.doctree b/.doctrees/examples/sg_execution_times.doctree
diff --git a/.doctrees/examples/vector_conversion.doctree b/.doctrees/examples/vector_conversion.doctree
diff --git a/.doctrees/sample_data/adh_san_diego.doctree b/.doctrees/sample_data/adh_san_diego.doctree
diff --git a/.doctrees/sample_data/disk.doctree b/.doctrees/sample_data/disk.doctree
diff --git a/.doctrees/sample_data/elevation_nl.doctree b/.doctrees/sample_data/elevation_nl.doctree
diff --git a/.doctrees/sample_data/index.doctree b/.doctrees/sample_data/index.doctree
diff --git a/.doctrees/sample_data/provinces_nl.doctree b/.doctrees/sample_data/provinces_nl.doctree
diff --git a/.doctrees/sample_data/sg_execution_times.doctree b/.doctrees/sample_data/sg_execution_times.doctree
diff --git a/.doctrees/sg_execution_times.doctree b/.doctrees/sg_execution_times.doctree
diff --git a/_downloads/1da8bbc63e9e34158260eadd1533549c/quick_overview.zip b/_downloads/1da8bbc63e9e34158260eadd1533549c/quick_overview.zip
diff --git a/_downloads/2dbba5ebb6d2057d196983a008981162/voronoi.zip b/_downloads/2dbba5ebb6d2057d196983a008981162/voronoi.zip
diff --git a/_downloads/37998fdc2548b23faf513b314db93d21/regridder_overview.zip b/_downloads/37998fdc2548b23faf513b314db93d21/regridder_overview.zip
diff --git a/_downloads/39f17b9092149c422db99554823632f1/provinces_nl.py b/_downloads/39f17b9092149c422db99554823632f1/provinces_nl.py
@@ -1,6 +1,6 @@
 """
-Pronvinces NL
-=============
+Provinces NL
+============
 
 This is a small vector dataset containing polygons of the provinces of the
 Netherlands, including water, presented as geopandas GeoDataFrame.

diff --git a/_downloads/3e8af3e56da80727f8440a5b5f94f5cb/disk.zip b/_downloads/3e8af3e56da80727f8440a5b5f94f5cb/disk.zip
diff --git a/_downloads/3eb350a8b54f214b88c5181e546a155e/adh_san_diego.zip b/_downloads/3eb350a8b54f214b88c5181e546a155e/adh_san_diego.zip
diff --git a/_downloads/422003fc9b51482872f8f3701ce47abe/provinces_nl.zip b/_downloads/422003fc9b51482872f8f3701ce47abe/provinces_nl.zip
diff --git a/_downloads/43d7b47db560c8c70c383a84a444ed83/connectivity.zip b/_downloads/43d7b47db560c8c70c383a84a444ed83/connectivity.zip
diff --git a/_downloads/6672a97162052d8d1deacaf8d183f5e3/provinces_nl.ipynb b/_downloads/6672a97162052d8d1deacaf8d183f5e3/provinces_nl.ipynb
@@ -4,7 +4,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "\n# Pronvinces NL\n\nThis is a small vector dataset containing polygons of the provinces of the\nNetherlands, including water, presented as geopandas GeoDataFrame.\n"
+        "\n# Provinces NL\n\nThis is a small vector dataset containing polygons of the provinces of the\nNetherlands, including water, presented as geopandas GeoDataFrame.\n"
       ]
     },
     {

diff --git a/_downloads/714f83d87afaca41fed5d7f2c5f887d4/vector_conversion.py b/_downloads/714f83d87afaca41fed5d7f2c5f887d4/vector_conversion.py
@@ -3,7 +3,7 @@
 ==========================
 
 A great deal of geospatial data is available not in gridded form, but in
-vectorized form: as points, lines, and polygons. In the Python data ecosystem,
+vector form: as points, lines, and polygons. In the Python data ecosystem,
 these geometries and their associated data are generally represented by a
 geopandas GeoDataFrame.
 

