New Publications

docs/EHupdates.rst

@@ -1,6 +1,6 @@
 .. image:: https://raw.githubusercontent.com/MattWillFlood/EntropyHub/main/metrics.entropyhub.svg
     :align: right
-    :height: 80px
+    :height: 50px
     :target: https://github.com/MattWillFlood/EntropyHub
 
 **************

docs/Home.rst

@@ -18,7 +18,7 @@ An open-source toolkit for entropic data analysis
     :height: 150px
 
 .. centered:: Available in: 
-.. centered:: `Matlab  <https://www.mathworks.com/matlabcentral/fileexchange/94185-entropyhub>`_ // `Python <https://pypi.org/project/EntropyHub/>`_  // `Julia <https://mattwillflood.github.io/EntropyHub.jl/stable/>`_
+.. centered:: `Matlab  <https://www.mathworks.com/matlabcentral/fileexchange/94185-entropyhub>`_ // `Python <https://pypi.org/project/EntropyHub/>`_  // `Julia <https://mattwillflood.github.io/EntropyHub.jl/stable/>`_ 
 
 .. toctree::
    :maxdepth: 3

docs/_build/html/EHupdates.html

@@ -124,8 +124,8 @@
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="julia/EHjulia.html">EntropyHub - Julia</a><ul>
-<li class="toctree-l2"><a class="reference external" href="https://docs.juliahub.com/EntropyHub/npy5E/0.2.0/">EntropyHub.jl</a></li>
-<li class="toctree-l2"><a class="reference external" href="https://mattwillflood.github.io/EntropyHub.jl/Examples/Examples">Examples</a></li>
+<li class="toctree-l2"><a class="reference external" href="https://mattwillflood.github.io/EntropyHub.jl/stable/">EntropyHub.jl</a></li>
+<li class="toctree-l2"><a class="reference external" href="https://mattwillflood.github.io/EntropyHub.jl/stable/Examples/Examples">Examples</a></li>
 </ul>
 </li>
 </ul>
@@ -155,7 +155,7 @@
           <div role="main" class="document" itemscope="itemscope" itemtype="http://schema.org/Article">
            <div itemprop="articleBody">
 
-  <a class="reference external image-reference" href="https://github.com/MattWillFlood/EntropyHub"><img alt="https://raw.githubusercontent.com/MattWillFlood/EntropyHub/main/metrics.entropyhub.svg" class="align-right" height="80px" src="https://raw.githubusercontent.com/MattWillFlood/EntropyHub/main/metrics.entropyhub.svg" /></a>
+  <a class="reference external image-reference" href="https://github.com/MattWillFlood/EntropyHub"><img alt="https://raw.githubusercontent.com/MattWillFlood/EntropyHub/main/metrics.entropyhub.svg" class="align-right" height="50px" src="https://raw.githubusercontent.com/MattWillFlood/EntropyHub/main/metrics.entropyhub.svg" /></a>
 <section id="latest-updates">
 <h1>Latest Updates<a class="headerlink" href="#latest-updates" title="Permalink to this heading"></a></h1>
 <div class="toctree-wrapper compound">

docs/_build/html/Home.html

@@ -164,7 +164,7 @@ <h2>An open-source toolkit for entropic data analysis<a class="headerlink" href=
 <a class="reference internal image-reference" href="_images/EntropyHub_Profiler.png"><img alt="_images/EntropyHub_Profiler.png" class="align-center" src="_images/EntropyHub_Profiler.png" style="width: 150px; height: 150px;" /></a>
 <p class="centered">
 <strong>Available in:</strong></p><p class="centered">
-<strong><a class="reference external" href="https://www.mathworks.com/matlabcentral/fileexchange/94185-entropyhub">Matlab</a> // <a class="reference external" href="https://pypi.org/project/EntropyHub/">Python</a>  // <a href="#id1"><span class="problematic" id="id2">`Julia &lt;https://mattwillflood.github.io/EntropyHub.jl/stable/`_</span></a></strong></p><div class="toctree-wrapper compound">
+<strong><a class="reference external" href="https://www.mathworks.com/matlabcentral/fileexchange/94185-entropyhub">Matlab</a> // <a class="reference external" href="https://pypi.org/project/EntropyHub/">Python</a>  // <a class="reference external" href="https://mattwillflood.github.io/EntropyHub.jl/stable/">Julia</a></strong></p><div class="toctree-wrapper compound">
 </div>
 <ul class="simple">
 <li><p><a class="reference external" href="./EHupdates.html">Latest Updates</a></p></li>

