[ci skip] Merge pull request #63 from ogrisel/fix-pytest-collection-path

FIX do not pytest collect outside of the hazardous module folder a245e87
soda-inria · Jul 3, 2024 · 124af1e · 124af1e
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diff --git a/.doctrees/auto_examples/plot_marginal_cumulative_incidence_estimation.doctree b/.doctrees/auto_examples/plot_marginal_cumulative_incidence_estimation.doctree
diff --git a/.doctrees/auto_examples/sg_execution_times.doctree b/.doctrees/auto_examples/sg_execution_times.doctree
diff --git a/.doctrees/environment.pickle b/.doctrees/environment.pickle
diff --git a/.doctrees/sg_execution_times.doctree b/.doctrees/sg_execution_times.doctree
diff --git a/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip b/_downloads/07fcc19ba03226cd3d83d4e40ec44385/auto_examples_python.zip
diff --git a/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip b/_downloads/6f1e7a639e0699d6164445b55e6c116d/auto_examples_jupyter.zip
diff --git a/_sources/auto_examples/plot_marginal_cumulative_incidence_estimation.rst.txt b/_sources/auto_examples/plot_marginal_cumulative_incidence_estimation.rst.txt
@@ -279,19 +279,19 @@ theoretical CIFs:
 
  .. code-block:: none
 
-    Integrated theoretical any event survival curve in 0.628 s
-    Integrated theoretical cumulative incidence curve for event 1 in 0.692 s
-    GB Incidence for event 1 fit in 0.479 s
+    Integrated theoretical any event survival curve in 0.591 s
+    Integrated theoretical cumulative incidence curve for event 1 in 0.653 s
+    GB Incidence for event 1 fit in 0.448 s
     GB Incidence for event 1 prediction in 0.082 s
-    Aalen-Johansen for event 1 fit in 5.195 s
-    Integrated theoretical cumulative incidence curve for event 2 in 5.388 s
-    GB Incidence for event 2 fit in 0.440 s
-    GB Incidence for event 2 prediction in 0.082 s
-    Aalen-Johansen for event 2 fit in 5.166 s
-    Integrated theoretical cumulative incidence curve for event 3 in 5.248 s
-    GB Incidence for event 3 fit in 0.429 s
+    Aalen-Johansen for event 1 fit in 5.187 s
+    Integrated theoretical cumulative incidence curve for event 2 in 5.364 s
+    GB Incidence for event 2 fit in 0.433 s
+    GB Incidence for event 2 prediction in 0.083 s
+    Aalen-Johansen for event 2 fit in 5.156 s
+    Integrated theoretical cumulative incidence curve for event 3 in 5.236 s
+    GB Incidence for event 3 fit in 0.450 s
     GB Incidence for event 3 prediction in 0.082 s
-    Aalen-Johansen for event 3 fit in 5.249 s
+    Aalen-Johansen for event 3 fit in 5.276 s
 
 
 
@@ -363,19 +363,19 @@ of censoring.
 
  .. code-block:: none
 
-    Integrated theoretical any event survival curve in 0.605 s
-    Integrated theoretical cumulative incidence curve for event 1 in 0.668 s
-    GB Incidence for event 1 fit in 0.449 s
-    GB Incidence for event 1 prediction in 0.083 s
-    Aalen-Johansen for event 1 fit in 5.208 s
-    Integrated theoretical cumulative incidence curve for event 2 in 5.316 s
-    GB Incidence for event 2 fit in 0.446 s
-    GB Incidence for event 2 prediction in 0.081 s
-    Aalen-Johansen for event 2 fit in 5.176 s
-    Integrated theoretical cumulative incidence curve for event 3 in 5.258 s
-    GB Incidence for event 3 fit in 0.420 s
-    GB Incidence for event 3 prediction in 0.083 s
-    Aalen-Johansen for event 3 fit in 5.164 s
+    Integrated theoretical any event survival curve in 0.591 s
+    Integrated theoretical cumulative incidence curve for event 1 in 0.653 s
+    GB Incidence for event 1 fit in 0.435 s
+    GB Incidence for event 1 prediction in 0.082 s
+    Aalen-Johansen for event 1 fit in 5.163 s
+    Integrated theoretical cumulative incidence curve for event 2 in 5.256 s
+    GB Incidence for event 2 fit in 0.439 s
+    GB Incidence for event 2 prediction in 0.082 s
+    Aalen-Johansen for event 2 fit in 5.180 s
+    Integrated theoretical cumulative incidence curve for event 3 in 5.260 s
+    GB Incidence for event 3 fit in 0.411 s
+    GB Incidence for event 3 prediction in 0.082 s
+    Aalen-Johansen for event 3 fit in 5.190 s
 
 
 
@@ -425,16 +425,16 @@ constraint:
 
  .. code-block:: none
 
-    Integrated theoretical any event survival curve in 0.600 s
-    Integrated theoretical cumulative incidence curve for event 1 in 0.663 s
-    GB Incidence for event 1 fit in 0.432 s
+    Integrated theoretical any event survival curve in 0.589 s
+    Integrated theoretical cumulative incidence curve for event 1 in 0.651 s
+    GB Incidence for event 1 fit in 0.428 s
     GB Incidence for event 1 prediction in 0.082 s
-    Integrated theoretical cumulative incidence curve for event 2 in 0.147 s
-    GB Incidence for event 2 fit in 0.441 s
+    Integrated theoretical cumulative incidence curve for event 2 in 0.145 s
+    GB Incidence for event 2 fit in 0.435 s
     GB Incidence for event 2 prediction in 0.081 s
-    Integrated theoretical cumulative incidence curve for event 3 in 0.147 s
-    GB Incidence for event 3 fit in 0.424 s
-    GB Incidence for event 3 prediction in 0.081 s
+    Integrated theoretical cumulative incidence curve for event 3 in 0.144 s
+    GB Incidence for event 3 fit in 0.418 s
+    GB Incidence for event 3 prediction in 0.082 s
 
 
 
@@ -450,7 +450,7 @@ uncertainty).
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 39.633 seconds)
+   **Total running time of the script:** (0 minutes 39.413 seconds)
 
 
 .. _sphx_glr_download_auto_examples_plot_marginal_cumulative_incidence_estimation.py:

diff --git a/_sources/auto_examples/sg_execution_times.rst.txt b/_sources/auto_examples/sg_execution_times.rst.txt
@@ -6,7 +6,7 @@
 
 Computation times
 =================
-**00:39.633** total execution time for 1 file **from auto_examples**:
+**00:39.413** total execution time for 1 file **from auto_examples**:
 
 .. container::
 
@@ -33,5 +33,5 @@ Computation times
      - Time
      - Mem (MB)
    * - :ref:`sphx_glr_auto_examples_plot_marginal_cumulative_incidence_estimation.py` (``plot_marginal_cumulative_incidence_estimation.py``)
-     - 00:39.633
+     - 00:39.413
      - 0.0
diff --git a/_sources/sg_execution_times.rst.txt b/_sources/sg_execution_times.rst.txt
@@ -6,7 +6,7 @@
 
 Computation times
 =================
-**00:39.633** total execution time for 1 file **from all galleries**:
+**00:39.413** total execution time for 1 file **from all galleries**:
 
 .. container::
 
@@ -33,5 +33,5 @@ Computation times
      - Time
      - Mem (MB)
    * - :ref:`sphx_glr_auto_examples_plot_marginal_cumulative_incidence_estimation.py` (``../examples/plot_marginal_cumulative_incidence_estimation.py``)
-     - 00:39.633
+     - 00:39.413
      - 0.0
diff --git a/auto_examples/plot_marginal_cumulative_incidence_estimation.html b/auto_examples/plot_marginal_cumulative_incidence_estimation.html
@@ -549,19 +549,19 @@ <h2>CIFs estimated on uncensored data<a class="headerlink" href="#cifs-estimated
 <span class="p">)</span>
 </pre></div>
 </div>
-<img src="../_images/sphx_glr_plot_marginal_cumulative_incidence_estimation_001.png" srcset="../_images/sphx_glr_plot_marginal_cumulative_incidence_estimation_001.png" alt="Cause-specific cumulative incidence functions (0.0% censoring), Event 1, Event 2, Event 3" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Integrated theoretical any event survival curve in 0.628 s
-Integrated theoretical cumulative incidence curve for event 1 in 0.692 s
-GB Incidence for event 1 fit in 0.479 s
+<img src="../_images/sphx_glr_plot_marginal_cumulative_incidence_estimation_001.png" srcset="../_images/sphx_glr_plot_marginal_cumulative_incidence_estimation_001.png" alt="Cause-specific cumulative incidence functions (0.0% censoring), Event 1, Event 2, Event 3" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Integrated theoretical any event survival curve in 0.591 s
+Integrated theoretical cumulative incidence curve for event 1 in 0.653 s
+GB Incidence for event 1 fit in 0.448 s
 GB Incidence for event 1 prediction in 0.082 s
-Aalen-Johansen for event 1 fit in 5.195 s
-Integrated theoretical cumulative incidence curve for event 2 in 5.388 s
-GB Incidence for event 2 fit in 0.440 s
-GB Incidence for event 2 prediction in 0.082 s
-Aalen-Johansen for event 2 fit in 5.166 s
-Integrated theoretical cumulative incidence curve for event 3 in 5.248 s
-GB Incidence for event 3 fit in 0.429 s
+Aalen-Johansen for event 1 fit in 5.187 s
+Integrated theoretical cumulative incidence curve for event 2 in 5.364 s
+GB Incidence for event 2 fit in 0.433 s
+GB Incidence for event 2 prediction in 0.083 s
+Aalen-Johansen for event 2 fit in 5.156 s
+Integrated theoretical cumulative incidence curve for event 3 in 5.236 s
+GB Incidence for event 3 fit in 0.450 s
 GB Incidence for event 3 prediction in 0.082 s
-Aalen-Johansen for event 3 fit in 5.249 s
+Aalen-Johansen for event 3 fit in 5.276 s
 </pre></div>
 </div>
 </section>
@@ -600,19 +600,19 @@ <h2>CIFs estimated on censored data<a class="headerlink" href="#cifs-estimated-o
 <span class="p">)</span>
 </pre></div>
 </div>
-<img src="../_images/sphx_glr_plot_marginal_cumulative_incidence_estimation_002.png" srcset="../_images/sphx_glr_plot_marginal_cumulative_incidence_estimation_002.png" alt="Cause-specific cumulative incidence functions (47.6% censoring), Event 1, Event 2, Event 3" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Integrated theoretical any event survival curve in 0.605 s
-Integrated theoretical cumulative incidence curve for event 1 in 0.668 s
-GB Incidence for event 1 fit in 0.449 s
-GB Incidence for event 1 prediction in 0.083 s
-Aalen-Johansen for event 1 fit in 5.208 s
-Integrated theoretical cumulative incidence curve for event 2 in 5.316 s
-GB Incidence for event 2 fit in 0.446 s
-GB Incidence for event 2 prediction in 0.081 s
-Aalen-Johansen for event 2 fit in 5.176 s
-Integrated theoretical cumulative incidence curve for event 3 in 5.258 s
-GB Incidence for event 3 fit in 0.420 s
-GB Incidence for event 3 prediction in 0.083 s
-Aalen-Johansen for event 3 fit in 5.164 s
+<img src="../_images/sphx_glr_plot_marginal_cumulative_incidence_estimation_002.png" srcset="../_images/sphx_glr_plot_marginal_cumulative_incidence_estimation_002.png" alt="Cause-specific cumulative incidence functions (47.6% censoring), Event 1, Event 2, Event 3" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Integrated theoretical any event survival curve in 0.591 s
+Integrated theoretical cumulative incidence curve for event 1 in 0.653 s
+GB Incidence for event 1 fit in 0.435 s
+GB Incidence for event 1 prediction in 0.082 s
+Aalen-Johansen for event 1 fit in 5.163 s
+Integrated theoretical cumulative incidence curve for event 2 in 5.256 s
+GB Incidence for event 2 fit in 0.439 s
+GB Incidence for event 2 prediction in 0.082 s
+Aalen-Johansen for event 2 fit in 5.180 s
+Integrated theoretical cumulative incidence curve for event 3 in 5.260 s
+GB Incidence for event 3 fit in 0.411 s
+GB Incidence for event 3 prediction in 0.082 s
+Aalen-Johansen for event 3 fit in 5.190 s
 </pre></div>
 </div>
 <p>Note that the Aalen-Johansen estimator is unbiased and empirically recovers
@@ -637,24 +637,24 @@ <h2>CIFs estimated on censored data<a class="headerlink" href="#cifs-estimated-o
 <span class="p">)</span>
 </pre></div>
 </div>
-<img src="../_images/sphx_glr_plot_marginal_cumulative_incidence_estimation_003.png" srcset="../_images/sphx_glr_plot_marginal_cumulative_incidence_estimation_003.png" alt="Cause-specific cumulative incidence functions (47.6% censoring), Event 1, Event 2, Event 3" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Integrated theoretical any event survival curve in 0.600 s
-Integrated theoretical cumulative incidence curve for event 1 in 0.663 s
-GB Incidence for event 1 fit in 0.432 s
+<img src="../_images/sphx_glr_plot_marginal_cumulative_incidence_estimation_003.png" srcset="../_images/sphx_glr_plot_marginal_cumulative_incidence_estimation_003.png" alt="Cause-specific cumulative incidence functions (47.6% censoring), Event 1, Event 2, Event 3" class = "sphx-glr-single-img"/><div class="sphx-glr-script-out highlight-none notranslate"><div class="highlight"><pre><span></span>Integrated theoretical any event survival curve in 0.589 s
+Integrated theoretical cumulative incidence curve for event 1 in 0.651 s
+GB Incidence for event 1 fit in 0.428 s
 GB Incidence for event 1 prediction in 0.082 s
-Integrated theoretical cumulative incidence curve for event 2 in 0.147 s
-GB Incidence for event 2 fit in 0.441 s
+Integrated theoretical cumulative incidence curve for event 2 in 0.145 s
+GB Incidence for event 2 fit in 0.435 s
 GB Incidence for event 2 prediction in 0.081 s
-Integrated theoretical cumulative incidence curve for event 3 in 0.147 s
-GB Incidence for event 3 fit in 0.424 s
-GB Incidence for event 3 prediction in 0.081 s
+Integrated theoretical cumulative incidence curve for event 3 in 0.144 s
+GB Incidence for event 3 fit in 0.418 s
+GB Incidence for event 3 prediction in 0.082 s
 </pre></div>
 </div>
 <p>The resulting incidence curves are indeed monotonic. However, for smaller
 training set sizes, the resulting models can be significantly biased, in
 particular large time horizons, where the CIFs are getting flatter. This
 effect diminishes with larger training set sizes (lower epistemic
 uncertainty).</p>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 39.633 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 39.413 seconds)</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-plot-marginal-cumulative-incidence-estimation-py">
 <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
 <p><a class="reference download internal" download="" href="../_downloads/2932d6ac7842b6d781c27c5737ae52fa/plot_marginal_cumulative_incidence_estimation.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">plot_marginal_cumulative_incidence_estimation.ipynb</span></code></a></p>

diff --git a/auto_examples/sg_execution_times.html b/auto_examples/sg_execution_times.html
@@ -339,7 +339,7 @@
 
   <section id="computation-times">
 <span id="sphx-glr-auto-examples-sg-execution-times"></span><h1>Computation times<a class="headerlink" href="#computation-times" title="Link to this heading">#</a></h1>
-<p><strong>00:39.633</strong> total execution time for 1 file <strong>from auto_examples</strong>:</p>
+<p><strong>00:39.413</strong> total execution time for 1 file <strong>from auto_examples</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" />
@@ -361,7 +361,7 @@
 </thead>
 <tbody>
 <tr class="row-even"><td><p><a class="reference internal" href="plot_marginal_cumulative_incidence_estimation.html#sphx-glr-auto-examples-plot-marginal-cumulative-incidence-estimation-py"><span class="std std-ref">Estimating marginal cumulative incidence functions</span></a> (<code class="docutils literal notranslate"><span class="pre">plot_marginal_cumulative_incidence_estimation.py</span></code>)</p></td>
-<td><p>00:39.633</p></td>
+<td><p>00:39.413</p></td>
 <td><p>0.0</p></td>
 </tr>
 </tbody>

diff --git a/searchindex.js b/searchindex.js
diff --git a/sg_execution_times.html b/sg_execution_times.html
@@ -339,7 +339,7 @@
 
   <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>00:39.633</strong> total execution time for 1 file <strong>from all galleries</strong>:</p>
+<p><strong>00:39.413</strong> total execution time for 1 file <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" />
@@ -361,7 +361,7 @@
 </thead>
 <tbody>
 <tr class="row-even"><td><p><a class="reference internal" href="auto_examples/plot_marginal_cumulative_incidence_estimation.html#sphx-glr-auto-examples-plot-marginal-cumulative-incidence-estimation-py"><span class="std std-ref">Estimating marginal cumulative incidence functions</span></a> (<code class="docutils literal notranslate"><span class="pre">../examples/plot_marginal_cumulative_incidence_estimation.py</span></code>)</p></td>
-<td><p>00:39.633</p></td>
+<td><p>00:39.413</p></td>
 <td><p>0.0</p></td>
 </tr>
 </tbody>