diff --git a/_downloads/90d50f8fc21b6ec5d818d26f7955df8a/overlap_regridder.zip b/_downloads/90d50f8fc21b6ec5d818d26f7955df8a/overlap_regridder.zip
diff --git a/_downloads/97eabe2c66fc9328b1e51f27fdee52f6/partitioning.zip b/_downloads/97eabe2c66fc9328b1e51f27fdee52f6/partitioning.zip
diff --git a/_downloads/9be12df0ec6c323839ed0cb99cc89228/elevation_nl.zip b/_downloads/9be12df0ec6c323839ed0cb99cc89228/elevation_nl.zip
diff --git a/_downloads/a50ba9731493d1c74010dcadb8694b20/selection.zip b/_downloads/a50ba9731493d1c74010dcadb8694b20/selection.zip
diff --git a/_downloads/be05b5a234b2a85e0ca223679f6e137e/vector_conversion.ipynb b/_downloads/be05b5a234b2a85e0ca223679f6e137e/vector_conversion.ipynb
@@ -4,7 +4,7 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "\n# Vector geometry conversion\n\nA great deal of geospatial data is available not in gridded form, but in\nvectorized form: as points, lines, and polygons. In the Python data ecosystem,\nthese geometries and their associated data are generally represented by a\ngeopandas GeoDataFrame.\n\nXugrid provides a number of utilities to use such data in combination with\nunstructured grids. These are demonstrated below.\n"
+        "\n# Vector geometry conversion\n\nA great deal of geospatial data is available not in gridded form, but in\nvector form: as points, lines, and polygons. In the Python data ecosystem,\nthese geometries and their associated data are generally represented by a\ngeopandas GeoDataFrame.\n\nXugrid provides a number of utilities to use such data in combination with\nunstructured grids. These are demonstrated below.\n"
       ]
     },
     {

diff --git a/_downloads/cc393383c363f7c590c6ef714836f52a/xoxo.zip b/_downloads/cc393383c363f7c590c6ef714836f52a/xoxo.zip
diff --git a/_downloads/d2379110fee2f2fbaf724f0142daaa8d/plotting.zip b/_downloads/d2379110fee2f2fbaf724f0142daaa8d/plotting.zip
diff --git a/_downloads/f25be90ee220882246ef4778e276e863/vector_conversion.zip b/_downloads/f25be90ee220882246ef4778e276e863/vector_conversion.zip
diff --git a/_sources/examples-dev/sg_execution_times.rst.txt b/_sources/examples-dev/sg_execution_times.rst.txt
@@ -6,7 +6,7 @@
 
 Computation times
 =================
-**00:01.155** total execution time for 1 file **from examples-dev**:
+**00:01.159** total execution time for 1 file **from examples-dev**:
 
 .. container::
 
@@ -33,5 +33,5 @@ Computation times
      - Time
      - Mem (MB)
    * - :ref:`sphx_glr_examples-dev_voronoi.py` (``voronoi.py``)
-     - 00:01.155
+     - 00:01.159
      - 0.0
diff --git 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 1.155 seconds)
+   **Total running time of the script:** (0 minutes 1.159 seconds)
 
 
 .. _sphx_glr_download_examples-dev_voronoi.py:

diff --git 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
 
 
-    <matplotlib.collections.PolyCollection object at 0x7fec05aead20>
+    <matplotlib.collections.PolyCollection object at 0x7f00d5fdefc0>
 
 
 
@@ -165,7 +165,7 @@ start by setting a single value in the center of the grid to ``True``.
  .. code-block:: none
 
 
-    <matplotlib.collections.PolyCollection object at 0x7fec04c95370>
+    <matplotlib.collections.PolyCollection object at 0x7f00d6963b60>
 
 
 
@@ -200,7 +200,7 @@ alternative border value:
  .. code-block:: none
 
 
-    <matplotlib.collections.PolyCollection object at 0x7febfbe593a0>
+    <matplotlib.collections.PolyCollection object at 0x7f00d7213d10>
 
 
 
@@ -238,7 +238,7 @@ analyse connected parts of the mesh.
  .. code-block:: none
 
 
-    <matplotlib.collections.PolyCollection object at 0x7febfae0cf80>
+    <matplotlib.collections.PolyCollection object at 0x7f00d6971850>
 
 
 
@@ -272,7 +272,7 @@ Tesselation.
  .. code-block:: none
 
 
-    <matplotlib.collections.LineCollection object at 0x7fec04cabd70>
+    <matplotlib.collections.LineCollection object at 0x7f00d7ba9790>
 
 
 
@@ -316,7 +316,7 @@ the original.
  .. code-block:: none
 
 
-    <matplotlib.collections.LineCollection object at 0x7febfb0bfd10>
+    <matplotlib.collections.LineCollection object at 0x7f00d69a2810>
 
 
 
@@ -355,7 +355,7 @@ We can break down one of the Voronoi tesselations from above into triangles:
  .. code-block:: none
 
 
-    <matplotlib.collections.LineCollection object at 0x7febfad8b2c0>
+    <matplotlib.collections.LineCollection object at 0x7f00d7bdb6b0>
 
 
 
@@ -409,7 +409,7 @@ the upper and lower parts:
  .. code-block:: none
 
 
-    <matplotlib.collections.LineCollection object at 0x7febfbb07da0>
+    <matplotlib.collections.LineCollection object at 0x7f00dfd18da0>
 
 
 
@@ -439,7 +439,7 @@ We can now use Laplace interpolation to fill the gaps in the grid.
  .. code-block:: none
 
 
-    <matplotlib.collections.PolyCollection object at 0x7febfbc712e0>
+    <matplotlib.collections.PolyCollection object at 0x7f00d6abbc50>
 
 
 
@@ -477,7 +477,7 @@ interpolation.
  .. code-block:: none
 
 
-    <matplotlib.collections.PolyCollection object at 0x7febfaf07d10>
+    <matplotlib.collections.PolyCollection object at 0x7f00d6c37b90>
 
 
 
@@ -518,7 +518,7 @@ To illustrate, let's take a look at the connectivity matrix of the Xoxo grid.
  .. code-block:: none
 
 
-    <matplotlib.image.AxesImage object at 0x7febfbb89100>
+    <matplotlib.image.AxesImage object at 0x7f00d5ba9910>
 
 
 
@@ -554,14 +554,14 @@ locality:
  .. code-block:: none
 
 
-    <matplotlib.image.AxesImage object at 0x7febfcb11280>
+    <matplotlib.image.AxesImage object at 0x7f00d6ea72f0>
 
 
 
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 1.390 seconds)
+   **Total running time of the script:** (0 minutes 1.401 seconds)
 
 
 .. _sphx_glr_download_examples_connectivity.py:

diff --git a/_sources/examples/index.rst.txt b/_sources/examples/index.rst.txt
@@ -137,7 +137,7 @@ notebook for interactive exploration.
 
 .. raw:: html
 
-    <div class="sphx-glr-thumbcontainer" tooltip="A great deal of geospatial data is available not in gridded form, but in vectorized form: as points, lines, and polygons. In the Python data ecosystem, these geometries and their associated data are generally represented by a geopandas GeoDataFrame.">
+    <div class="sphx-glr-thumbcontainer" tooltip="A great deal of geospatial data is available not in gridded form, but in vector form: as points, lines, and polygons. In the Python data ecosystem, these geometries and their associated data are generally represented by a geopandas GeoDataFrame.">
 
 .. only:: html
 

diff --git 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
 
 
-    <matplotlib.collections.LineCollection object at 0x7febfacee180>
+    <matplotlib.collections.LineCollection object at 0x7f00d6bd63c0>
 
 
 
@@ -202,7 +202,7 @@ conservative methods, such as conductance:
  .. code-block:: none
 
 
-    <matplotlib.collections.PolyCollection object at 0x7febfc136450>
+    <matplotlib.collections.PolyCollection object at 0x7f00d6a9f2f0>
 
 
 
@@ -298,7 +298,7 @@ OverlapRegridder:
  .. code-block:: none
 
 
-    <matplotlib.collections.PolyCollection object at 0x7febfb0cff20>
+    <matplotlib.collections.PolyCollection object at 0x7f00d6078ce0>
 
 
 
@@ -373,7 +373,7 @@ Then, provide it as the regridder method as above:
  .. code-block:: none
 
 
-    <matplotlib.collections.PolyCollection object at 0x7febfbb324b0>
+    <matplotlib.collections.PolyCollection object at 0x7f00d5dfb080>
 
 
 
@@ -384,7 +384,7 @@ Then, provide it as the regridder method as above:
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 4.055 seconds)
+   **Total running time of the script:** (0 minutes 4.034 seconds)
 
 
 .. _sphx_glr_download_examples_overlap_regridder.py: