deploy: 9600cfe

README.html

@@ -300,16 +300,16 @@ <h2>What is this?<a class="headerlink" href="#what-is-this" title="Link to this
 <h2>What papers use this package?<a class="headerlink" href="#what-papers-use-this-package" title="Link to this heading">¶</a></h2>
 <p float="left">
   <a href="https://doi.org/10.1109/TBME.2024.3432800" target="_blank"> <img src="_static/papers/Learning.jpg" width="29%" /> </a>
-  &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
+  &nbsp;
   <a href="https://doi.org/10.33965/ijcsis_2024190101" target="_blank"> <img src="_static/papers/Analysis.jpg" width="26.5%" /> </a>
-  &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
+  &nbsp;
   <a href="https://doi.org/10.1101/2024.05.28.24307964" target="_blank"> <img src="_static/papers/Identification.jpg" width="29%" /> </a>
 </p>
 <p float="left">
 <a href="https://doi.org/10/gtm4bt" target="_blank"> <img src="_static/papers/Influence.jpg" width="26.5%" /> </a>
-  &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
+  &nbsp;
   <a href="https://doi.org/10/gsgk4s" target="_blank"> <img src="_static/papers/Proportional.jpg" width="29%" /> </a>
-  &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
+  &nbsp
   <a href="https://doi.org/10/gq2f47" target="_blank"> <img src="_static/papers/Accurate.jpg" width="29%" /> </a>
 </p>
 </section>
@@ -324,8 +324,8 @@ <h2>How to install?<a class="headerlink" href="#how-to-install" title="Link to t
 <li><p>install <a class="reference external" href="https://python-poetry.org/docs/#installation">poetry</a></p></li>
 <li><p>based on your hardware:</p>
 <ul>
-<li><p>GPU (NVIDIA): `poetry install</p></li>
-<li><p>CPU: run <code class="docutils literal notranslate"><span class="pre">pip</span> <span class="pre">install</span> <span class="pre">torch</span> <span class="pre">torchvision</span></code> after <code class="docutils literal notranslate"><span class="pre">poetry</span> <span class="pre">install</span></code></p></li>
+<li><p>GPU (NVIDIA): <code class="docutils literal notranslate"><span class="pre">poetry</span> <span class="pre">install</span></code></p></li>
+<li><p>CPU: run <code class="docutils literal notranslate"><span class="pre">pip</span> <span class="pre">install</span> <span class="pre">torch</span> <span class="pre">torchvision</span> <span class="pre">--upgrade</span></code> after <code class="docutils literal notranslate"><span class="pre">poetry</span> <span class="pre">install</span></code></p></li>
 </ul>
 </li>
 <li><p>for building the documentation add <code class="docutils literal notranslate"><span class="pre">docs</span></code> to the <em>with</em> flag: <code class="docutils literal notranslate"><span class="pre">poetry</span> <span class="pre">install</span> <span class="pre">--with</span> <span class="pre">docs</span></code></p></li>

_sources/README.md.txt

@@ -14,17 +14,17 @@ DocOctopy , the **research** library for kinematics, kinetics, and everything el
 ## What papers use this package?
 <p float="left">
   <a href="https://doi.org/10.1109/TBME.2024.3432800" target="_blank"> <img src="_static/papers/Learning.jpg" width="29%" /> </a>
-  &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
+  &nbsp;
   <a href="https://doi.org/10.33965/ijcsis_2024190101" target="_blank"> <img src="_static/papers/Analysis.jpg" width="26.5%" /> </a>
-  &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
+  &nbsp;
   <a href="https://doi.org/10.1101/2024.05.28.24307964" target="_blank"> <img src="_static/papers/Identification.jpg" width="29%" /> </a>
 </p>
 
 <p float="left">
 <a href="https://doi.org/10/gtm4bt" target="_blank"> <img src="_static/papers/Influence.jpg" width="26.5%" /> </a>
-  &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
+  &nbsp;
   <a href="https://doi.org/10/gsgk4s" target="_blank"> <img src="_static/papers/Proportional.jpg" width="29%" /> </a>
-  &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;
+  &nbsp
   <a href="https://doi.org/10/gq2f47" target="_blank"> <img src="_static/papers/Accurate.jpg" width="29%" /> </a>
 </p>
 
@@ -34,8 +34,8 @@ DocOctopy , the **research** library for kinematics, kinetics, and everything el
 - clone
 - install [poetry](https://python-poetry.org/docs/#installation)
 - based on your hardware:
-  - GPU (NVIDIA): `poetry install
-  - CPU: run `pip install torch torchvision` after `poetry install`
+  - GPU (NVIDIA): `poetry install`
+  - CPU: run `pip install torch torchvision --upgrade` after `poetry install`
 - for building the documentation add `docs` to the *with* flag: `poetry install --with docs`
 
 ## What is what?

_sources/auto_examples/1_understanding_basics.rst.txt

@@ -352,7 +352,7 @@ In case you do not want to index using the filter sequence name, you can retriev
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 5.617 seconds)
+   **Total running time of the script:** (0 minutes 5.164 seconds)
 
 **Estimated memory usage:**  553 MB
 

_sources/auto_examples/2_complex_filtering.rst.txt

@@ -461,9 +461,9 @@ This can be achieved in a more concise way by using the apply_filter_pipeline me
 
 .. rst-class:: sphx-glr-timing
 
-   **Total running time of the script:** (0 minutes 6.962 seconds)
+   **Total running time of the script:** (0 minutes 6.255 seconds)
 
-**Estimated memory usage:**  1314 MB
+**Estimated memory usage:**  1363 MB
 
 
 .. _sphx_glr_download_auto_examples_2_complex_filtering.py:

_sources/auto_examples/sg_execution_times.rst.txt

@@ -6,7 +6,7 @@
 
 Computation times
 =================
-**02:50.639** total execution time for 4 files **from auto_examples**:
+**02:49.599** total execution time for 4 files **from auto_examples**:
 
 .. container::
 
@@ -33,14 +33,14 @@ Computation times
      - Time
      - Mem (MB)
    * - :ref:`sphx_glr_auto_examples_4_train_model.py` (``4_train_model.py``)
-     - 02:18.109
-     - 114.9
+     - 02:18.261
+     - 114.8
    * - :ref:`sphx_glr_auto_examples_3_create_dataset.py` (``3_create_dataset.py``)
-     - 00:19.950
-     - 982.8
+     - 00:19.919
+     - 945.3
    * - :ref:`sphx_glr_auto_examples_2_complex_filtering.py` (``2_complex_filtering.py``)
-     - 00:06.962
-     - 1313.5
+     - 00:06.255
+     - 1363.1
    * - :ref:`sphx_glr_auto_examples_1_understanding_basics.py` (``1_understanding_basics.py``)
-     - 00:05.617
-     - 553.5
+     - 00:05.164
+     - 553.4

_sources/sg_execution_times.rst.txt

@@ -6,7 +6,7 @@
 
 Computation times
 =================
-**02:50.639** total execution time for 4 files **from all galleries**:
+**02:49.599** total execution time for 4 files **from all galleries**:
 
 .. container::
 
@@ -33,14 +33,14 @@ Computation times
      - Time
      - Mem (MB)
    * - :ref:`sphx_glr_auto_examples_4_train_model.py` (``../../examples/4_train_model.py``)
-     - 02:18.109
-     - 114.9
+     - 02:18.261
+     - 114.8
    * - :ref:`sphx_glr_auto_examples_3_create_dataset.py` (``../../examples/3_create_dataset.py``)
-     - 00:19.950
-     - 982.8
+     - 00:19.919
+     - 945.3
    * - :ref:`sphx_glr_auto_examples_2_complex_filtering.py` (``../../examples/2_complex_filtering.py``)
-     - 00:06.962
-     - 1313.5
+     - 00:06.255
+     - 1363.1
    * - :ref:`sphx_glr_auto_examples_1_understanding_basics.py` (``../../examples/1_understanding_basics.py``)
-     - 00:05.617
-     - 553.5
+     - 00:05.164
+     - 553.4

auto_examples/1_understanding_basics.html

@@ -482,7 +482,7 @@ <h2>Accessing the filtered data<a class="headerlink" href="#accessing-the-filter
 True
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 5.617 seconds)</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 5.164 seconds)</p>
 <p><strong>Estimated memory usage:</strong>  553 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-1-understanding-basics-py">
 <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">

auto_examples/2_complex_filtering.html

@@ -575,8 +575,8 @@ <h2>Easier way of applying the filter pipeline<a class="headerlink" href="#easie
 --
 </pre></div>
 </div>
-<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 6.962 seconds)</p>
-<p><strong>Estimated memory usage:</strong>  1314 MB</p>
+<p class="sphx-glr-timing"><strong>Total running time of the script:</strong> (0 minutes 6.255 seconds)</p>
+<p><strong>Estimated memory usage:</strong>  1363 MB</p>
 <div class="sphx-glr-footer sphx-glr-footer-example docutils container" id="sphx-glr-download-auto-examples-2-complex-filtering-py">
 <div class="sphx-glr-download sphx-glr-download-jupyter docutils container">
 <p><a class="reference download internal" download="" href="../_downloads/05bdb3140c2c6ae43d9ab96ca1aabb68/2_complex_filtering.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">2_complex_filtering.ipynb</span></code></a></p>