docs/_build/html/Publications.html

@@ -124,8 +124,8 @@
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="julia/EHjulia.html">EntropyHub - Julia</a><ul>
-<li class="toctree-l2"><a class="reference external" href="https://docs.juliahub.com/EntropyHub/npy5E/0.2.0/">EntropyHub.jl</a></li>
-<li class="toctree-l2"><a class="reference external" href="https://mattwillflood.github.io/EntropyHub.jl/Examples/Examples">Examples</a></li>
+<li class="toctree-l2"><a class="reference external" href="https://mattwillflood.github.io/EntropyHub.jl/stable/">EntropyHub.jl</a></li>
+<li class="toctree-l2"><a class="reference external" href="https://mattwillflood.github.io/EntropyHub.jl/stable/Examples/Examples">Examples</a></li>
 </ul>
 </li>
 </ul>
@@ -170,6 +170,14 @@ <h2>List of research articles citing EntropyHub<a class="headerlink" href="#list
 <h3>2024<a class="headerlink" href="#id1" title="Permalink to this heading"></a></h3>
 <ul>
 <li><dl>
+<dt><a class="reference external" href="https://pubs.aip.org/aip/cha/article/34/4/043136/3282829/From-physiological-complexity-to-data-interactions">From physiological complexity to data interactions—A case study of recordings from exercise monitoring</a></dt><dd><div class="line-block">
+<div class="line">Małgorzata Andrzejewska, Tomasz Wróblewski, Szymon Cygan, Mateusz Ozimek, Monika Petelczyc</div>
+<div class="line"><em>Chaos</em></div>
+</div>
+</dd>
+</dl>
+</li>
+<li><dl>
 <dt><a class="reference external" href="https://www.mdpi.com/2075-4663/12/4/90#">Predictability and Complexity of Fine and Gross Motor Skills in Fibromyalgia Patients: A Pilot Study</a></dt><dd><div class="line-block">
 <div class="line">Nancy Brígida, David Catela, Cristiana Mercê, Marco Branco</div>
 <div class="line"><em>Sports (MDPI)</em></div>

docs/_build/html/_sources/EHupdates.rst.txt

@@ -1,6 +1,6 @@
 .. image:: https://raw.githubusercontent.com/MattWillFlood/EntropyHub/main/metrics.entropyhub.svg
     :align: right
-    :height: 80px
+    :height: 50px
     :target: https://github.com/MattWillFlood/EntropyHub
 
 **************

docs/_build/html/_sources/Home.rst.txt

@@ -18,7 +18,7 @@ An open-source toolkit for entropic data analysis
     :height: 150px
 
 .. centered:: Available in: 
-.. centered:: `Matlab  <https://www.mathworks.com/matlabcentral/fileexchange/94185-entropyhub>`_ // `Python <https://pypi.org/project/EntropyHub/>`_  // `Julia <https://mattwillflood.github.io/EntropyHub.jl/stable/`_
+.. centered:: `Matlab  <https://www.mathworks.com/matlabcentral/fileexchange/94185-entropyhub>`_ // `Python <https://pypi.org/project/EntropyHub/>`_  // `Julia <https://mattwillflood.github.io/EntropyHub.jl/stable/>`_ 
 
 .. toctree::
    :maxdepth: 3

docs/_build/html/_sources/Publications.rst.txt

@@ -29,6 +29,10 @@ List of research articles citing EntropyHub
 2024
 ----
 
+* `From physiological complexity to data interactions—A case study of recordings from exercise monitoring <https://pubs.aip.org/aip/cha/article/34/4/043136/3282829/From-physiological-complexity-to-data-interactions>`_
+    | Małgorzata Andrzejewska, Tomasz Wróblewski, Szymon Cygan, Mateusz Ozimek, Monika Petelczyc
+    | *Chaos*
+
 * `Predictability and Complexity of Fine and Gross Motor Skills in Fibromyalgia Patients: A Pilot Study <https://www.mdpi.com/2075-4663/12/4/90#>`_
     | Nancy Brígida, David Catela, Cristiana Mercê, Marco Branco
     | *Sports (MDPI)*

docs/_build/html/matlab/Functions/matBase.html

@@ -418,21 +418,23 @@ <h2>Functions for estimating the entropy of a single univariate time series.<a c
 (<code class="docutils literal notranslate"><span class="pre">RDE</span></code>) estimated from the data sequence (<code class="docutils literal notranslate"><span class="pre">Sig</span></code>) using the specified
 name/value pair arguments:</p>
 <blockquote>
-<div><ul class="simple">
+<div><ul>
 <li><p><code class="docutils literal notranslate"><span class="pre">m</span></code>     - Embedding Dimension, a positive integer</p></li>
 <li><p><code class="docutils literal notranslate"><span class="pre">tau</span></code>   - Time Delay, a positive integer</p></li>
 <li><p><code class="docutils literal notranslate"><span class="pre">c</span></code>     - Number of symbols, an integer &gt; 1</p></li>
-<li><p><code class="docutils literal notranslate"><span class="pre">Typex</span></code> - Type of data-to-symbolic sequence transform, one of the following:
-{<code class="docutils literal notranslate"><span class="pre">linear</span></code>, <code class="docutils literal notranslate"><span class="pre">kmeans</span></code>, <code class="docutils literal notranslate"><span class="pre">ncdf</span></code>, <code class="docutils literal notranslate"><span class="pre">finesort</span></code>, <code class="docutils literal notranslate"><span class="pre">equal</span></code>}
-See the <cite>EntropyHub Guide</cite> for more info on these transforms.</p></li>
+<li><dl class="simple">
+<dt><code class="docutils literal notranslate"><span class="pre">Typex</span></code> - Type of data-to-symbolic sequence transform, one of the following:</dt><dd><p>{<code class="docutils literal notranslate"><span class="pre">linear</span></code>, <code class="docutils literal notranslate"><span class="pre">kmeans</span></code>, <code class="docutils literal notranslate"><span class="pre">ncdf</span></code>, <code class="docutils literal notranslate"><span class="pre">finesort</span></code>, <code class="docutils literal notranslate"><span class="pre">equal</span></code>}</p>
+</dd>
+</dl>
+<p>See the <cite>EntropyHub Guide</cite> for more info on these transforms.</p>
+</li>
 <li><p><code class="docutils literal notranslate"><span class="pre">Logx</span></code>  - Logarithm base, a positive scalar</p></li>
 <li><p><code class="docutils literal notranslate"><span class="pre">Fluct</span></code> - When <code class="docutils literal notranslate"><span class="pre">Fluct</span> <span class="pre">==</span> <span class="pre">true</span></code>, <code class="docutils literal notranslate"><span class="pre">DispEn</span></code> returns the fluctuation-based
 Dispersion entropy.   [default: false]</p></li>
 <li><dl class="simple">
-<dt><code class="docutils literal notranslate"><span class="pre">Norm</span></code>  - Normalisation of <code class="docutils literal notranslate"><span class="pre">Dispx</span></code> and <code class="docutils literal notranslate"><span class="pre">RDE</span></code> values, a boolean:</dt><dd><ul>
+<dt><code class="docutils literal notranslate"><span class="pre">Norm</span></code>  - Normalisation of <code class="docutils literal notranslate"><span class="pre">Dispx</span></code> and <code class="docutils literal notranslate"><span class="pre">RDE</span></code> values, a boolean:</dt><dd><ul class="simple">
 <li><p>[false]   no normalisation - default</p></li>
-<li><p>[true]    normalises w.r.t number of possible dispersion 
-patterns (<code class="docutils literal notranslate"><span class="pre">c^m</span></code>  or <code class="docutils literal notranslate"><span class="pre">(2c</span> <span class="pre">-1)^m-1</span></code> if <code class="docutils literal notranslate"><span class="pre">Fluct</span> <span class="pre">==</span> <span class="pre">true</span></code>).</p></li>
+<li><p>[true]    normalises w.r.t number of possible dispersion patterns (<code class="docutils literal notranslate"><span class="pre">c^m</span></code> or <code class="docutils literal notranslate"><span class="pre">(2c</span> <span class="pre">-1)^m-1</span></code> if <code class="docutils literal notranslate"><span class="pre">Fluct</span> <span class="pre">==</span> <span class="pre">true</span></code>).</p></li>
 </ul>
 </dd>
 </dl>
@@ -441,7 +443,7 @@ <h2>Functions for estimating the entropy of a single univariate time series.<a c
 </ul>
 </div></blockquote>
 <dl class="simple">
-<dt>See also:</dt><dd><p>PermEn, SyDyEn, MSEn.</p>
+<dt>See also:</dt><dd><p>DispEn2D, MvDispEn, PermEn, SyDyEn, MSEn.</p>
 </dd>
 <dt>References:</dt><dd><dl class="simple">
 <dt>[1] Mostafa Rostaghi and Hamed Azami,</dt><dd><p>“Dispersion entropy: A measure for time-series analysis.” 

docs/_build/html/matlab/Functions/matMultiscale.html

@@ -234,16 +234,15 @@ <h2>Functions for estimating the multiscale entropy of a univariate time series.
 </div></blockquote>
 <blockquote>
 <div><ul class="simple">
-<li><p><code class="docutils literal notranslate"><span class="pre">'SampEn2D'</span></code>   - Bidimensional Sample Entropy</p></li>
-<li><p><code class="docutils literal notranslate"><span class="pre">'FuzzEn2D'</span></code>   - Bidimensional Fuzzy Entropy</p></li>
-<li><p><code class="docutils literal notranslate"><span class="pre">'DispEn2D'</span></code>   - Bidimensional Dispersion Entropy</p></li>
-<li><p><code class="docutils literal notranslate"><span class="pre">'DistEn2D'</span></code>   - Bidimensional Distribution Entropy</p></li>
-<li><p><code class="docutils literal notranslate"><span class="pre">'EspEn2D'</span></code>    - Bidimensional Espinosa Entropy</p></li>
-<li><p><code class="docutils literal notranslate"><span class="pre">'PermEn2D'</span></code>   - Bidimensional Permutation Entropy</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">'MvSampEn2D'</span></code>   - Multivariate Sample Entropy</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">'MvFuzzEn2D'</span></code>   - Multivariate Fuzzy Entropy</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">'MvDispEn2D'</span></code>   - Multivariate Dispersion Entropy</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">'MvCoSiEn2D'</span></code>   - Multivariate Cosine Similarity Entropy</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">'MvPermEn2D'</span></code>   - Multivariate Permutation Entropy</p></li>
 </ul>
 </div></blockquote>
 <dl class="simple">
-<dt>See also:</dt><dd><p>MSEn, XMSEn, MSEn2D, cMSEn, rMSEn, hMSEn,rXMSEn, cXMSEn, hXMSEn</p>
+<dt>See also:</dt><dd><p>MSEn, XMSEn, MvMSEn, cMSEn, rMSEn, hMSEn,rXMSEn, cXMSEn, hXMSEn</p>
 </dd>
 </dl>
 </dd></dl>

docs/_build/html/matlab/Functions/matMultiscaleCross.html

@@ -234,16 +234,15 @@ <h2>Functions for estimating the multiscale cross-entropy between two univariate
 </div></blockquote>
 <blockquote>
 <div><ul class="simple">
-<li><p><code class="docutils literal notranslate"><span class="pre">'SampEn2D'</span></code>   - Bidimensional Sample Entropy</p></li>
-<li><p><code class="docutils literal notranslate"><span class="pre">'FuzzEn2D'</span></code>   - Bidimensional Fuzzy Entropy</p></li>
-<li><p><code class="docutils literal notranslate"><span class="pre">'DispEn2D'</span></code>   - Bidimensional Dispersion Entropy</p></li>
-<li><p><code class="docutils literal notranslate"><span class="pre">'DistEn2D'</span></code>   - Bidimensional Distribution Entropy</p></li>
-<li><p><code class="docutils literal notranslate"><span class="pre">'EspEn2D'</span></code>    - Bidimensional Espinosa Entropy</p></li>
-<li><p><code class="docutils literal notranslate"><span class="pre">'PermEn2D'</span></code>   - Bidimensional Permutation Entropy</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">'MvSampEn2D'</span></code>   - Multivariate Sample Entropy</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">'MvFuzzEn2D'</span></code>   - Multivariate Fuzzy Entropy</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">'MvDispEn2D'</span></code>   - Multivariate Dispersion Entropy</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">'MvCoSiEn2D'</span></code>   - Multivariate Cosine Similarity Entropy</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">'MvPermEn2D'</span></code>   - Multivariate Permutation Entropy</p></li>
 </ul>
 </div></blockquote>
 <dl class="simple">
-<dt>See also:</dt><dd><p>MSEn, XMSEn, MSEn2D, cMSEn, rMSEn, hMSEn,rXMSEn, cXMSEn, hXMSEn</p>
+<dt>See also:</dt><dd><p>MSEn, XMSEn, MvMSEn, cMSEn, rMSEn, hMSEn,rXMSEn, cXMSEn, hXMSEn</p>
 </dd>
 </dl>
 </dd></dl>