CircleCI update of dev docs (460).

dev/_sources/auto_examples/affinities/demo_ea_adaptivity.rst.txt

@@ -207,7 +207,7 @@ This affinity is an important component of the **TSNE** algorithm.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 2.973 seconds)
+   **Total running time of the script:** (0 minutes 3.166 seconds)
 
 
 .. _sphx_glr_download_auto_examples_affinities_demo_ea_adaptivity.py:

dev/_sources/auto_examples/affinities/sg_execution_times.rst.txt

@@ -6,7 +6,7 @@
 
 Computation times
 =================
-**00:02.973** total execution time for 1 file **from auto_examples/affinities**:
+**00:03.166** total execution time for 1 file **from auto_examples/affinities**:
 
 .. container::
 
@@ -33,5 +33,5 @@ Computation times
      - Time
      - Mem (MB)
    * - :ref:`sphx_glr_auto_examples_affinities_demo_ea_adaptivity.py` (``demo_ea_adaptivity.py``)
-     - 00:02.973
+     - 00:03.166
      - 0.0

dev/_sources/auto_examples/basics/demo_ne_methods_affinity_matcher.rst.txt

@@ -249,7 +249,7 @@ On the efficiency of using the torchdr API rather than AffinityMatcher directly
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 56.286 seconds)
+   **Total running time of the script:** (1 minutes 14.869 seconds)
 
 
 .. _sphx_glr_download_auto_examples_basics_demo_ne_methods_affinity_matcher.py:

dev/_sources/auto_examples/basics/demo_pca_via_affinity_matcher.rst.txt

@@ -158,7 +158,7 @@ both methods.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 5.006 seconds)
+   **Total running time of the script:** (0 minutes 5.351 seconds)
 
 
 .. _sphx_glr_download_auto_examples_basics_demo_pca_via_affinity_matcher.py:

dev/_sources/auto_examples/basics/demo_tsne_swiss_roll.rst.txt

@@ -215,7 +215,7 @@ mistakenly considered neighbors.
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (1 minutes 7.864 seconds)
+   **Total running time of the script:** (1 minutes 14.668 seconds)
 
 
 .. _sphx_glr_download_auto_examples_basics_demo_tsne_swiss_roll.py:

dev/_sources/auto_examples/basics/sg_execution_times.rst.txt

@@ -6,7 +6,7 @@
 
 Computation times
 =================
-**02:09.157** total execution time for 3 files **from auto_examples/basics**:
+**02:34.888** total execution time for 3 files **from auto_examples/basics**:
 
 .. container::
 
@@ -32,12 +32,12 @@ Computation times
    * - Example
      - Time
      - Mem (MB)
-   * - :ref:`sphx_glr_auto_examples_basics_demo_tsne_swiss_roll.py` (``demo_tsne_swiss_roll.py``)
-     - 01:07.864
-     - 0.0
    * - :ref:`sphx_glr_auto_examples_basics_demo_ne_methods_affinity_matcher.py` (``demo_ne_methods_affinity_matcher.py``)
-     - 00:56.286
+     - 01:14.869
+     - 0.0
+   * - :ref:`sphx_glr_auto_examples_basics_demo_tsne_swiss_roll.py` (``demo_tsne_swiss_roll.py``)
+     - 01:14.668
      - 0.0
    * - :ref:`sphx_glr_auto_examples_basics_demo_pca_via_affinity_matcher.py` (``demo_pca_via_affinity_matcher.py``)
-     - 00:05.006
+     - 00:05.351
      - 0.0

dev/_sources/sg_execution_times.rst.txt

@@ -6,7 +6,7 @@
 
 Computation times
 =================
-**02:12.130** total execution time for 4 files **from all galleries**:
+**02:38.054** total execution time for 4 files **from all galleries**:
 
 .. container::
 
@@ -32,15 +32,15 @@ Computation times
    * - Example
      - Time
      - Mem (MB)
-   * - :ref:`sphx_glr_auto_examples_basics_demo_tsne_swiss_roll.py` (``../../examples/basics/demo_tsne_swiss_roll.py``)
-     - 01:07.864
-     - 0.0
    * - :ref:`sphx_glr_auto_examples_basics_demo_ne_methods_affinity_matcher.py` (``../../examples/basics/demo_ne_methods_affinity_matcher.py``)
-     - 00:56.286
+     - 01:14.869
+     - 0.0
+   * - :ref:`sphx_glr_auto_examples_basics_demo_tsne_swiss_roll.py` (``../../examples/basics/demo_tsne_swiss_roll.py``)
+     - 01:14.668
      - 0.0
    * - :ref:`sphx_glr_auto_examples_basics_demo_pca_via_affinity_matcher.py` (``../../examples/basics/demo_pca_via_affinity_matcher.py``)
-     - 00:05.006
+     - 00:05.351
      - 0.0
    * - :ref:`sphx_glr_auto_examples_affinities_demo_ea_adaptivity.py` (``../../examples/affinities/demo_ea_adaptivity.py``)
-     - 00:02.973
+     - 00:03.166
      - 0.0

dev/auto_examples/affinities/demo_ea_adaptivity.html

@@ -208,7 +208,7 @@ <h2>Entropic affinity (adaptive bandwidth)<a class="headerlink" href="#entropic-
 <img src="../../_images/sphx_glr_demo_ea_adaptivity_002.png" srcset="../../_images/sphx_glr_demo_ea_adaptivity_002.png" alt="Entropic Affinity Matrix, Entropic Affinity Graph" class = "sphx-glr-single-img"/><p>We can now observe a <strong>homogeneous density of connections</strong> across clusters.
 Thus, the entropic affinity effectively filters out the various noise levels.</p>
 <p>This affinity is an important component of the <strong>TSNE</strong> algorithm.</p>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 2.973 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 3.166 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-affinities-demo-ea-adaptivity-py">
 <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/17d429f11ca029172465ca0d7bb1879e/demo_ea_adaptivity.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">demo_ea_adaptivity.ipynb</span></code></a></p>

dev/auto_examples/affinities/sg_execution_times.html

@@ -84,7 +84,7 @@
 
   <section id="computation-times">
 <span id="sphx-glr-auto-examples-affinities-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Link to this heading"></a></h1>
-<p><strong>00:02.973</strong> total execution time for 1 file <strong>from auto_examples/affinities</strong>:</p>
+<p><strong>00:03.166</strong> total execution time for 1 file <strong>from auto_examples/affinities</strong>:</p>
 <div class="docutils container">
 <style scoped>
 <link href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/5.3.0/css/bootstrap.min.css" rel="stylesheet" />
@@ -106,7 +106,7 @@
 </thead>
 <tbody>
 <tr class="row-even"><td><p><a class="reference internal" href="demo_ea_adaptivity.html#sphx-glr-auto-examples-affinities-demo-ea-adaptivity-py"><span class="std std-ref">Entropic Affinities can adapt to varying noise levels</span></a> (<code class="docutils literal notranslate"><span class="pre">demo_ea_adaptivity.py</span></code>)</p></td>
-<td><p>00:02.973</p></td>
+<td><p>00:03.166</p></td>
 <td><p>0.0</p></td>
 </tr>
 </tbody>

dev/auto_examples/basics/demo_ne_methods_affinity_matcher.html

@@ -240,7 +240,7 @@ <h2>On the efficiency of using the torchdr API rather than AffinityMatcher direc
 In TorchDR, it is therefore recommended to use the specific class associated
 with the desired algorithm when available.</p>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 56.286 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (1 minutes 14.869 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-basics-demo-ne-methods-affinity-matcher-py">
 <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/286dcc8a82b9a5553a5d809cc0f6fa61/demo_ne_methods_affinity_matcher.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">demo_ne_methods_affinity_matcher.ipynb</span></code></a></p>

dev/auto_examples/basics/demo_pca_via_affinity_matcher.html

@@ -170,7 +170,7 @@ <h2>PCA via AffinityMatcher<a class="headerlink" href="#pca-via-affinitymatcher"
 </div>
 <img src="../../_images/sphx_glr_demo_pca_via_affinity_matcher_002.png" srcset="../../_images/sphx_glr_demo_pca_via_affinity_matcher_002.png" alt="PCA via AffinityMatcher" class = "sphx-glr-single-img"/><p>We can see that we obtain the same PCA embedding (up to a rotation) using
 both methods.</p>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 5.006 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 5.351 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-basics-demo-pca-via-affinity-matcher-py">
 <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/01119b09b904483a657e921d21bc15d1/demo_pca_via_affinity_matcher.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">demo_pca_via_affinity_matcher.ipynb</span></code></a></p>

dev/auto_examples/basics/demo_tsne_swiss_roll.html

@@ -186,7 +186,7 @@ <h2>See the impact of perplexity<a class="headerlink" href="#see-the-impact-of-p
 and fails to capture the manifold’s geometry. Conversely, when the perplexity is too
 high, points that are distant on the manifold but close in the ambient space are
 mistakenly considered neighbors.</p>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (1 minutes 7.864 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (1 minutes 14.668 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-basics-demo-tsne-swiss-roll-py">
 <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
 <p><a class="reference download internal" download="" href="../../_downloads/d07a5a618e87545c420604821fa60541/demo_tsne_swiss_roll.ipynb"><code class="xref download docutils literal notranslate"><span class="pre">Download</span> <span class="pre">Jupyter</span> <span class="pre">notebook:</span> <span class="pre">demo_tsne_swiss_roll.ipynb</span></code></a></p>

dev/auto_examples/basics/sg_execution_times.html

@@ -84,7 +84,7 @@
 
   <section id="computation-times">
 <span id="sphx-glr-auto-examples-basics-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Link to this heading"></a></h1>
-<p><strong>02:09.157</strong> total execution time for 3 files <strong>from auto_examples/basics</strong>:</p>
+<p><strong>02:34.888</strong> total execution time for 3 files <strong>from auto_examples/basics</strong>:</p>
 <div class="docutils container">
 <style scoped>
 <link href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/5.3.0/css/bootstrap.min.css" rel="stylesheet" />
@@ -105,16 +105,16 @@
 </tr>
 </thead>
 <tbody>
-<tr class="row-even"><td><p><a class="reference internal" href="demo_tsne_swiss_roll.html#sphx-glr-auto-examples-basics-demo-tsne-swiss-roll-py"><span class="std std-ref">TSNE embedding of the swiss roll dataset</span></a> (<code class="docutils literal notranslate"><span class="pre">demo_tsne_swiss_roll.py</span></code>)</p></td>
-<td><p>01:07.864</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="demo_ne_methods_affinity_matcher.html#sphx-glr-auto-examples-basics-demo-ne-methods-affinity-matcher-py"><span class="std std-ref">Neighbor Embedding on genomics &amp; equivalent affinity matcher formulation</span></a> (<code class="docutils literal notranslate"><span class="pre">demo_ne_methods_affinity_matcher.py</span></code>)</p></td>
+<td><p>01:14.869</p></td>
 <td><p>0.0</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="demo_ne_methods_affinity_matcher.html#sphx-glr-auto-examples-basics-demo-ne-methods-affinity-matcher-py"><span class="std std-ref">Neighbor Embedding on genomics &amp; equivalent affinity matcher formulation</span></a> (<code class="docutils literal notranslate"><span class="pre">demo_ne_methods_affinity_matcher.py</span></code>)</p></td>
-<td><p>00:56.286</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="demo_tsne_swiss_roll.html#sphx-glr-auto-examples-basics-demo-tsne-swiss-roll-py"><span class="std std-ref">TSNE embedding of the swiss roll dataset</span></a> (<code class="docutils literal notranslate"><span class="pre">demo_tsne_swiss_roll.py</span></code>)</p></td>
+<td><p>01:14.668</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="demo_pca_via_affinity_matcher.html#sphx-glr-auto-examples-basics-demo-pca-via-affinity-matcher-py"><span class="std std-ref">PCA via SVD and via AffinityMatcher</span></a> (<code class="docutils literal notranslate"><span class="pre">demo_pca_via_affinity_matcher.py</span></code>)</p></td>
-<td><p>00:05.006</p></td>
+<td><p>00:05.351</p></td>
 <td><p>0.0</p></td>
 </tr>
 </tbody>

dev/sg_execution_times.html

@@ -84,7 +84,7 @@
 
   <section id="computation-times">
 <span id="sphx-glr-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Link to this heading"></a></h1>
-<p><strong>02:12.130</strong> total execution time for 4 files <strong>from all galleries</strong>:</p>
+<p><strong>02:38.054</strong> total execution time for 4 files <strong>from all galleries</strong>:</p>
 <div class="docutils container">
 <style scoped>
 <link href="https://cdnjs.cloudflare.com/ajax/libs/twitter-bootstrap/5.3.0/css/bootstrap.min.css" rel="stylesheet" />
@@ -105,20 +105,20 @@
 </tr>
 </thead>
 <tbody>
-<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/basics/demo_tsne_swiss_roll.html#sphx-glr-auto-examples-basics-demo-tsne-swiss-roll-py"><span class="std std-ref">TSNE embedding of the swiss roll dataset</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/basics/demo_tsne_swiss_roll.py</span></code>)</p></td>
-<td><p>01:07.864</p></td>
+<tr class="row-even"><td><p><a class="reference internal" href="auto_examples/basics/demo_ne_methods_affinity_matcher.html#sphx-glr-auto-examples-basics-demo-ne-methods-affinity-matcher-py"><span class="std std-ref">Neighbor Embedding on genomics &amp; equivalent affinity matcher formulation</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/basics/demo_ne_methods_affinity_matcher.py</span></code>)</p></td>
+<td><p>01:14.869</p></td>
 <td><p>0.0</p></td>
 </tr>
-<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/basics/demo_ne_methods_affinity_matcher.html#sphx-glr-auto-examples-basics-demo-ne-methods-affinity-matcher-py"><span class="std std-ref">Neighbor Embedding on genomics &amp; equivalent affinity matcher formulation</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/basics/demo_ne_methods_affinity_matcher.py</span></code>)</p></td>
-<td><p>00:56.286</p></td>
+<tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/basics/demo_tsne_swiss_roll.html#sphx-glr-auto-examples-basics-demo-tsne-swiss-roll-py"><span class="std std-ref">TSNE embedding of the swiss roll dataset</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/basics/demo_tsne_swiss_roll.py</span></code>)</p></td>
+<td><p>01:14.668</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-even"><td><p><a class="reference internal" href="auto_examples/basics/demo_pca_via_affinity_matcher.html#sphx-glr-auto-examples-basics-demo-pca-via-affinity-matcher-py"><span class="std std-ref">PCA via SVD and via AffinityMatcher</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/basics/demo_pca_via_affinity_matcher.py</span></code>)</p></td>
-<td><p>00:05.006</p></td>
+<td><p>00:05.351</p></td>
 <td><p>0.0</p></td>
 </tr>
 <tr class="row-odd"><td><p><a class="reference internal" href="auto_examples/affinities/demo_ea_adaptivity.html#sphx-glr-auto-examples-affinities-demo-ea-adaptivity-py"><span class="std std-ref">Entropic Affinities can adapt to varying noise levels</span></a> (<code class="docutils literal notranslate"><span class="pre">../../examples/affinities/demo_ea_adaptivity.py</span></code>)</p></td>
-<td><p>00:02.973</p></td>
+<td><p>00:03.166</p></td>
 <td><p>0.0</p></td>
 </tr>
 </tbody>