deploy: 0142412

.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: 8d20069a5ad17e464a276db66857ed03
+config: 4d98c0a32dca65a16f68eb1fcde32261
 tags: 645f666f9bcd5a90fca523b33c5a78b7

_modules/xugrid/ugrid/ugrid2d.html

@@ -2482,10 +2482,16 @@ <h1>Source code for xugrid.ugrid.ugrid2d</h1><div class="highlight"><pre>
         <span class="c1"># Allocate face_node_connectivity</span>
         <span class="n">face_nodes</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">empty</span><span class="p">((</span><span class="n">ny</span> <span class="o">*</span> <span class="n">nx</span><span class="p">,</span> <span class="mi">4</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="n">IntDType</span><span class="p">)</span>
         <span class="c1"># Set connectivity in counterclockwise manner</span>
-        <span class="n">face_nodes</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">linear_index</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">:]</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span>  <span class="c1"># upper right</span>
-        <span class="n">face_nodes</span><span class="p">[:,</span> <span class="mi">1</span><span class="p">]</span> <span class="o">=</span> <span class="n">linear_index</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span>  <span class="c1"># upper left</span>
-        <span class="n">face_nodes</span><span class="p">[:,</span> <span class="mi">2</span><span class="p">]</span> <span class="o">=</span> <span class="n">linear_index</span><span class="p">[</span><span class="mi">1</span><span class="p">:,</span> <span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span>  <span class="c1"># lower left</span>
-        <span class="n">face_nodes</span><span class="p">[:,</span> <span class="mi">3</span><span class="p">]</span> <span class="o">=</span> <span class="n">linear_index</span><span class="p">[</span><span class="mi">1</span><span class="p">:,</span> <span class="mi">1</span><span class="p">:]</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span>  <span class="c1"># lower right</span>
+        <span class="n">left</span><span class="p">,</span> <span class="n">right</span> <span class="o">=</span> <span class="nb">slice</span><span class="p">(</span><span class="kc">None</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">),</span> <span class="nb">slice</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
+        <span class="n">lower</span><span class="p">,</span> <span class="n">upper</span> <span class="o">=</span> <span class="nb">slice</span><span class="p">(</span><span class="kc">None</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">),</span> <span class="nb">slice</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
+        <span class="k">if</span> <span class="n">node_x</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">&lt;</span> <span class="n">node_x</span><span class="p">[</span><span class="mi">0</span><span class="p">]:</span>  <span class="c1"># x_decreasing</span>
+            <span class="n">left</span><span class="p">,</span> <span class="n">right</span> <span class="o">=</span> <span class="n">right</span><span class="p">,</span> <span class="n">left</span>
+        <span class="k">if</span> <span class="n">node_y</span><span class="p">[</span><span class="n">ny</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]</span> <span class="o">&lt;</span> <span class="n">node_y</span><span class="p">[</span><span class="mi">0</span><span class="p">]:</span>  <span class="c1"># y_decreasing</span>
+            <span class="n">lower</span><span class="p">,</span> <span class="n">upper</span> <span class="o">=</span> <span class="n">upper</span><span class="p">,</span> <span class="n">lower</span>
+        <span class="n">face_nodes</span><span class="p">[:,</span> <span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="n">linear_index</span><span class="p">[</span><span class="n">lower</span><span class="p">,</span> <span class="n">left</span><span class="p">]</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span>
+        <span class="n">face_nodes</span><span class="p">[:,</span> <span class="mi">1</span><span class="p">]</span> <span class="o">=</span> <span class="n">linear_index</span><span class="p">[</span><span class="n">lower</span><span class="p">,</span> <span class="n">right</span><span class="p">]</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span>
+        <span class="n">face_nodes</span><span class="p">[:,</span> <span class="mi">2</span><span class="p">]</span> <span class="o">=</span> <span class="n">linear_index</span><span class="p">[</span><span class="n">upper</span><span class="p">,</span> <span class="n">right</span><span class="p">]</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span>
+        <span class="n">face_nodes</span><span class="p">[:,</span> <span class="mi">3</span><span class="p">]</span> <span class="o">=</span> <span class="n">linear_index</span><span class="p">[</span><span class="n">upper</span><span class="p">,</span> <span class="n">left</span><span class="p">]</span><span class="o">.</span><span class="n">ravel</span><span class="p">()</span>
         <span class="k">return</span> <span class="n">Ugrid2d</span><span class="p">(</span><span class="n">node_x</span><span class="p">,</span> <span class="n">node_y</span><span class="p">,</span> <span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">face_nodes</span><span class="p">)</span>
 
 <div class="viewcode-block" id="Ugrid2d.from_structured_intervals1d">

_sources/examples-dev/sg_execution_times.rst.txt

@@ -6,8 +6,8 @@
 
 Computation times
 =================
-**00:01.305** total execution time for **examples-dev** files:
+**00:01.224** total execution time for **examples-dev** files:
 
 +----------------------------------------------------------+-----------+--------+
-| :ref:`sphx_glr_examples-dev_voronoi.py` (``voronoi.py``) | 00:01.305 | 0.0 MB |
+| :ref:`sphx_glr_examples-dev_voronoi.py` (``voronoi.py``) | 00:01.224 | 0.0 MB |
 +----------------------------------------------------------+-----------+--------+

_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 1.305 seconds)
+   **Total running time of the script:** (0 minutes 1.224 seconds)
 
 
 .. _sphx_glr_download_examples-dev_voronoi.py:

_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 0x7f212d786790>
+    <matplotlib.collections.PolyCollection object at 0x7fcdb71607d0>
 
 
 
@@ -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 0x7f213980d790>
+    <matplotlib.collections.PolyCollection object at 0x7fcdc38fd810>
 
 
 
@@ -200,7 +200,7 @@ alternative border value:
  .. code-block:: none
 
 
-    <matplotlib.collections.PolyCollection object at 0x7f2138ae2150>
+    <matplotlib.collections.PolyCollection object at 0x7fcdb7d04910>
 
 
 
@@ -238,7 +238,7 @@ analyse connected parts of the mesh.
  .. code-block:: none
 
 
-    <matplotlib.collections.PolyCollection object at 0x7f212d4f2850>
+    <matplotlib.collections.PolyCollection object at 0x7fcdb84a9710>
 
 
 
@@ -272,7 +272,7 @@ Tesselation.
  .. code-block:: none
 
 
-    <matplotlib.collections.LineCollection object at 0x7f212c2b1610>
+    <matplotlib.collections.LineCollection object at 0x7fcdb8f39510>
 
 
 
@@ -316,7 +316,7 @@ the original.
  .. code-block:: none
 
 
-    <matplotlib.collections.LineCollection object at 0x7f212c35c0d0>
+    <matplotlib.collections.LineCollection object at 0x7fcdc38a1450>
 
 
 
@@ -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 0x7f212d293c10>
+    <matplotlib.collections.LineCollection object at 0x7fcdb7a60f50>
 
 
 
@@ -409,7 +409,7 @@ the upper and lower parts:
  .. code-block:: none
 
 
-    <matplotlib.collections.LineCollection object at 0x7f212cecd2d0>
+    <matplotlib.collections.LineCollection object at 0x7fcdb71301d0>
 
 
 
@@ -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 0x7f212d1e6450>
+    <matplotlib.collections.PolyCollection object at 0x7fcdb7f5d810>
 
 
 
@@ -477,7 +477,7 @@ interpolation.
  .. code-block:: none
 
 
-    <matplotlib.collections.PolyCollection object at 0x7f212ce11710>
+    <matplotlib.collections.PolyCollection object at 0x7fcdb832c6d0>
 
 
 
@@ -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 0x7f212cf1af50>
+    <matplotlib.image.AxesImage object at 0x7fcdb84eb750>
 
 
 
@@ -554,14 +554,14 @@ locality:
  .. code-block:: none
 
 
-    <matplotlib.image.AxesImage object at 0x7f212d6e8d90>
+    <matplotlib.image.AxesImage object at 0x7fcdb856ad50>
 
 
 
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 1.665 seconds)
+   **Total running time of the script:** (0 minutes 1.659 seconds)
 
 
 .. _sphx_glr_download_examples_connectivity.py:

_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 0x7f2138a86590>
+    <matplotlib.collections.LineCollection object at 0x7fcdb7c8a1d0>
 
 
 
@@ -202,7 +202,7 @@ conservative methods, such as conductance:
  .. code-block:: none
 
 
-    <matplotlib.collections.PolyCollection object at 0x7f212e105790>
+    <matplotlib.collections.PolyCollection object at 0x7fcdb8065890>
 
 
 
@@ -280,7 +280,7 @@ To use our custom method, we provide at initialization of the OverlapRegridder:
  .. code-block:: none
 
 
-    <matplotlib.collections.PolyCollection object at 0x7f212c2e5ad0>
+    <matplotlib.collections.PolyCollection object at 0x7fcdb85d1690>
 
 
 
@@ -320,7 +320,7 @@ function can deal with NaN values! -- hence ``nanpercentile`` rather than
  .. code-block:: none
 
 
-    <matplotlib.collections.PolyCollection object at 0x7f212d7d7090>
+    <matplotlib.collections.PolyCollection object at 0x7fcdb85e9cd0>
 
 
 
@@ -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 3.981 seconds)
+   **Total running time of the script:** (0 minutes 4.012 seconds)
 
 
 .. _sphx_glr_download_examples_overlap_regridder.py: