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auto_examples/it/plot_entropies.html

@@ -591,7 +591,7 @@ <h2>Entropy of data sampled from an exponential distribution<a class="headerlink
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+<img src="../../_images/sphx_glr_plot_entropies_003.png" srcset="../../_images/sphx_glr_plot_entropies_003.png" alt="Comparison of entropy estimators when the data are sampled from a exponential distribution" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 20.386 seconds)</p>
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auto_examples/it/plot_entropies_mvar.html

@@ -567,7 +567,7 @@ <h2>Comparison of estimators<a class="headerlink" href="#comparison-of-estimator
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+<img src="../../_images/sphx_glr_plot_entropies_mvar_001.png" srcset="../../_images/sphx_glr_plot_entropies_mvar_001.png" alt="2-dimensional multivariate normal, 4-dimensional multivariate normal, 6-dimensional multivariate normal, 8-dimensional multivariate normal" class = "sphx-glr-single-img"/><p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 32.307 seconds)</p>
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auto_examples/it/plot_entropy_high_dimensional.html

@@ -564,7 +564,7 @@ <h2>Definition of entropy estimators<a class="headerlink" href="#definition-of-e
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auto_examples/it/plot_mi.html

@@ -556,7 +556,7 @@ <h2>MI of data sampled from normal distribution<a class="headerlink" href="#mi-o
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auto_examples/it/plot_mi_high_dimensional.html

@@ -568,7 +568,7 @@ <h2>MI of data sampled from splitted multinormal distribution<a class="headerlin
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auto_examples/it/sg_execution_times.html

@@ -404,7 +404,7 @@ <h1>Computation times</h1>
 
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-<p><strong>02:09.017</strong> total execution time for 6 files <strong>from auto_examples/it</strong>:</p>
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-<td><p>00:20.927</p></td>
+<td><p>00:20.743</p></td>
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 <tr class="row-even"><td><p><a class="reference internal" href="plot_entropies.html#sphx-glr-auto-examples-it-plot-entropies-py"><span class="std std-ref">Comparison of entropy estimators for various distributions</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_entropies.py</span></code>)</p></td>
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+<td><p>00:20.386</p></td>
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 <tr class="row-odd"><td><p><a class="reference internal" href="tuto_core.html#sphx-glr-auto-examples-it-tuto-core-py"><span class="std std-ref">Introduction to core information theoretical metrics</span></a> (<code class="docutils literal notranslate"><span class="pre">tuto_core.py</span></code>)</p></td>
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+<td><p>00:00.232</p></td>
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auto_examples/it/tuto_core.html

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auto_examples/metrics/plot_infotopo.html

@@ -471,11 +471,11 @@ <h2>Spatial spreading : the problem with the O-information<a class="headerlink"
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+100%|██████████| Oinfo (7):  5/5 [00:01&lt;00:00,    2.68it/s]
 </pre></div>
 </div>
 <p>Now we can plot the landscape. This landscape show the values of HOI for
@@ -528,19 +528,19 @@ <h2>Multiplet isolation using the Topological Information<a class="headerlink" h
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+100%|██████████| Entropy H(7):  7/7 [00:00&lt;00:00,    9.37it/s]
 
 
 Mutual information:   0%|          | 0/99 [00:00&lt;?, ?it/s]
 
 
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 </pre></div>
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 <p>Again, we can plot the landscape. This time, as we can see, there’s no more
@@ -574,7 +574,7 @@ <h2>Multiplet isolation using the Topological Information<a class="headerlink" h
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