Fixing documentation and type hints

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Petrônio Cândido 2022-04-10 14:32:24 -03:00
parent 06d1bf6e6a
commit 6885f2df5b
156 changed files with 12401 additions and 5725 deletions

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@ -1,4 +1,4 @@
# Sphinx build info version 1
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@ -104,7 +92,6 @@
<li><a href="pyFTS/data/mackey_glass.html">pyFTS.data.mackey_glass</a></li>
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@ -171,7 +158,7 @@
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@ -190,13 +177,13 @@
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@ -43,7 +31,7 @@
<li class="right" >
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>modules</a> |</li>
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@ -61,15 +49,15 @@
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">scipy.stats</span> <span class="k">as</span> <span class="nn">st</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">SortedCollection</span><span class="p">,</span> <span class="n">fts</span>
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="kn">import</span> <span class="n">ProbabilityDistribution</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">SortedCollection</span><span class="p">,</span> <span class="n">fts</span>
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">ProbabilityDistribution</span>
<div class="viewcode-block" id="ARIMA"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.BSTS.ARIMA">[docs]</a><span class="k">class</span> <span class="nc">ARIMA</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Façade for statsmodels.tsa.arima_model</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">ARIMA</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;BSTS&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">&quot;Bayesian Structural Time Series&quot;</span>
@ -188,7 +176,7 @@
<h3 id="searchlabel">Quick search</h3>
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@ -207,14 +195,14 @@
<li class="right" >
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<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.benchmarks.BSTS</a></li>
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
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Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.benchmarks.Measures</a></li>
</ul>
@ -64,8 +52,8 @@
<span class="kn">import</span> <span class="nn">time</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">SortedCollection</span>
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="kn">import</span> <span class="n">ProbabilityDistribution</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">SortedCollection</span>
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">ProbabilityDistribution</span>
<div class="viewcode-block" id="acf"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.acf">[docs]</a><span class="k">def</span> <span class="nf">acf</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span>
@ -86,21 +74,33 @@
<span class="k">return</span> <span class="mi">1</span> <span class="o">/</span> <span class="p">((</span><span class="n">n</span> <span class="o">-</span> <span class="n">k</span><span class="p">)</span> <span class="o">*</span> <span class="n">sigma</span><span class="p">)</span> <span class="o">*</span> <span class="n">s</span></div>
<div class="viewcode-block" id="rmse"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.rmse">[docs]</a><span class="k">def</span> <span class="nf">rmse</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">):</span>
<div class="viewcode-block" id="rmse"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.rmse">[docs]</a><span class="k">def</span> <span class="nf">rmse</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">offset</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Root Mean Squared Error</span>
<span class="sd"> :param targets: </span>
<span class="sd"> :param forecasts: </span>
<span class="sd"> :param targets: array of targets</span>
<span class="sd"> :param forecasts: array of forecasts</span>
<span class="sd"> :param order: model order</span>
<span class="sd"> :param offset: forecast offset related to target. </span>
<span class="sd"> :return: </span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
<span class="n">targets</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">targets</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">forecasts</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
<span class="n">forecasts</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">nanmean</span><span class="p">((</span><span class="n">targets</span> <span class="o">-</span> <span class="n">forecasts</span><span class="p">)</span> <span class="o">**</span> <span class="mi">2</span><span class="p">))</span></div>
<span class="k">if</span> <span class="n">offset</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">nanmean</span><span class="p">((</span><span class="n">targets</span><span class="p">[</span><span class="n">order</span><span class="p">:]</span> <span class="o">-</span> <span class="n">forecasts</span><span class="p">[:])</span> <span class="o">**</span> <span class="mi">2</span><span class="p">))</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">nanmean</span><span class="p">((</span><span class="n">targets</span><span class="p">[</span><span class="n">order</span><span class="o">+</span><span class="n">offset</span><span class="p">:]</span> <span class="o">-</span> <span class="n">forecasts</span><span class="p">[:</span><span class="o">-</span><span class="n">offset</span><span class="p">])</span> <span class="o">**</span> <span class="mi">2</span><span class="p">))</span></div>
<div class="viewcode-block" id="nmrse"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.nmrse">[docs]</a><span class="k">def</span> <span class="nf">nmrse</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">offset</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot; Normalized Root Mean Squared Error &quot;&quot;&quot;</span>
<span class="k">return</span> <span class="n">rmse</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="n">offset</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">targets</span><span class="p">)</span> <span class="o">-</span> <span class="n">np</span><span class="o">.</span><span class="n">min</span><span class="p">(</span><span class="n">targets</span><span class="p">))</span> <span class="c1">## normalizing in targets because on forecasts might explode to inf (when model predict a line)</span></div>
<div class="viewcode-block" id="rmse_interval"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.rmse_interval">[docs]</a><span class="k">def</span> <span class="nf">rmse_interval</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Root Mean Squared Error</span>
@ -631,7 +631,7 @@
<h3 id="searchlabel">Quick search</h3>
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<form class="search" action="../../../search.html" method="get">
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@ -650,14 +650,14 @@
<li class="right" >
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<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.benchmarks.Measures</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

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@ -5,31 +5,19 @@
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<title>pyFTS.benchmarks.ResidualAnalysis &#8212; pyFTS 1.6 documentation</title>
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<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>pyFTS.benchmarks.ResidualAnalysis &#8212; pyFTS 1.7 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.benchmarks.ResidualAnalysis</a></li>
</ul>
@ -64,9 +52,9 @@
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">matplotlib</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">Transformations</span><span class="p">,</span><span class="n">Util</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="kn">import</span> <span class="n">Measures</span>
<span class="kn">from</span> <span class="nn">scipy</span> <span class="kn">import</span> <span class="n">stats</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Transformations</span><span class="p">,</span><span class="n">Util</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span>
<span class="kn">from</span> <span class="nn">scipy</span> <span class="k">import</span> <span class="n">stats</span>
<div class="viewcode-block" id="residuals"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.ResidualAnalysis.residuals">[docs]</a><span class="k">def</span> <span class="nf">residuals</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
@ -75,8 +63,8 @@
<div class="viewcode-block" id="ljung_box_test"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.ResidualAnalysis.ljung_box_test">[docs]</a><span class="k">def</span> <span class="nf">ljung_box_test</span><span class="p">(</span><span class="n">residuals</span><span class="p">,</span> <span class="n">lags</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">],</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">):</span>
<span class="kn">from</span> <span class="nn">statsmodels.stats.diagnostic</span> <span class="kn">import</span> <span class="n">acorr_ljungbox</span>
<span class="kn">from</span> <span class="nn">scipy.stats</span> <span class="kn">import</span> <span class="n">chi2</span>
<span class="kn">from</span> <span class="nn">statsmodels.stats.diagnostic</span> <span class="k">import</span> <span class="n">acorr_ljungbox</span>
<span class="kn">from</span> <span class="nn">scipy.stats</span> <span class="k">import</span> <span class="n">chi2</span>
<span class="n">stat</span><span class="p">,</span> <span class="n">pval</span> <span class="o">=</span> <span class="n">acorr_ljungbox</span><span class="p">(</span><span class="n">residuals</span><span class="p">,</span> <span class="n">lags</span><span class="o">=</span><span class="n">lags</span><span class="p">)</span>
@ -99,7 +87,7 @@
<span class="sd"> :param models: </span>
<span class="sd"> :return: a Pandas dataframe with the Box-Ljung statistic for each model</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">statsmodels.stats.diagnostic</span> <span class="kn">import</span> <span class="n">acorr_ljungbox</span>
<span class="kn">from</span> <span class="nn">statsmodels.stats.diagnostic</span> <span class="k">import</span> <span class="n">acorr_ljungbox</span>
<span class="n">rows</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">columns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">&quot;Model&quot;</span><span class="p">,</span><span class="s2">&quot;Order&quot;</span><span class="p">,</span><span class="s2">&quot;AVG&quot;</span><span class="p">,</span><span class="s2">&quot;STD&quot;</span><span class="p">,</span><span class="s2">&quot;Box-Ljung&quot;</span><span class="p">,</span><span class="s2">&quot;p-value&quot;</span><span class="p">,</span><span class="s2">&quot;Result&quot;</span><span class="p">]</span>
<span class="k">for</span> <span class="n">mfts</span> <span class="ow">in</span> <span class="n">models</span><span class="p">:</span>
@ -189,7 +177,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
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<input type="submit" value="Go" />
</form>
</div>
@ -208,14 +196,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.benchmarks.ResidualAnalysis</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
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<title>pyFTS.benchmarks.Tests &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.benchmarks.Tests</a></li>
</ul>
@ -59,7 +47,7 @@
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks.Measures</span> <span class="kn">import</span> <span class="n">acf</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks.Measures</span> <span class="k">import</span> <span class="n">acf</span>
<div class="viewcode-block" id="BoxPierceStatistic"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Tests.BoxPierceStatistic">[docs]</a><span class="k">def</span> <span class="nf">BoxPierceStatistic</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">h</span><span class="p">):</span>
@ -159,7 +147,7 @@
<span class="sd"> :param method:</span>
<span class="sd"> :return:</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">stac.stac</span> <span class="kn">import</span> <span class="n">nonparametric_tests</span> <span class="k">as</span> <span class="n">npt</span>
<span class="kn">from</span> <span class="nn">stac.stac</span> <span class="k">import</span> <span class="n">nonparametric_tests</span> <span class="k">as</span> <span class="n">npt</span>
<span class="n">methods</span> <span class="o">=</span> <span class="n">tests</span><span class="o">.</span><span class="n">columns</span><span class="p">[</span><span class="mi">1</span><span class="p">:]</span>
@ -204,7 +192,7 @@
<span class="sd"> :param method:</span>
<span class="sd"> :return:</span>
<span class="sd"> &#39;&#39;&#39;</span>
<span class="kn">from</span> <span class="nn">stac.stac</span> <span class="kn">import</span> <span class="n">nonparametric_tests</span> <span class="k">as</span> <span class="n">npt</span>
<span class="kn">from</span> <span class="nn">stac.stac</span> <span class="k">import</span> <span class="n">nonparametric_tests</span> <span class="k">as</span> <span class="n">npt</span>
<span class="k">if</span> <span class="n">method</span> <span class="o">==</span> <span class="s1">&#39;bonferroni_dunn&#39;</span><span class="p">:</span>
<span class="n">comparisons</span><span class="p">,</span> <span class="n">z_values</span><span class="p">,</span> <span class="n">p_values</span><span class="p">,</span> <span class="n">adj_p_values</span> <span class="o">=</span> <span class="n">npt</span><span class="o">.</span><span class="n">bonferroni_dunn_test</span><span class="p">(</span><span class="n">post_hoc</span><span class="p">,</span><span class="n">control_method</span><span class="p">)</span>
@ -234,7 +222,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
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<input type="submit" value="Go" />
</form>
</div>
@ -253,14 +241,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.benchmarks.Tests</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0"><script type="text/javascript">
var _gaq = _gaq || [];
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<title>pyFTS.benchmarks.Util &#8212; pyFTS 1.6 documentation</title>
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<title>pyFTS.benchmarks.Util &#8212; pyFTS 1.7 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.benchmarks.Util</a></li>
</ul>
@ -69,8 +57,8 @@
<span class="c1">#from mpl_toolkits.mplot3d import Axes3D</span>
<span class="kn">from</span> <span class="nn">copy</span> <span class="kn">import</span> <span class="n">deepcopy</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">Util</span>
<span class="kn">from</span> <span class="nn">copy</span> <span class="k">import</span> <span class="n">deepcopy</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Util</span>
<div class="viewcode-block" id="open_benchmark_db"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Util.open_benchmark_db">[docs]</a><span class="k">def</span> <span class="nf">open_benchmark_db</span><span class="p">(</span><span class="n">name</span><span class="p">):</span>
@ -1387,7 +1375,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
<input type="text" name="q" aria-labelledby="searchlabel" autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false"/>
<input type="submit" value="Go" />
</form>
</div>
@ -1406,14 +1394,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.benchmarks.Util</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0"><script type="text/javascript">
var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-55120145-3']);
_gaq.push(['_trackPageview']);
(function() {
var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
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<title>pyFTS.benchmarks.arima &#8212; pyFTS 1.6 documentation</title>
<link rel="stylesheet" href="../../../_static/bizstyle.css" type="text/css" />
<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>pyFTS.benchmarks.arima &#8212; pyFTS 1.7 documentation</title>
<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css" />
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.benchmarks.arima</a></li>
</ul>
@ -60,17 +48,17 @@
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">from</span> <span class="nn">statsmodels.tsa.arima_model</span> <span class="kn">import</span> <span class="n">ARIMA</span> <span class="k">as</span> <span class="n">stats_arima</span>
<span class="kn">from</span> <span class="nn">statsmodels.tsa.arima_model</span> <span class="k">import</span> <span class="n">ARIMA</span> <span class="k">as</span> <span class="n">stats_arima</span>
<span class="kn">import</span> <span class="nn">scipy.stats</span> <span class="k">as</span> <span class="nn">st</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">SortedCollection</span><span class="p">,</span> <span class="n">fts</span>
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="kn">import</span> <span class="n">ProbabilityDistribution</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">SortedCollection</span><span class="p">,</span> <span class="n">fts</span>
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">ProbabilityDistribution</span>
<div class="viewcode-block" id="ARIMA"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.arima.ARIMA">[docs]</a><span class="k">class</span> <span class="nc">ARIMA</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Façade for statsmodels.tsa.arima_model</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">ARIMA</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;ARIMA&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">&quot;Auto Regressive Integrated Moving Average&quot;</span>
@ -288,7 +276,7 @@
<h3 id="searchlabel">Quick search</h3>
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<input type="text" name="q" aria-labelledby="searchlabel" />
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<input type="submit" value="Go" />
</form>
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@ -307,14 +295,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.benchmarks.arima</a></li>
</ul>
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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@ -5,31 +5,19 @@
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<title>pyFTS.benchmarks.benchmarks &#8212; pyFTS 1.6 documentation</title>
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<title>pyFTS.benchmarks.benchmarks &#8212; pyFTS 1.7 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.benchmarks.benchmarks</a></li>
</ul>
@ -63,25 +51,25 @@
<span class="kn">import</span> <span class="nn">datetime</span>
<span class="kn">import</span> <span class="nn">time</span>
<span class="kn">from</span> <span class="nn">copy</span> <span class="kn">import</span> <span class="n">deepcopy</span>
<span class="kn">from</span> <span class="nn">copy</span> <span class="k">import</span> <span class="n">deepcopy</span>
<span class="kn">import</span> <span class="nn">traceback</span>
<span class="kn">import</span> <span class="nn">matplotlib</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">mpl_toolkits.mplot3d</span> <span class="kn">import</span> <span class="n">Axes3D</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="kn">import</span> <span class="n">product</span>
<span class="kn">from</span> <span class="nn">mpl_toolkits.mplot3d</span> <span class="k">import</span> <span class="n">Axes3D</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="k">import</span> <span class="n">product</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">Transformations</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">song</span><span class="p">,</span> <span class="n">chen</span><span class="p">,</span> <span class="n">yu</span><span class="p">,</span> <span class="n">ismailefendi</span><span class="p">,</span> <span class="n">sadaei</span><span class="p">,</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">pwfts</span><span class="p">,</span> <span class="n">ifts</span><span class="p">,</span> <span class="n">cheng</span><span class="p">,</span> <span class="n">hwang</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="kn">import</span> <span class="n">mvfts</span><span class="p">,</span> <span class="n">wmvfts</span><span class="p">,</span> <span class="n">cmvfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.ensemble</span> <span class="kn">import</span> <span class="n">ensemble</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="kn">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">naive</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">ResidualAnalysis</span><span class="p">,</span> <span class="n">quantreg</span><span class="p">,</span> <span class="n">knn</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="kn">import</span> <span class="n">Util</span> <span class="k">as</span> <span class="n">bUtil</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">Util</span> <span class="k">as</span> <span class="n">cUtil</span>
<span class="kn">from</span> <span class="nn">pyFTS.common.transformations.differential</span> <span class="k">import</span> <span class="n">Differential</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">song</span><span class="p">,</span> <span class="n">chen</span><span class="p">,</span> <span class="n">yu</span><span class="p">,</span> <span class="n">ismailefendi</span><span class="p">,</span> <span class="n">sadaei</span><span class="p">,</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">pwfts</span><span class="p">,</span> <span class="n">ifts</span><span class="p">,</span> <span class="n">cheng</span><span class="p">,</span> <span class="n">hwang</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="k">import</span> <span class="n">mvfts</span><span class="p">,</span> <span class="n">wmvfts</span><span class="p">,</span> <span class="n">cmvfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.ensemble</span> <span class="k">import</span> <span class="n">ensemble</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">naive</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">ResidualAnalysis</span><span class="p">,</span> <span class="n">quantreg</span><span class="p">,</span> <span class="n">knn</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Util</span> <span class="k">as</span> <span class="n">bUtil</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Util</span> <span class="k">as</span> <span class="n">cUtil</span>
<span class="c1"># from sklearn.cross_validation import KFold</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span>
<span class="n">colors</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;grey&#39;</span><span class="p">,</span> <span class="s1">&#39;darkgrey&#39;</span><span class="p">,</span> <span class="s1">&#39;rosybrown&#39;</span><span class="p">,</span> <span class="s1">&#39;maroon&#39;</span><span class="p">,</span> <span class="s1">&#39;red&#39;</span><span class="p">,</span><span class="s1">&#39;orange&#39;</span><span class="p">,</span> <span class="s1">&#39;gold&#39;</span><span class="p">,</span> <span class="s1">&#39;yellow&#39;</span><span class="p">,</span> <span class="s1">&#39;olive&#39;</span><span class="p">,</span> <span class="s1">&#39;green&#39;</span><span class="p">,</span>
<span class="s1">&#39;darkgreen&#39;</span><span class="p">,</span> <span class="s1">&#39;cyan&#39;</span><span class="p">,</span> <span class="s1">&#39;lightblue&#39;</span><span class="p">,</span><span class="s1">&#39;blue&#39;</span><span class="p">,</span> <span class="s1">&#39;darkblue&#39;</span><span class="p">,</span> <span class="s1">&#39;purple&#39;</span><span class="p">,</span> <span class="s1">&#39;darkviolet&#39;</span> <span class="p">]</span>
@ -139,7 +127,7 @@
<div class="viewcode-block" id="multivariate_sliding_window_benchmarks2"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.multivariate_sliding_window_benchmarks2">[docs]</a><span class="k">def</span> <span class="nf">multivariate_sliding_window_benchmarks2</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">windowsize</span><span class="p">,</span> <span class="n">train</span><span class="o">=</span><span class="mf">0.8</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="kn">import</span> <span class="n">common</span><span class="p">,</span> <span class="n">variable</span><span class="p">,</span> <span class="n">mvfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="k">import</span> <span class="n">common</span><span class="p">,</span> <span class="n">variable</span><span class="p">,</span> <span class="n">mvfts</span>
<span class="n">tag</span> <span class="o">=</span> <span class="n">__pop</span><span class="p">(</span><span class="s1">&#39;tag&#39;</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="n">kwargs</span><span class="p">)</span>
<span class="n">dataset</span> <span class="o">=</span> <span class="n">__pop</span><span class="p">(</span><span class="s1">&#39;dataset&#39;</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="n">kwargs</span><span class="p">)</span>
@ -489,7 +477,7 @@
<span class="n">inc</span> <span class="o">=</span> <span class="n">__pop</span><span class="p">(</span><span class="s2">&quot;inc&quot;</span><span class="p">,</span> <span class="mf">0.1</span><span class="p">,</span> <span class="n">kwargs</span><span class="p">)</span>
<span class="k">if</span> <span class="n">progress</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">tqdm</span> <span class="kn">import</span> <span class="n">tqdm</span>
<span class="kn">from</span> <span class="nn">tqdm</span> <span class="k">import</span> <span class="n">tqdm</span>
<span class="n">_tdata</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="n">windowsize</span> <span class="o">*</span> <span class="n">inc</span><span class="p">)</span>
<span class="n">_tasks</span> <span class="o">=</span> <span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">partitioners_models</span><span class="p">)</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">orders</span><span class="p">)</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">partitions</span><span class="p">)</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">transformations</span><span class="p">)</span> <span class="o">*</span> <span class="nb">len</span><span class="p">(</span><span class="n">steps_ahead</span><span class="p">))</span>
<span class="n">_tbcmk</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">benchmark_pool</span><span class="p">)</span><span class="o">*</span><span class="nb">len</span><span class="p">(</span><span class="n">steps_ahead</span><span class="p">)</span>
@ -597,10 +585,10 @@
<span class="sd"> :return: a dictionary with the benchmark results</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">time</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">yu</span><span class="p">,</span> <span class="n">chen</span><span class="p">,</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">pwfts</span><span class="p">,</span><span class="n">ismailefendi</span><span class="p">,</span><span class="n">sadaei</span><span class="p">,</span> <span class="n">song</span><span class="p">,</span> <span class="n">cheng</span><span class="p">,</span> <span class="n">hwang</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span><span class="p">,</span> <span class="n">FCM</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="kn">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">naive</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">quantreg</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">Transformations</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">yu</span><span class="p">,</span> <span class="n">chen</span><span class="p">,</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">pwfts</span><span class="p">,</span><span class="n">ismailefendi</span><span class="p">,</span><span class="n">sadaei</span><span class="p">,</span> <span class="n">song</span><span class="p">,</span> <span class="n">cheng</span><span class="p">,</span> <span class="n">hwang</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span><span class="p">,</span> <span class="n">FCM</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">naive</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">quantreg</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Transformations</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[</span><span class="n">song</span><span class="o">.</span><span class="n">ConventionalFTS</span><span class="p">,</span> <span class="n">chen</span><span class="o">.</span><span class="n">ConventionalFTS</span><span class="p">,</span> <span class="n">yu</span><span class="o">.</span><span class="n">WeightedFTS</span><span class="p">,</span> <span class="n">ismailefendi</span><span class="o">.</span><span class="n">ImprovedWeightedFTS</span><span class="p">,</span>
<span class="n">cheng</span><span class="o">.</span><span class="n">TrendWeightedFTS</span><span class="p">,</span> <span class="n">sadaei</span><span class="o">.</span><span class="n">ExponentialyWeightedFTS</span><span class="p">,</span> <span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">,</span> <span class="n">hwang</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">,</span>
@ -612,7 +600,7 @@
<span class="n">tmp3</span> <span class="o">=</span> <span class="p">[</span><span class="n">Measures</span><span class="o">.</span><span class="n">get_point_statistics</span><span class="p">]</span>
<span class="n">tmp5</span> <span class="o">=</span> <span class="p">[</span><span class="n">Transformations</span><span class="o">.</span><span class="n">Differential</span><span class="p">]</span>
<span class="n">tmp5</span> <span class="o">=</span> <span class="p">[</span><span class="n">Differential</span><span class="p">]</span>
<span class="n">indexer</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;indexer&#39;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
@ -661,9 +649,9 @@
<span class="sd"> :return: a dictionary with the benchmark results</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">time</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">hofts</span><span class="p">,</span><span class="n">ifts</span><span class="p">,</span><span class="n">pwfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span><span class="p">,</span> <span class="n">FCM</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="kn">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">quantreg</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span><span class="p">,</span><span class="n">ifts</span><span class="p">,</span><span class="n">pwfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span><span class="p">,</span> <span class="n">FCM</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">quantreg</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[</span><span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">,</span> <span class="n">ifts</span><span class="o">.</span><span class="n">IntervalFTS</span><span class="p">,</span> <span class="n">pwfts</span><span class="o">.</span><span class="n">ProbabilisticWeightedFTS</span><span class="p">]</span>
@ -723,11 +711,11 @@
<span class="sd"> &quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">time</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">ifts</span><span class="p">,</span> <span class="n">pwfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.ensemble</span> <span class="kn">import</span> <span class="n">ensemble</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span><span class="p">,</span> <span class="n">FCM</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="kn">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">quantreg</span><span class="p">,</span> <span class="n">knn</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.seasonal</span> <span class="kn">import</span> <span class="n">SeasonalIndexer</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">ifts</span><span class="p">,</span> <span class="n">pwfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.ensemble</span> <span class="k">import</span> <span class="n">ensemble</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span><span class="p">,</span> <span class="n">FCM</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">quantreg</span><span class="p">,</span> <span class="n">knn</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.seasonal</span> <span class="k">import</span> <span class="n">SeasonalIndexer</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[</span><span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">,</span> <span class="n">ifts</span><span class="o">.</span><span class="n">IntervalFTS</span><span class="p">,</span> <span class="n">pwfts</span><span class="o">.</span><span class="n">ProbabilisticWeightedFTS</span><span class="p">,</span> <span class="n">arima</span><span class="o">.</span><span class="n">ARIMA</span><span class="p">,</span>
<span class="n">ensemble</span><span class="o">.</span><span class="n">AllMethodEnsembleFTS</span><span class="p">,</span> <span class="n">knn</span><span class="o">.</span><span class="n">KNearestNeighbors</span><span class="p">]</span>
@ -788,10 +776,10 @@
<div class="viewcode-block" id="mv_run_point2"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.mv_run_point2">[docs]</a><span class="k">def</span> <span class="nf">mv_run_point2</span><span class="p">(</span><span class="n">mfts</span><span class="p">,</span> <span class="n">train_data</span><span class="p">,</span> <span class="n">test_data</span><span class="p">,</span> <span class="n">window_key</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="kn">import</span> <span class="nn">time</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">ifts</span><span class="p">,</span> <span class="n">pwfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="kn">import</span> <span class="n">mvfts</span><span class="p">,</span> <span class="n">wmvfts</span><span class="p">,</span> <span class="n">granular</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span><span class="p">,</span> <span class="n">FCM</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="kn">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">quantreg</span><span class="p">,</span> <span class="n">BSTS</span><span class="p">,</span> <span class="n">benchmarks</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">ifts</span><span class="p">,</span> <span class="n">pwfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="k">import</span> <span class="n">mvfts</span><span class="p">,</span> <span class="n">wmvfts</span><span class="p">,</span> <span class="n">granular</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span><span class="p">,</span> <span class="n">FCM</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">quantreg</span><span class="p">,</span> <span class="n">BSTS</span><span class="p">,</span> <span class="n">benchmarks</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[</span><span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">,</span> <span class="n">ifts</span><span class="o">.</span><span class="n">IntervalFTS</span><span class="p">,</span> <span class="n">ifts</span><span class="o">.</span><span class="n">WeightedIntervalFTS</span><span class="p">,</span> <span class="n">pwfts</span><span class="o">.</span><span class="n">ProbabilisticWeightedFTS</span><span class="p">]</span>
@ -848,10 +836,10 @@
<div class="viewcode-block" id="run_point2"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.run_point2">[docs]</a><span class="k">def</span> <span class="nf">run_point2</span><span class="p">(</span><span class="n">fts_method</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="n">partitioner_method</span><span class="p">,</span> <span class="n">partitions</span><span class="p">,</span> <span class="n">transformation</span><span class="p">,</span> <span class="n">train_data</span><span class="p">,</span> <span class="n">test_data</span><span class="p">,</span> <span class="n">window_key</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="kn">import</span> <span class="nn">time</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">yu</span><span class="p">,</span> <span class="n">chen</span><span class="p">,</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">pwfts</span><span class="p">,</span><span class="n">ismailefendi</span><span class="p">,</span><span class="n">sadaei</span><span class="p">,</span> <span class="n">song</span><span class="p">,</span> <span class="n">cheng</span><span class="p">,</span> <span class="n">hwang</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span><span class="p">,</span> <span class="n">FCM</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="kn">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">naive</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">quantreg</span><span class="p">,</span> <span class="n">benchmarks</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">Transformations</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">yu</span><span class="p">,</span> <span class="n">chen</span><span class="p">,</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">pwfts</span><span class="p">,</span><span class="n">ismailefendi</span><span class="p">,</span><span class="n">sadaei</span><span class="p">,</span> <span class="n">song</span><span class="p">,</span> <span class="n">cheng</span><span class="p">,</span> <span class="n">hwang</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span><span class="p">,</span> <span class="n">FCM</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">naive</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">quantreg</span><span class="p">,</span> <span class="n">benchmarks</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Transformations</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[</span><span class="n">song</span><span class="o">.</span><span class="n">ConventionalFTS</span><span class="p">,</span> <span class="n">chen</span><span class="o">.</span><span class="n">ConventionalFTS</span><span class="p">,</span> <span class="n">yu</span><span class="o">.</span><span class="n">WeightedFTS</span><span class="p">,</span> <span class="n">ismailefendi</span><span class="o">.</span><span class="n">ImprovedWeightedFTS</span><span class="p">,</span>
<span class="n">cheng</span><span class="o">.</span><span class="n">TrendWeightedFTS</span><span class="p">,</span> <span class="n">sadaei</span><span class="o">.</span><span class="n">ExponentialyWeightedFTS</span><span class="p">,</span> <span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">,</span> <span class="n">hwang</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">,</span>
@ -863,7 +851,7 @@
<span class="n">tmp3</span> <span class="o">=</span> <span class="p">[</span><span class="n">Measures</span><span class="o">.</span><span class="n">get_point_statistics</span><span class="p">]</span>
<span class="n">tmp5</span> <span class="o">=</span> <span class="p">[</span><span class="n">Transformations</span><span class="o">.</span><span class="n">Differential</span><span class="p">]</span>
<span class="n">tmp5</span> <span class="o">=</span> <span class="p">[</span><span class="n">Differential</span><span class="p">]</span>
<span class="n">indexer</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;indexer&#39;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
@ -915,10 +903,10 @@
<div class="viewcode-block" id="mv_run_interval2"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.mv_run_interval2">[docs]</a><span class="k">def</span> <span class="nf">mv_run_interval2</span><span class="p">(</span><span class="n">mfts</span><span class="p">,</span><span class="n">train_data</span><span class="p">,</span> <span class="n">test_data</span><span class="p">,</span> <span class="n">window_key</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="kn">import</span> <span class="nn">time</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">hofts</span><span class="p">,</span><span class="n">ifts</span><span class="p">,</span><span class="n">pwfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="kn">import</span> <span class="n">mvfts</span><span class="p">,</span> <span class="n">wmvfts</span><span class="p">,</span> <span class="n">granular</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span><span class="p">,</span> <span class="n">FCM</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="kn">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">quantreg</span><span class="p">,</span> <span class="n">BSTS</span><span class="p">,</span> <span class="n">benchmarks</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span><span class="p">,</span><span class="n">ifts</span><span class="p">,</span><span class="n">pwfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="k">import</span> <span class="n">mvfts</span><span class="p">,</span> <span class="n">wmvfts</span><span class="p">,</span> <span class="n">granular</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span><span class="p">,</span> <span class="n">FCM</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">quantreg</span><span class="p">,</span> <span class="n">BSTS</span><span class="p">,</span> <span class="n">benchmarks</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[</span><span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">,</span> <span class="n">ifts</span><span class="o">.</span><span class="n">IntervalFTS</span><span class="p">,</span> <span class="n">ifts</span><span class="o">.</span><span class="n">WeightedIntervalFTS</span><span class="p">,</span> <span class="n">pwfts</span><span class="o">.</span><span class="n">ProbabilisticWeightedFTS</span><span class="p">]</span>
@ -978,9 +966,9 @@
<div class="viewcode-block" id="run_interval2"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.run_interval2">[docs]</a><span class="k">def</span> <span class="nf">run_interval2</span><span class="p">(</span><span class="n">fts_method</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="n">partitioner_method</span><span class="p">,</span> <span class="n">partitions</span><span class="p">,</span> <span class="n">transformation</span><span class="p">,</span> <span class="n">train_data</span><span class="p">,</span> <span class="n">test_data</span><span class="p">,</span> <span class="n">window_key</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="kn">import</span> <span class="nn">time</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">hofts</span><span class="p">,</span><span class="n">ifts</span><span class="p">,</span><span class="n">pwfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span><span class="p">,</span> <span class="n">FCM</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="kn">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">quantreg</span><span class="p">,</span> <span class="n">BSTS</span><span class="p">,</span> <span class="n">benchmarks</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span><span class="p">,</span><span class="n">ifts</span><span class="p">,</span><span class="n">pwfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span><span class="p">,</span> <span class="n">FCM</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">quantreg</span><span class="p">,</span> <span class="n">BSTS</span><span class="p">,</span> <span class="n">benchmarks</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[</span><span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">,</span> <span class="n">ifts</span><span class="o">.</span><span class="n">IntervalFTS</span><span class="p">,</span> <span class="n">ifts</span><span class="o">.</span><span class="n">WeightedIntervalFTS</span><span class="p">,</span> <span class="n">pwfts</span><span class="o">.</span><span class="n">ProbabilisticWeightedFTS</span><span class="p">]</span>
@ -1040,10 +1028,10 @@
<div class="viewcode-block" id="mv_run_probabilistic2"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.mv_run_probabilistic2">[docs]</a><span class="k">def</span> <span class="nf">mv_run_probabilistic2</span><span class="p">(</span><span class="n">mfts</span><span class="p">,</span> <span class="n">train_data</span><span class="p">,</span> <span class="n">test_data</span><span class="p">,</span> <span class="n">window_key</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="kn">import</span> <span class="nn">time</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">ifts</span><span class="p">,</span> <span class="n">pwfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="kn">import</span> <span class="n">mvfts</span><span class="p">,</span> <span class="n">wmvfts</span><span class="p">,</span> <span class="n">granular</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span><span class="p">,</span> <span class="n">FCM</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="kn">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">quantreg</span><span class="p">,</span> <span class="n">BSTS</span><span class="p">,</span> <span class="n">benchmarks</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">ifts</span><span class="p">,</span> <span class="n">pwfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="k">import</span> <span class="n">mvfts</span><span class="p">,</span> <span class="n">wmvfts</span><span class="p">,</span> <span class="n">granular</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span><span class="p">,</span> <span class="n">FCM</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">quantreg</span><span class="p">,</span> <span class="n">BSTS</span><span class="p">,</span> <span class="n">benchmarks</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[</span><span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">,</span> <span class="n">ifts</span><span class="o">.</span><span class="n">IntervalFTS</span><span class="p">,</span> <span class="n">ifts</span><span class="o">.</span><span class="n">WeightedIntervalFTS</span><span class="p">,</span> <span class="n">pwfts</span><span class="o">.</span><span class="n">ProbabilisticWeightedFTS</span><span class="p">]</span>
@ -1100,11 +1088,11 @@
<div class="viewcode-block" id="run_probabilistic2"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.run_probabilistic2">[docs]</a><span class="k">def</span> <span class="nf">run_probabilistic2</span><span class="p">(</span><span class="n">fts_method</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="n">partitioner_method</span><span class="p">,</span> <span class="n">partitions</span><span class="p">,</span> <span class="n">transformation</span><span class="p">,</span> <span class="n">train_data</span><span class="p">,</span> <span class="n">test_data</span><span class="p">,</span> <span class="n">window_key</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="kn">import</span> <span class="nn">time</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">ifts</span><span class="p">,</span> <span class="n">pwfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.ensemble</span> <span class="kn">import</span> <span class="n">ensemble</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span><span class="p">,</span> <span class="n">FCM</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="kn">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">quantreg</span><span class="p">,</span> <span class="n">knn</span><span class="p">,</span> <span class="n">benchmarks</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.seasonal</span> <span class="kn">import</span> <span class="n">SeasonalIndexer</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">ifts</span><span class="p">,</span> <span class="n">pwfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.ensemble</span> <span class="k">import</span> <span class="n">ensemble</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span><span class="p">,</span> <span class="n">FCM</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">quantreg</span><span class="p">,</span> <span class="n">knn</span><span class="p">,</span> <span class="n">benchmarks</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.seasonal</span> <span class="k">import</span> <span class="n">SeasonalIndexer</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[</span><span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">,</span> <span class="n">ifts</span><span class="o">.</span><span class="n">IntervalFTS</span><span class="p">,</span> <span class="n">pwfts</span><span class="o">.</span><span class="n">ProbabilisticWeightedFTS</span><span class="p">,</span> <span class="n">arima</span><span class="o">.</span><span class="n">ARIMA</span><span class="p">,</span>
<span class="n">ensemble</span><span class="o">.</span><span class="n">AllMethodEnsembleFTS</span><span class="p">,</span> <span class="n">knn</span><span class="o">.</span><span class="n">KNearestNeighbors</span><span class="p">]</span>
@ -1441,7 +1429,7 @@
<span class="n">ls</span> <span class="o">=</span> <span class="s2">&quot;-&quot;</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">ls</span> <span class="o">=</span> <span class="s2">&quot;--&quot;</span>
<span class="n">tmpmi</span><span class="p">,</span> <span class="n">tmpma</span> <span class="o">=</span> <span class="n">Util</span><span class="o">.</span><span class="n">plot_interval</span><span class="p">(</span><span class="n">ax</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">,</span> <span class="n">fts</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">lbl</span><span class="p">,</span> <span class="n">typeonlegend</span><span class="o">=</span><span class="n">typeonlegend</span><span class="p">,</span>
<span class="n">tmpmi</span><span class="p">,</span> <span class="n">tmpma</span> <span class="o">=</span> <span class="n">cUtil</span><span class="o">.</span><span class="n">plot_interval</span><span class="p">(</span><span class="n">ax</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">,</span> <span class="n">fts</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">lbl</span><span class="p">,</span> <span class="n">typeonlegend</span><span class="o">=</span><span class="n">typeonlegend</span><span class="p">,</span>
<span class="n">color</span><span class="o">=</span><span class="n">colors</span><span class="p">[</span><span class="n">count</span><span class="p">],</span> <span class="n">ls</span><span class="o">=</span><span class="n">ls</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="n">linewidth</span><span class="p">)</span>
<span class="n">mi</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmpmi</span><span class="p">)</span>
<span class="n">ma</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmpma</span><span class="p">)</span>
@ -1476,89 +1464,6 @@
<span class="n">ax</span><span class="o">.</span><span class="n">set_ylim</span><span class="p">([</span><span class="nb">min</span><span class="p">(</span><span class="n">original</span><span class="p">),</span> <span class="nb">max</span><span class="p">(</span><span class="n">original</span><span class="p">)])</span></div>
<div class="viewcode-block" id="SelecaoSimples_MenorRMSE"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.SelecaoSimples_MenorRMSE">[docs]</a><span class="k">def</span> <span class="nf">SelecaoSimples_MenorRMSE</span><span class="p">(</span><span class="n">original</span><span class="p">,</span> <span class="n">parameters</span><span class="p">,</span> <span class="n">modelo</span><span class="p">):</span>
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">errors</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">forecasted_best</span> <span class="o">=</span> <span class="p">[]</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Série Original&quot;</span><span class="p">)</span>
<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">[</span><span class="mi">20</span><span class="p">,</span> <span class="mi">12</span><span class="p">])</span>
<span class="n">fig</span><span class="o">.</span><span class="n">suptitle</span><span class="p">(</span><span class="s2">&quot;Comparação de modelos &quot;</span><span class="p">)</span>
<span class="n">ax0</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.65</span><span class="p">,</span> <span class="mf">0.45</span><span class="p">])</span> <span class="c1"># left, bottom, width, height</span>
<span class="n">ax0</span><span class="o">.</span><span class="n">set_xlim</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">original</span><span class="p">)])</span>
<span class="n">ax0</span><span class="o">.</span><span class="n">set_ylim</span><span class="p">([</span><span class="nb">min</span><span class="p">(</span><span class="n">original</span><span class="p">),</span> <span class="nb">max</span><span class="p">(</span><span class="n">original</span><span class="p">)])</span>
<span class="n">ax0</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;Série Temporal&#39;</span><span class="p">)</span>
<span class="n">ax0</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;F(T)&#39;</span><span class="p">)</span>
<span class="n">ax0</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">&#39;T&#39;</span><span class="p">)</span>
<span class="n">ax0</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">original</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;Original&quot;</span><span class="p">)</span>
<span class="n">min_rmse</span> <span class="o">=</span> <span class="mf">100000.0</span>
<span class="n">best</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">parameters</span><span class="p">:</span>
<span class="n">sets</span> <span class="o">=</span> <span class="n">Grid</span><span class="o">.</span><span class="n">GridPartitioner</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">original</span><span class="p">,</span> <span class="n">npart</span><span class="o">=</span><span class="n">p</span><span class="p">)</span><span class="o">.</span><span class="n">sets</span>
<span class="n">fts</span> <span class="o">=</span> <span class="n">modelo</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">p</span><span class="p">)</span> <span class="o">+</span> <span class="s2">&quot; particoes&quot;</span><span class="p">)</span>
<span class="n">fts</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="n">original</span><span class="p">,</span> <span class="n">sets</span><span class="o">=</span><span class="n">sets</span><span class="p">)</span>
<span class="c1"># print(original)</span>
<span class="n">forecasted</span> <span class="o">=</span> <span class="n">fts</span><span class="o">.</span><span class="n">forecast</span><span class="p">(</span><span class="n">original</span><span class="p">)</span>
<span class="n">forecasted</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">original</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
<span class="c1"># print(forecasted)</span>
<span class="n">ax0</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">forecasted</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">fts</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
<span class="n">error</span> <span class="o">=</span> <span class="n">Measures</span><span class="o">.</span><span class="n">rmse</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">forecasted</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">original</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="n">p</span><span class="p">,</span> <span class="n">error</span><span class="p">)</span>
<span class="n">errors</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">error</span><span class="p">)</span>
<span class="k">if</span> <span class="n">error</span> <span class="o">&lt;</span> <span class="n">min_rmse</span><span class="p">:</span>
<span class="n">min_rmse</span> <span class="o">=</span> <span class="n">error</span>
<span class="n">best</span> <span class="o">=</span> <span class="n">fts</span>
<span class="n">forecasted_best</span> <span class="o">=</span> <span class="n">forecasted</span>
<span class="n">handles0</span><span class="p">,</span> <span class="n">labels0</span> <span class="o">=</span> <span class="n">ax0</span><span class="o">.</span><span class="n">get_legend_handles_labels</span><span class="p">()</span>
<span class="n">ax0</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">handles0</span><span class="p">,</span> <span class="n">labels0</span><span class="p">)</span>
<span class="n">ax1</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.7</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.3</span><span class="p">,</span> <span class="mf">0.45</span><span class="p">])</span> <span class="c1"># left, bottom, width, height</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;Comparação dos Erros Quadráticos Médios&#39;</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;RMSE&#39;</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">&#39;Quantidade de Partições&#39;</span><span class="p">)</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">set_xlim</span><span class="p">([</span><span class="nb">min</span><span class="p">(</span><span class="n">parameters</span><span class="p">),</span> <span class="nb">max</span><span class="p">(</span><span class="n">parameters</span><span class="p">)])</span>
<span class="n">ax1</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">parameters</span><span class="p">,</span> <span class="n">errors</span><span class="p">)</span>
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">best</span><span class="p">)</span>
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">forecasted_best</span><span class="p">)</span>
<span class="c1"># Modelo diferencial</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\n</span><span class="s2">Série Diferencial&quot;</span><span class="p">)</span>
<span class="n">difffts</span> <span class="o">=</span> <span class="n">Transformations</span><span class="o">.</span><span class="n">differential</span><span class="p">(</span><span class="n">original</span><span class="p">)</span>
<span class="n">errors</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">forecastedd_best</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">ax2</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mf">0.65</span><span class="p">,</span> <span class="mf">0.45</span><span class="p">])</span> <span class="c1"># left, bottom, width, height</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">set_xlim</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">difffts</span><span class="p">)])</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">set_ylim</span><span class="p">([</span><span class="nb">min</span><span class="p">(</span><span class="n">difffts</span><span class="p">),</span> <span class="nb">max</span><span class="p">(</span><span class="n">difffts</span><span class="p">)])</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;Série Temporal&#39;</span><span class="p">)</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;F(T)&#39;</span><span class="p">)</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">&#39;T&#39;</span><span class="p">)</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">difffts</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;Original&quot;</span><span class="p">)</span>
<span class="n">min_rmse</span> <span class="o">=</span> <span class="mf">100000.0</span>
<span class="n">bestd</span> <span class="o">=</span> <span class="kc">None</span>
<span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">parameters</span><span class="p">:</span>
<span class="n">sets</span> <span class="o">=</span> <span class="n">Grid</span><span class="o">.</span><span class="n">GridPartitioner</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">difffts</span><span class="p">,</span> <span class="n">npart</span><span class="o">=</span><span class="n">p</span><span class="p">)</span>
<span class="n">fts</span> <span class="o">=</span> <span class="n">modelo</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">p</span><span class="p">)</span> <span class="o">+</span> <span class="s2">&quot; particoes&quot;</span><span class="p">)</span>
<span class="n">fts</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="n">difffts</span><span class="p">,</span> <span class="n">sets</span><span class="o">=</span><span class="n">sets</span><span class="p">)</span>
<span class="n">forecasted</span> <span class="o">=</span> <span class="n">fts</span><span class="o">.</span><span class="n">forecast</span><span class="p">(</span><span class="n">difffts</span><span class="p">)</span>
<span class="n">forecasted</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">difffts</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">forecasted</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">fts</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
<span class="n">error</span> <span class="o">=</span> <span class="n">Measures</span><span class="o">.</span><span class="n">rmse</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">forecasted</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">difffts</span><span class="p">))</span>
<span class="nb">print</span><span class="p">(</span><span class="n">p</span><span class="p">,</span> <span class="n">error</span><span class="p">)</span>
<span class="n">errors</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">error</span><span class="p">)</span>
<span class="k">if</span> <span class="n">error</span> <span class="o">&lt;</span> <span class="n">min_rmse</span><span class="p">:</span>
<span class="n">min_rmse</span> <span class="o">=</span> <span class="n">error</span>
<span class="n">bestd</span> <span class="o">=</span> <span class="n">fts</span>
<span class="n">forecastedd_best</span> <span class="o">=</span> <span class="n">forecasted</span>
<span class="n">handles0</span><span class="p">,</span> <span class="n">labels0</span> <span class="o">=</span> <span class="n">ax2</span><span class="o">.</span><span class="n">get_legend_handles_labels</span><span class="p">()</span>
<span class="n">ax2</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">handles0</span><span class="p">,</span> <span class="n">labels0</span><span class="p">)</span>
<span class="n">ax3</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_axes</span><span class="p">([</span><span class="mf">0.7</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mf">0.3</span><span class="p">,</span> <span class="mf">0.45</span><span class="p">])</span> <span class="c1"># left, bottom, width, height</span>
<span class="n">ax3</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s1">&#39;Comparação dos Erros Quadráticos Médios&#39;</span><span class="p">)</span>
<span class="n">ax3</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;RMSE&#39;</span><span class="p">)</span>
<span class="n">ax3</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">&#39;Quantidade de Partições&#39;</span><span class="p">)</span>
<span class="n">ax3</span><span class="o">.</span><span class="n">set_xlim</span><span class="p">([</span><span class="nb">min</span><span class="p">(</span><span class="n">parameters</span><span class="p">),</span> <span class="nb">max</span><span class="p">(</span><span class="n">parameters</span><span class="p">)])</span>
<span class="n">ax3</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">parameters</span><span class="p">,</span> <span class="n">errors</span><span class="p">)</span>
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">bestd</span><span class="p">)</span>
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">forecastedd_best</span><span class="p">)</span>
<span class="k">return</span> <span class="n">ret</span></div>
<div class="viewcode-block" id="compareModelsPlot"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.compareModelsPlot">[docs]</a><span class="k">def</span> <span class="nf">compareModelsPlot</span><span class="p">(</span><span class="n">original</span><span class="p">,</span> <span class="n">models_fo</span><span class="p">,</span> <span class="n">models_ho</span><span class="p">):</span>
<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="p">[</span><span class="mi">13</span><span class="p">,</span> <span class="mi">6</span><span class="p">])</span>
<span class="n">fig</span><span class="o">.</span><span class="n">suptitle</span><span class="p">(</span><span class="s2">&quot;Comparação de modelos &quot;</span><span class="p">)</span>
@ -1878,7 +1783,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
<input type="text" name="q" aria-labelledby="searchlabel" autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false"/>
<input type="submit" value="Go" />
</form>
</div>
@ -1897,14 +1802,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.benchmarks.benchmarks</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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@ -5,31 +5,19 @@
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<title>pyFTS.benchmarks.knn &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.benchmarks.knn</a></li>
</ul>
@ -59,18 +47,18 @@
<span class="c1"># -*- coding: utf8 -*-</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">statsmodels.tsa.tsatools</span> <span class="kn">import</span> <span class="n">lagmat</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">fts</span>
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="kn">import</span> <span class="n">ProbabilityDistribution</span>
<span class="kn">from</span> <span class="nn">sklearn.neighbors</span> <span class="kn">import</span> <span class="n">KDTree</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="kn">import</span> <span class="n">product</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.ensemble.ensemble</span> <span class="kn">import</span> <span class="n">sampler</span>
<span class="kn">from</span> <span class="nn">statsmodels.tsa.tsatools</span> <span class="k">import</span> <span class="n">lagmat</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">fts</span>
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">ProbabilityDistribution</span>
<span class="kn">from</span> <span class="nn">sklearn.neighbors</span> <span class="k">import</span> <span class="n">KDTree</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="k">import</span> <span class="n">product</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.ensemble.ensemble</span> <span class="k">import</span> <span class="n">sampler</span>
<div class="viewcode-block" id="KNearestNeighbors"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.knn.KNearestNeighbors">[docs]</a><span class="k">class</span> <span class="nc">KNearestNeighbors</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> A façade for sklearn.neighbors</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">KNearestNeighbors</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;kNN&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">&quot;kNN&quot;</span>
@ -242,7 +230,7 @@
<h3 id="searchlabel">Quick search</h3>
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@ -261,14 +249,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.benchmarks.knn</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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</body>
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@ -5,31 +5,19 @@
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@ -43,7 +31,7 @@
<li class="right" >
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>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-this"><a href="">pyFTS.benchmarks.naive</a></li>
</ul>
@ -58,12 +46,12 @@
<span></span><span class="ch">#!/usr/bin/python</span>
<span class="c1"># -*- coding: utf8 -*-</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">fts</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">fts</span>
<div class="viewcode-block" id="Naive"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.naive.Naive">[docs]</a><span class="k">class</span> <span class="nc">Naive</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Naïve Forecasting method&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">Naive</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;Naive&quot;</span><span class="p">,</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Naïve Model&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">&quot;Naïve Model&quot;</span>
@ -86,7 +74,7 @@
<h3 id="searchlabel">Quick search</h3>
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@ -105,14 +93,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
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<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.benchmarks.naive</a></li>
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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@ -5,31 +5,19 @@
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<title>pyFTS.benchmarks.quantreg &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.benchmarks.quantreg</a></li>
</ul>
@ -60,15 +48,15 @@
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">from</span> <span class="nn">statsmodels.regression.quantile_regression</span> <span class="kn">import</span> <span class="n">QuantReg</span>
<span class="kn">from</span> <span class="nn">statsmodels.tsa.tsatools</span> <span class="kn">import</span> <span class="n">lagmat</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">SortedCollection</span><span class="p">,</span> <span class="n">fts</span>
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="kn">import</span> <span class="n">ProbabilityDistribution</span>
<span class="kn">from</span> <span class="nn">statsmodels.regression.quantile_regression</span> <span class="k">import</span> <span class="n">QuantReg</span>
<span class="kn">from</span> <span class="nn">statsmodels.tsa.tsatools</span> <span class="k">import</span> <span class="n">lagmat</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">SortedCollection</span><span class="p">,</span> <span class="n">fts</span>
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">ProbabilityDistribution</span>
<div class="viewcode-block" id="QuantileRegression"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.quantreg.QuantileRegression">[docs]</a><span class="k">class</span> <span class="nc">QuantileRegression</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Façade for statsmodels.regression.quantile_regression&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">QuantileRegression</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;QAR&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">&quot;Quantile Regression&quot;</span>
@ -235,7 +223,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
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<input type="submit" value="Go" />
</form>
</div>
@ -254,14 +242,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.benchmarks.quantreg</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
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<title>pyFTS.common.Composite &#8212; pyFTS 1.6 documentation</title>
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<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>pyFTS.common.Composite &#8212; pyFTS 1.7 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.common.Composite</a></li>
</ul>
@ -60,15 +48,15 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="kn">import</span> <span class="o">*</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">FuzzySet</span>
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="k">import</span> <span class="o">*</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">FuzzySet</span>
<div class="viewcode-block" id="FuzzySet"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Composite.FuzzySet">[docs]</a><span class="k">class</span> <span class="nc">FuzzySet</span><span class="p">(</span><span class="n">FuzzySet</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Composite Fuzzy Set</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">superset</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">superset</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Create an empty composite fuzzy set</span>
<span class="sd"> :param name: fuzzy set name</span>
@ -134,7 +122,7 @@
<span class="bp">self</span><span class="o">.</span><span class="n">centroid</span> <span class="o">=</span> <span class="nb">set</span><span class="o">.</span><span class="n">centroid</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="nb">str</span><span class="p">([</span><span class="nb">str</span><span class="p">(</span><span class="n">k</span><span class="p">)</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">])</span>
<span class="k">return</span> <span class="s2">&quot;</span><span class="si">{}</span><span class="s2">: </span><span class="si">{}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="n">tmp</span><span class="p">)</span></div>
@ -151,7 +139,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
<input type="text" name="q" aria-labelledby="searchlabel" autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false"/>
<input type="submit" value="Go" />
</form>
</div>
@ -170,14 +158,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.common.Composite</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0"><script type="text/javascript">
var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-55120145-3']);
_gaq.push(['_trackPageview']);
(function() {
var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
})();
</script>
<title>pyFTS.common.FLR &#8212; pyFTS 1.6 documentation</title>
<link rel="stylesheet" href="../../../_static/bizstyle.css" type="text/css" />
<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>pyFTS.common.FLR &#8212; pyFTS 1.7 documentation</title>
<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css" />
<link rel="stylesheet" type="text/css" href="../../../_static/bizstyle.css" />
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<script src="../../../_static/jquery.js"></script>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.common.FLR</a></li>
</ul>
@ -60,7 +48,7 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span>
<div class="viewcode-block" id="FLR"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FLR.FLR">[docs]</a><span class="k">class</span> <span class="nc">FLR</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
@ -69,7 +57,7 @@
<span class="sd"> Represents a temporal transition of the fuzzy set LHS on time t for the fuzzy set RHS on time t+1.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="n">RHS</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="n">RHS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Creates a Fuzzy Logical Relationship</span>
<span class="sd"> &quot;&quot;&quot;</span>
@ -78,13 +66,13 @@
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="n">RHS</span>
<span class="sd">&quot;&quot;&quot;Right Hand Side fuzzy set&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">+</span> <span class="s2">&quot; -&gt; &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
<div class="viewcode-block" id="IndexedFLR"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FLR.IndexedFLR">[docs]</a><span class="k">class</span> <span class="nc">IndexedFLR</span><span class="p">(</span><span class="n">FLR</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Season Indexed Fuzzy Logical Relationship&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">index</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="n">RHS</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">index</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="n">RHS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Create a Season Indexed Fuzzy Logical Relationship</span>
<span class="sd"> &quot;&quot;&quot;</span>
@ -92,7 +80,7 @@
<span class="bp">self</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="n">index</span>
<span class="sd">&quot;&quot;&quot;seasonal index&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">index</span><span class="p">)</span> <span class="o">+</span> <span class="s2">&quot;: &quot;</span><span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">+</span> <span class="s2">&quot; -&gt; &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
@ -187,7 +175,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
<input type="text" name="q" aria-labelledby="searchlabel" autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false"/>
<input type="submit" value="Go" />
</form>
</div>
@ -206,14 +194,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.common.FLR</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0"><script type="text/javascript">
var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-55120145-3']);
_gaq.push(['_trackPageview']);
(function() {
var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
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</script>
<title>pyFTS.common.FuzzySet &#8212; pyFTS 1.6 documentation</title>
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<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
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<title>pyFTS.common.FuzzySet &#8212; pyFTS 1.7 documentation</title>
<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css" />
<link rel="stylesheet" type="text/css" href="../../../_static/bizstyle.css" />
<script id="documentation_options" data-url_root="../../../" src="../../../_static/documentation_options.js"></script>
<script data-url_root="../../../" id="documentation_options" src="../../../_static/documentation_options.js"></script>
<script src="../../../_static/jquery.js"></script>
<script src="../../../_static/underscore.js"></script>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.common.FuzzySet</a></li>
</ul>
@ -56,8 +44,8 @@
<h1>Source code for pyFTS.common.FuzzySet</h1><div class="highlight"><pre>
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="kn">import</span> <span class="o">*</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">Membership</span>
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="k">import</span> <span class="o">*</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Membership</span>
<div class="viewcode-block" id="FuzzySet"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.FuzzySet">[docs]</a><span class="k">class</span> <span class="nc">FuzzySet</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
@ -65,21 +53,21 @@
<span class="sd"> Fuzzy Set</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">mf</span><span class="p">,</span> <span class="n">parameters</span><span class="p">,</span> <span class="n">centroid</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span> <span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">mf</span><span class="p">,</span> <span class="n">parameters</span> <span class="p">:</span> <span class="nb">list</span><span class="p">,</span> <span class="n">centroid</span> <span class="p">:</span> <span class="nb">float</span><span class="p">,</span> <span class="n">alpha</span> <span class="p">:</span> <span class="nb">float</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Create a Fuzzy Set</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">name</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="n">name</span>
<span class="sd">&quot;&quot;&quot;The fuzzy set name&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">=</span> <span class="n">mf</span>
<span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">=</span> <span class="n">mf</span>
<span class="sd">&quot;&quot;&quot;The membership function&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">parameters</span> <span class="o">=</span> <span class="n">parameters</span>
<span class="bp">self</span><span class="o">.</span><span class="n">parameters</span> <span class="p">:</span> <span class="nb">list</span> <span class="o">=</span> <span class="n">parameters</span>
<span class="sd">&quot;&quot;&quot;The parameters of the membership function&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">centroid</span> <span class="o">=</span> <span class="n">centroid</span>
<span class="bp">self</span><span class="o">.</span><span class="n">centroid</span> <span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">centroid</span>
<span class="sd">&quot;&quot;&quot;The fuzzy set center of mass (or midpoint)&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">alpha</span> <span class="o">=</span> <span class="n">alpha</span>
<span class="bp">self</span><span class="o">.</span><span class="n">alpha</span> <span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">alpha</span>
<span class="sd">&quot;&quot;&quot;The alpha cut value&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;type&#39;</span><span class="p">,</span> <span class="s1">&#39;common&#39;</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;type&#39;</span><span class="p">,</span> <span class="s1">&#39;common&#39;</span><span class="p">)</span>
<span class="sd">&quot;&quot;&quot;The fuzzy set type (common, composite, nonstationary, etc)&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">variable</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;variable&#39;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="sd">&quot;&quot;&quot;In multivariate time series, indicate for which variable this fuzzy set belogs&quot;&quot;&quot;</span>
@ -134,7 +122,7 @@
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">Z</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">+</span> <span class="s2">&quot;: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">mf</span><span class="o">.</span><span class="vm">__name__</span><span class="p">)</span> <span class="o">+</span> <span class="s2">&quot;(&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">parameters</span><span class="p">)</span> <span class="o">+</span> <span class="s2">&quot;)&quot;</span></div>
@ -227,7 +215,7 @@
<span class="k">return</span> <span class="p">[</span><span class="n">k</span><span class="o">.</span><span class="n">name</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">tmp1</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="o">.</span><span class="n">centroid</span><span class="p">)]</span></div>
<div class="viewcode-block" id="fuzzyfy_instance"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.fuzzyfy_instance">[docs]</a><span class="k">def</span> <span class="nf">fuzzyfy_instance</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="n">fuzzy_sets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<div class="viewcode-block" id="fuzzyfy_instance"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.fuzzyfy_instance">[docs]</a><span class="k">def</span> <span class="nf">fuzzyfy_instance</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="n">fuzzy_sets</span> <span class="p">:</span> <span class="nb">dict</span> <span class="p">,</span> <span class="n">ordered_sets</span> <span class="p">:</span> <span class="nb">list</span> <span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Calculate the membership values for a data point given fuzzy sets</span>
@ -248,7 +236,7 @@
<span class="k">return</span> <span class="n">mv</span></div>
<div class="viewcode-block" id="fuzzyfy_instances"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.fuzzyfy_instances">[docs]</a><span class="k">def</span> <span class="nf">fuzzyfy_instances</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">fuzzy_sets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<div class="viewcode-block" id="fuzzyfy_instances"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.fuzzyfy_instances">[docs]</a><span class="k">def</span> <span class="nf">fuzzyfy_instances</span><span class="p">(</span><span class="n">data</span> <span class="p">:</span> <span class="nb">list</span><span class="p">,</span> <span class="n">fuzzy_sets</span> <span class="p">:</span> <span class="nb">dict</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Calculate the membership values for a data point given fuzzy sets</span>
@ -266,7 +254,7 @@
<span class="k">return</span> <span class="n">ret</span></div>
<div class="viewcode-block" id="get_fuzzysets"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.get_fuzzysets">[docs]</a><span class="k">def</span> <span class="nf">get_fuzzysets</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="n">fuzzy_sets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">alpha_cut</span><span class="o">=</span><span class="mf">0.0</span><span class="p">):</span>
<div class="viewcode-block" id="get_fuzzysets"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.get_fuzzysets">[docs]</a><span class="k">def</span> <span class="nf">get_fuzzysets</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="n">fuzzy_sets</span> <span class="p">:</span> <span class="nb">dict</span><span class="p">,</span> <span class="n">ordered_sets</span> <span class="p">:</span> <span class="nb">list</span> <span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">alpha_cut</span> <span class="p">:</span> <span class="nb">float</span> <span class="o">=</span><span class="mf">0.0</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Return the fuzzy sets which membership value for a inst is greater than the alpha_cut</span>
@ -289,7 +277,7 @@
<span class="k">raise</span> <span class="n">ex</span></div>
<div class="viewcode-block" id="get_maximum_membership_fuzzyset"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.get_maximum_membership_fuzzyset">[docs]</a><span class="k">def</span> <span class="nf">get_maximum_membership_fuzzyset</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="n">fuzzy_sets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<div class="viewcode-block" id="get_maximum_membership_fuzzyset"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.get_maximum_membership_fuzzyset">[docs]</a><span class="k">def</span> <span class="nf">get_maximum_membership_fuzzyset</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="n">fuzzy_sets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="o">=</span><span class="kc">None</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">FuzzySet</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Fuzzify a data point, returning the fuzzy set with maximum membership value</span>
@ -305,7 +293,7 @@
<span class="k">return</span> <span class="n">fuzzy_sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span></div>
<div class="viewcode-block" id="get_maximum_membership_fuzzyset_index"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.get_maximum_membership_fuzzyset_index">[docs]</a><span class="k">def</span> <span class="nf">get_maximum_membership_fuzzyset_index</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="n">fuzzy_sets</span><span class="p">):</span>
<div class="viewcode-block" id="get_maximum_membership_fuzzyset_index"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.get_maximum_membership_fuzzyset_index">[docs]</a><span class="k">def</span> <span class="nf">get_maximum_membership_fuzzyset_index</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="n">fuzzy_sets</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">int</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Fuzzify a data point, returning the fuzzy set with maximum membership value</span>
@ -377,7 +365,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
<input type="text" name="q" aria-labelledby="searchlabel" autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false"/>
<input type="submit" value="Go" />
</form>
</div>
@ -396,14 +384,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.common.FuzzySet</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0"><script type="text/javascript">
var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-55120145-3']);
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<title>pyFTS.common.Membership &#8212; pyFTS 1.6 documentation</title>
<link rel="stylesheet" href="../../../_static/bizstyle.css" type="text/css" />
<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>pyFTS.common.Membership &#8212; pyFTS 1.7 documentation</title>
<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css" />
<link rel="stylesheet" type="text/css" href="../../../_static/bizstyle.css" />
<script id="documentation_options" data-url_root="../../../" src="../../../_static/documentation_options.js"></script>
<script data-url_root="../../../" id="documentation_options" src="../../../_static/documentation_options.js"></script>
<script src="../../../_static/jquery.js"></script>
<script src="../../../_static/underscore.js"></script>
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<link rel="index" title="Index" href="../../../genindex.html" />
<link rel="search" title="Search" href="../../../search.html" />
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.common.Membership</a></li>
</ul>
@ -61,7 +49,7 @@
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">math</span>
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="kn">import</span> <span class="o">*</span>
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="k">import</span> <span class="o">*</span>
<div class="viewcode-block" id="trimf"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Membership.trimf">[docs]</a><span class="k">def</span> <span class="nf">trimf</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">parameters</span><span class="p">):</span>
@ -161,7 +149,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
<input type="text" name="q" aria-labelledby="searchlabel" autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false"/>
<input type="submit" value="Go" />
</form>
</div>
@ -180,14 +168,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.common.Membership</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0"><script type="text/javascript">
var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-55120145-3']);
_gaq.push(['_trackPageview']);
(function() {
var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
})();
</script>
<title>pyFTS.common.SortedCollection &#8212; pyFTS 1.6 documentation</title>
<link rel="stylesheet" href="../../../_static/bizstyle.css" type="text/css" />
<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>pyFTS.common.SortedCollection &#8212; pyFTS 1.7 documentation</title>
<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css" />
<link rel="stylesheet" type="text/css" href="../../../_static/bizstyle.css" />
<script id="documentation_options" data-url_root="../../../" src="../../../_static/documentation_options.js"></script>
<script data-url_root="../../../" id="documentation_options" src="../../../_static/documentation_options.js"></script>
<script src="../../../_static/jquery.js"></script>
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<link rel="index" title="Index" href="../../../genindex.html" />
<link rel="search" title="Search" href="../../../search.html" />
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<meta name="viewport" content="width=device-width,initial-scale=1.0" />
<!--[if lt IE 9]>
<script src="_static/css3-mediaqueries.js"></script>
<![endif]-->
@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.common.SortedCollection</a></li>
</ul>
@ -55,7 +43,7 @@
<div class="body" role="main">
<h1>Source code for pyFTS.common.SortedCollection</h1><div class="highlight"><pre>
<span></span><span class="kn">from</span> <span class="nn">bisect</span> <span class="kn">import</span> <span class="n">bisect_left</span><span class="p">,</span> <span class="n">bisect_right</span>
<span></span><span class="kn">from</span> <span class="nn">bisect</span> <span class="k">import</span> <span class="n">bisect_left</span><span class="p">,</span> <span class="n">bisect_right</span>
<span class="c1">#</span>
<span class="c1"># Original Source Code: https://code.activestate.com/recipes/577197-sortedcollection/</span>
@ -131,7 +119,7 @@
<span class="sd"> &#39;&#39;&#39;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">iterable</span><span class="o">=</span><span class="p">(),</span> <span class="n">key</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">iterable</span><span class="o">=</span><span class="p">(),</span> <span class="n">key</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_given_key</span> <span class="o">=</span> <span class="n">key</span>
<span class="n">key</span> <span class="o">=</span> <span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">)</span> <span class="k">if</span> <span class="n">key</span> <span class="ow">is</span> <span class="kc">None</span> <span class="k">else</span> <span class="n">key</span>
<span class="n">decorated</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">((</span><span class="n">key</span><span class="p">(</span><span class="n">item</span><span class="p">),</span> <span class="n">item</span><span class="p">)</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">iterable</span><span class="p">)</span>
@ -157,19 +145,19 @@
<div class="viewcode-block" id="SortedCollection.copy"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.SortedCollection.SortedCollection.copy">[docs]</a> <span class="k">def</span> <span class="nf">copy</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_key</span><span class="p">)</span></div>
<span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__getitem__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">i</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__getitem__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">i</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
<span class="k">def</span> <span class="fm">__iter__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__iter__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">iter</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__reversed__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__reversed__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">reversed</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__repr__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__repr__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="s1">&#39;</span><span class="si">%s</span><span class="s1">(</span><span class="si">%r</span><span class="s1">, key=</span><span class="si">%s</span><span class="s1">)&#39;</span> <span class="o">%</span> <span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">,</span>
@ -179,7 +167,7 @@
<span class="k">def</span> <span class="nf">__reduce__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="p">,</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_given_key</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__contains__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">item</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__contains__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">item</span><span class="p">):</span>
<span class="n">k</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_key</span><span class="p">(</span><span class="n">item</span><span class="p">)</span>
<span class="n">i</span> <span class="o">=</span> <span class="n">bisect_left</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
<span class="n">j</span> <span class="o">=</span> <span class="n">bisect_right</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
@ -294,7 +282,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
<input type="text" name="q" aria-labelledby="searchlabel" autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false"/>
<input type="submit" value="Go" />
</form>
</div>
@ -313,14 +301,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.common.SortedCollection</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0"><script type="text/javascript">
var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-55120145-3']);
_gaq.push(['_trackPageview']);
(function() {
var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
})();
</script>
<title>pyFTS.common.Util &#8212; pyFTS 1.6 documentation</title>
<link rel="stylesheet" href="../../../_static/bizstyle.css" type="text/css" />
<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>pyFTS.common.Util &#8212; pyFTS 1.7 documentation</title>
<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css" />
<link rel="stylesheet" type="text/css" href="../../../_static/bizstyle.css" />
<script id="documentation_options" data-url_root="../../../" src="../../../_static/documentation_options.js"></script>
<script data-url_root="../../../" id="documentation_options" src="../../../_static/documentation_options.js"></script>
<script src="../../../_static/jquery.js"></script>
<script src="../../../_static/underscore.js"></script>
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<link rel="index" title="Index" href="../../../genindex.html" />
<link rel="search" title="Search" href="../../../search.html" />
<meta name="viewport" content="width=device-width,initial-scale=1.0">
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<!--[if lt IE 9]>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.common.Util</a></li>
</ul>
@ -65,8 +53,8 @@
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">matplotlib.cm</span> <span class="k">as</span> <span class="nn">cmx</span>
<span class="kn">import</span> <span class="nn">matplotlib.colors</span> <span class="k">as</span> <span class="nn">pltcolors</span>
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="kn">import</span> <span class="n">ProbabilityDistribution</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">Transformations</span>
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">ProbabilityDistribution</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Transformations</span>
<div class="viewcode-block" id="plot_compared_intervals_ahead"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.plot_compared_intervals_ahead">[docs]</a><span class="k">def</span> <span class="nf">plot_compared_intervals_ahead</span><span class="p">(</span><span class="n">original</span><span class="p">,</span> <span class="n">models</span><span class="p">,</span> <span class="n">colors</span><span class="p">,</span> <span class="n">distributions</span><span class="p">,</span> <span class="n">time_from</span><span class="p">,</span> <span class="n">time_to</span><span class="p">,</span> <span class="n">intervals</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
@ -152,8 +140,8 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Auxiliar function to plot_compared_intervals_ahead</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">matplotlib.patches</span> <span class="kn">import</span> <span class="n">Rectangle</span>
<span class="kn">from</span> <span class="nn">matplotlib.collections</span> <span class="kn">import</span> <span class="n">PatchCollection</span>
<span class="kn">from</span> <span class="nn">matplotlib.patches</span> <span class="k">import</span> <span class="n">Rectangle</span>
<span class="kn">from</span> <span class="nn">matplotlib.collections</span> <span class="k">import</span> <span class="n">PatchCollection</span>
<span class="n">patches</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">colors</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">density</span><span class="o">.</span><span class="n">index</span><span class="p">:</span>
@ -193,8 +181,8 @@
<span class="sd"> :param reference_data:</span>
<span class="sd"> :return:</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">matplotlib.patches</span> <span class="kn">import</span> <span class="n">Rectangle</span>
<span class="kn">from</span> <span class="nn">matplotlib.collections</span> <span class="kn">import</span> <span class="n">PatchCollection</span>
<span class="kn">from</span> <span class="nn">matplotlib.patches</span> <span class="k">import</span> <span class="n">Rectangle</span>
<span class="kn">from</span> <span class="nn">matplotlib.collections</span> <span class="k">import</span> <span class="n">PatchCollection</span>
<span class="n">patches</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">colors</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">dt</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">probabilitydist</span><span class="p">):</span>
@ -550,7 +538,7 @@
<span class="n">rng</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="n">l</span><span class="o">-</span><span class="n">windowsize</span><span class="o">+</span><span class="n">ic</span><span class="p">,</span><span class="n">ic</span><span class="p">)</span>
<span class="k">if</span> <span class="n">progressbar</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">tqdm</span> <span class="kn">import</span> <span class="n">tqdm</span>
<span class="kn">from</span> <span class="nn">tqdm</span> <span class="k">import</span> <span class="n">tqdm</span>
<span class="n">rng</span> <span class="o">=</span> <span class="n">tqdm</span><span class="p">(</span><span class="n">rng</span><span class="p">)</span>
<span class="k">for</span> <span class="n">count</span> <span class="ow">in</span> <span class="n">rng</span><span class="p">:</span>
@ -620,7 +608,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
<input type="text" name="q" aria-labelledby="searchlabel" autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false"/>
<input type="submit" value="Go" />
</form>
</div>
@ -639,14 +627,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.common.Util</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0"><script type="text/javascript">
var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-55120145-3']);
_gaq.push(['_trackPageview']);
(function() {
var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
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</script>
<title>pyFTS.common.flrg &#8212; pyFTS 1.6 documentation</title>
<link rel="stylesheet" href="../../../_static/bizstyle.css" type="text/css" />
<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>pyFTS.common.flrg &#8212; pyFTS 1.7 documentation</title>
<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css" />
<link rel="stylesheet" type="text/css" href="../../../_static/bizstyle.css" />
<script id="documentation_options" data-url_root="../../../" src="../../../_static/documentation_options.js"></script>
<script data-url_root="../../../" id="documentation_options" src="../../../_static/documentation_options.js"></script>
<script src="../../../_static/jquery.js"></script>
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<link rel="index" title="Index" href="../../../genindex.html" />
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<meta name="viewport" content="width=device-width,initial-scale=1.0">
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<!--[if lt IE 9]>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.common.flrg</a></li>
</ul>
@ -66,7 +54,7 @@
<span class="sd"> when the LHS pattern is identified on time t.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="kc">None</span>
<span class="sd">&quot;&quot;&quot;Left Hand Side of the rule&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="kc">None</span>
@ -160,7 +148,7 @@
<span class="bp">self</span><span class="o">.</span><span class="n">upper</span> <span class="o">=</span> <span class="nb">max</span><span class="p">([</span><span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">s</span><span class="p">]]</span><span class="o">.</span><span class="n">upper</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()])</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">upper</span></div>
<span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span>
<div class="viewcode-block" id="FLRG.reset_calculated_values"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.flrg.FLRG.reset_calculated_values">[docs]</a> <span class="k">def</span> <span class="nf">reset_calculated_values</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
@ -181,7 +169,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
<input type="text" name="q" aria-labelledby="searchlabel" autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false"/>
<input type="submit" value="Go" />
</form>
</div>
@ -200,14 +188,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<h1>Source code for pyFTS.common.fts</h1><div class="highlight"><pre>
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">SortedCollection</span><span class="p">,</span> <span class="n">tree</span><span class="p">,</span> <span class="n">Util</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">Util</span>
<span class="kn">from</span> <span class="nn">pyFTS.common.transformations</span> <span class="k">import</span> <span class="n">transformation</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">partitioner</span>
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">ProbabilityDistribution</span>
<div class="viewcode-block" id="FTS"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS">[docs]</a><span class="k">class</span> <span class="nc">FTS</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Fuzzy Time Series object model</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Create a Fuzzy Time Series model</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span> <span class="nb">dict</span> <span class="o">=</span> <span class="p">{}</span>
<span class="sd">&quot;&quot;&quot;The list of Fuzzy Logical Relationship Groups - FLRG&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;order&#39;</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;order&#39;</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>
<span class="sd">&quot;&quot;&quot;A integer with the model order (number of past lags are used on forecasting)&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;name&#39;</span><span class="p">,</span><span class="s2">&quot;&quot;</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;name&#39;</span><span class="p">,</span><span class="s2">&quot;&quot;</span><span class="p">)</span>
<span class="sd">&quot;&quot;&quot;A string with a short name or alias for the model&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;name&#39;</span><span class="p">,</span><span class="s2">&quot;&quot;</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;name&#39;</span><span class="p">,</span><span class="s2">&quot;&quot;</span><span class="p">)</span>
<span class="sd">&quot;&quot;&quot;A string with the model name&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;name&#39;</span><span class="p">,</span><span class="s2">&quot;&quot;</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="p">:</span> <span class="nb">str</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;name&#39;</span><span class="p">,</span><span class="s2">&quot;&quot;</span><span class="p">)</span>
<span class="sd">&quot;&quot;&quot;A string with the model detailed information&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">is_wrapper</span> <span class="o">=</span> <span class="kc">False</span>
<span class="bp">self</span><span class="o">.</span><span class="n">is_wrapper</span> <span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="sd">&quot;&quot;&quot;Indicates that this model is a wrapper for other(s) method(s)&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="kc">False</span>
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="sd">&quot;&quot;&quot;A boolean value indicating if the model support orders greater than 1, default: False&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">min_order</span> <span class="o">=</span> <span class="mi">1</span>
<span class="bp">self</span><span class="o">.</span><span class="n">min_order</span> <span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="mi">1</span>
<span class="sd">&quot;&quot;&quot;In high order models, this integer value indicates the minimal order supported for the model, default: 1&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">has_seasonality</span> <span class="o">=</span> <span class="kc">False</span>
<span class="bp">self</span><span class="o">.</span><span class="n">has_seasonality</span> <span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="sd">&quot;&quot;&quot;A boolean value indicating if the model supports seasonal indexers, default: False&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">has_point_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
<span class="bp">self</span><span class="o">.</span><span class="n">has_point_forecasting</span> <span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">True</span>
<span class="sd">&quot;&quot;&quot;A boolean value indicating if the model supports point forecasting, default: True&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">has_interval_forecasting</span> <span class="o">=</span> <span class="kc">False</span>
<span class="bp">self</span><span class="o">.</span><span class="n">has_interval_forecasting</span> <span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="sd">&quot;&quot;&quot;A boolean value indicating if the model supports interval forecasting, default: False&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">has_probability_forecasting</span> <span class="o">=</span> <span class="kc">False</span>
<span class="bp">self</span><span class="o">.</span><span class="n">has_probability_forecasting</span> <span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="sd">&quot;&quot;&quot;A boolean value indicating if the model support probabilistic forecasting, default: False&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">is_multivariate</span> <span class="o">=</span> <span class="kc">False</span>
<span class="bp">self</span><span class="o">.</span><span class="n">is_multivariate</span> <span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="sd">&quot;&quot;&quot;A boolean value indicating if the model support multivariate time series (Pandas DataFrame), default: False&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">is_clustered</span> <span class="o">=</span> <span class="kc">False</span>
<span class="bp">self</span><span class="o">.</span><span class="n">is_clustered</span> <span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="sd">&quot;&quot;&quot;A boolean value indicating if the model support multivariate time series (Pandas DataFrame), but works like </span>
<span class="sd"> a monovariate method, default: False&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">dump</span> <span class="o">=</span> <span class="kc">False</span>
<span class="bp">self</span><span class="o">.</span><span class="n">transformations</span> <span class="o">=</span> <span class="p">[]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">dump</span> <span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="bp">self</span><span class="o">.</span><span class="n">transformations</span> <span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="n">transformation</span><span class="o">.</span><span class="n">Transformation</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
<span class="sd">&quot;&quot;&quot;A list with the data transformations (common.Transformations) applied on model pre and post processing, default: []&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">transformations_param</span> <span class="o">=</span> <span class="p">[]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">transformations_param</span> <span class="p">:</span> <span class="nb">list</span> <span class="o">=</span> <span class="p">[]</span>
<span class="sd">&quot;&quot;&quot;A list with the specific parameters for each data transformation&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">original_max</span> <span class="o">=</span> <span class="mi">0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">original_max</span> <span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="sd">&quot;&quot;&quot;A float with the upper limit of the Universe of Discourse, the maximal value found on training data&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">original_min</span> <span class="o">=</span> <span class="mi">0</span>
<span class="bp">self</span><span class="o">.</span><span class="n">original_min</span> <span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.0</span>
<span class="sd">&quot;&quot;&quot;A float with the lower limit of the Universe of Discourse, the minimal value found on training data&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;partitioner&quot;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span> <span class="p">:</span> <span class="n">partitioner</span><span class="o">.</span><span class="n">Partitioner</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;partitioner&quot;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="sd">&quot;&quot;&quot;A pyFTS.partitioners.Partitioner object with the Universe of Discourse partitioner used on the model. This is a mandatory dependecy. &quot;&quot;&quot;</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span> <span class="o">!=</span> <span class="kc">None</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span>
<span class="bp">self</span><span class="o">.</span><span class="n">auto_update</span> <span class="o">=</span> <span class="kc">False</span>
<span class="bp">self</span><span class="o">.</span><span class="n">auto_update</span> <span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="sd">&quot;&quot;&quot;A boolean value indicating that model is incremental&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">benchmark_only</span> <span class="o">=</span> <span class="kc">False</span>
<span class="bp">self</span><span class="o">.</span><span class="n">benchmark_only</span> <span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="sd">&quot;&quot;&quot;A boolean value indicating a façade for external (non-FTS) model used on benchmarks or ensembles.&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">indexer</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;indexer&quot;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="sd">&quot;&quot;&quot;An pyFTS.models.seasonal.Indexer object for indexing the time series data&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">uod_clip</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;uod_clip&quot;</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">uod_clip</span> <span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;uod_clip&quot;</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
<span class="sd">&quot;&quot;&quot;Flag indicating if the test data will be clipped inside the training Universe of Discourse&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">alpha_cut</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;alpha_cut&quot;</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">alpha_cut</span> <span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;alpha_cut&quot;</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">)</span>
<span class="sd">&quot;&quot;&quot;A float with the minimal membership to be considered on fuzzyfication process&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">lags</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;lags&quot;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">lags</span> <span class="p">:</span> <span class="nb">list</span><span class="p">[</span><span class="nb">int</span><span class="p">]</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;lags&quot;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="sd">&quot;&quot;&quot;The list of lag indexes for high order models&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span>
<span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span>
<span class="sd">&quot;&quot;&quot;A integer indicating the largest lag used by the model. This value also indicates the minimum number of past lags </span>
<span class="sd"> needed to forecast a single step ahead&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">log</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">([],</span><span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;Datetime&quot;</span><span class="p">,</span><span class="s2">&quot;Operation&quot;</span><span class="p">,</span><span class="s2">&quot;Value&quot;</span><span class="p">])</span>
<span class="bp">self</span><span class="o">.</span><span class="n">log</span> <span class="p">:</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">([],</span><span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s2">&quot;Datetime&quot;</span><span class="p">,</span><span class="s2">&quot;Operation&quot;</span><span class="p">,</span><span class="s2">&quot;Value&quot;</span><span class="p">])</span>
<span class="sd">&quot;&quot;&quot;&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">is_time_variant</span> <span class="o">=</span> <span class="kc">False</span>
<span class="bp">self</span><span class="o">.</span><span class="n">is_time_variant</span> <span class="p">:</span> <span class="nb">bool</span> <span class="o">=</span> <span class="kc">False</span>
<span class="sd">&quot;&quot;&quot;A boolean value indicating if this model is time variant&quot;&quot;&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">standard_horizon</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;standard_horizon&quot;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">standard_horizon</span> <span class="p">:</span> <span class="nb">int</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;standard_horizon&quot;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="sd">&quot;&quot;&quot;Standard forecasting horizon (Default: 1)&quot;&quot;&quot;</span>
<div class="viewcode-block" id="FTS.fuzzy"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.fuzzy">[docs]</a> <span class="k">def</span> <span class="nf">fuzzy</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
<div class="viewcode-block" id="FTS.fuzzy"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.fuzzy">[docs]</a> <span class="k">def</span> <span class="nf">fuzzy</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">dict</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Fuzzify a data point</span>
@ -234,7 +225,7 @@
<span class="k">else</span><span class="p">:</span>
<span class="k">if</span> <span class="n">distributed</span> <span class="o">==</span> <span class="s1">&#39;dispy&#39;</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">pyFTS.distributed</span> <span class="kn">import</span> <span class="n">dispy</span>
<span class="kn">from</span> <span class="nn">pyFTS.distributed</span> <span class="k">import</span> <span class="n">dispy</span>
<span class="n">nodes</span> <span class="o">=</span> <span class="n">kw</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s2">&quot;nodes&quot;</span><span class="p">,</span> <span class="p">[</span><span class="s1">&#39;127.0.0.1&#39;</span><span class="p">])</span>
<span class="n">num_batches</span> <span class="o">=</span> <span class="n">kw</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">&#39;num_batches&#39;</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
@ -242,7 +233,7 @@
<span class="n">ret</span> <span class="o">=</span> <span class="n">dispy</span><span class="o">.</span><span class="n">distributed_predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">kw</span><span class="p">,</span> <span class="n">nodes</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="n">num_batches</span><span class="p">,</span> <span class="o">**</span><span class="n">kw</span><span class="p">)</span>
<span class="k">elif</span> <span class="n">distributed</span> <span class="o">==</span> <span class="s1">&#39;spark&#39;</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">pyFTS.distributed</span> <span class="kn">import</span> <span class="n">spark</span>
<span class="kn">from</span> <span class="nn">pyFTS.distributed</span> <span class="k">import</span> <span class="n">spark</span>
<span class="n">ret</span> <span class="o">=</span> <span class="n">spark</span><span class="o">.</span><span class="n">distributed_predict</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">ndata</span><span class="p">,</span> <span class="n">model</span><span class="o">=</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kw</span><span class="p">)</span>
@ -255,7 +246,7 @@
<span class="k">return</span> <span class="n">ret</span></div>
<div class="viewcode-block" id="FTS.forecast"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<div class="viewcode-block" id="FTS.forecast"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Point forecast one step ahead</span>
@ -265,7 +256,7 @@
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="s1">&#39;This model do not perform one step ahead point forecasts!&#39;</span><span class="p">)</span></div>
<div class="viewcode-block" id="FTS.forecast_interval"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<div class="viewcode-block" id="FTS.forecast_interval"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Interval forecast one step ahead</span>
@ -275,7 +266,7 @@
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="s1">&#39;This model do not perform one step ahead interval forecasts!&#39;</span><span class="p">)</span></div>
<div class="viewcode-block" id="FTS.forecast_distribution"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_distribution">[docs]</a> <span class="k">def</span> <span class="nf">forecast_distribution</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<div class="viewcode-block" id="FTS.forecast_distribution"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_distribution">[docs]</a> <span class="k">def</span> <span class="nf">forecast_distribution</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Probabilistic forecast one step ahead</span>
@ -285,7 +276,7 @@
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="s1">&#39;This model do not perform one step ahead distribution forecasts!&#39;</span><span class="p">)</span></div>
<div class="viewcode-block" id="FTS.forecast_multivariate"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_multivariate">[docs]</a> <span class="k">def</span> <span class="nf">forecast_multivariate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<div class="viewcode-block" id="FTS.forecast_multivariate"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_multivariate">[docs]</a> <span class="k">def</span> <span class="nf">forecast_multivariate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Multivariate forecast one step ahead</span>
@ -296,7 +287,7 @@
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="s1">&#39;This model do not perform one step ahead multivariate forecasts!&#39;</span><span class="p">)</span></div>
<div class="viewcode-block" id="FTS.forecast_ahead"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_ahead">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<div class="viewcode-block" id="FTS.forecast_ahead"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_ahead">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Point forecast from 1 to H steps ahead, where H is given by the steps parameter</span>
@ -326,7 +317,7 @@
<span class="k">return</span> <span class="n">ret</span><span class="p">[</span><span class="o">-</span><span class="n">steps</span><span class="p">:]</span></div>
<div class="viewcode-block" id="FTS.forecast_ahead_interval"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_ahead_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<div class="viewcode-block" id="FTS.forecast_ahead_interval"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_ahead_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Interval forecast from 1 to H steps ahead, where H is given by the steps parameter</span>
@ -337,7 +328,7 @@
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="s1">&#39;This model do not perform multi step ahead interval forecasts!&#39;</span><span class="p">)</span></div>
<div class="viewcode-block" id="FTS.forecast_ahead_distribution"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_ahead_distribution">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead_distribution</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<div class="viewcode-block" id="FTS.forecast_ahead_distribution"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_ahead_distribution">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead_distribution</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Probabilistic forecast from 1 to H steps ahead, where H is given by the steps parameter</span>
@ -348,7 +339,7 @@
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="s1">&#39;This model do not perform multi step ahead distribution forecasts!&#39;</span><span class="p">)</span></div>
<div class="viewcode-block" id="FTS.forecast_ahead_multivariate"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_ahead_multivariate">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead_multivariate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<div class="viewcode-block" id="FTS.forecast_ahead_multivariate"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_ahead_multivariate">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead_multivariate</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Multivariate forecast n step ahead</span>
@ -359,7 +350,7 @@
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="s1">&#39;This model do not perform one step ahead multivariate forecasts!&#39;</span><span class="p">)</span></div>
<div class="viewcode-block" id="FTS.forecast_step"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_step">[docs]</a> <span class="k">def</span> <span class="nf">forecast_step</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">step</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<div class="viewcode-block" id="FTS.forecast_step"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_step">[docs]</a> <span class="k">def</span> <span class="nf">forecast_step</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">step</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Point forecast for H steps ahead, where H is given by the step parameter</span>
@ -381,7 +372,7 @@
<span class="n">start</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;start_at&#39;</span><span class="p">,</span><span class="mi">0</span><span class="p">)</span>
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">start</span><span class="o">+</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">start</span><span class="o">+</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="n">l</span><span class="o">+</span><span class="mi">1</span><span class="p">):</span>
<span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span><span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span><span class="n">k</span><span class="p">]</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast_ahead</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="n">step</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
@ -457,13 +448,13 @@
<span class="n">num_batches</span> <span class="o">=</span> <span class="mi">10</span>
<span class="k">if</span> <span class="n">distributed</span> <span class="o">==</span> <span class="s1">&#39;dispy&#39;</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">pyFTS.distributed</span> <span class="kn">import</span> <span class="n">dispy</span>
<span class="kn">from</span> <span class="nn">pyFTS.distributed</span> <span class="k">import</span> <span class="n">dispy</span>
<span class="n">nodes</span> <span class="o">=</span> <span class="n">kw</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">&#39;nodes&#39;</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span>
<span class="n">train_method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;train_method&#39;</span><span class="p">,</span> <span class="n">dispy</span><span class="o">.</span><span class="n">simple_model_train</span><span class="p">)</span>
<span class="n">dispy</span><span class="o">.</span><span class="n">distributed_train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">train_method</span><span class="p">,</span> <span class="n">nodes</span><span class="p">,</span> <span class="nb">type</span><span class="p">(</span><span class="bp">self</span><span class="p">),</span> <span class="n">data</span><span class="p">,</span> <span class="n">num_batches</span><span class="p">,</span> <span class="p">{},</span>
<span class="o">**</span><span class="n">kw</span><span class="p">)</span>
<span class="k">elif</span> <span class="n">distributed</span> <span class="o">==</span> <span class="s1">&#39;spark&#39;</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">pyFTS.distributed</span> <span class="kn">import</span> <span class="n">spark</span>
<span class="kn">from</span> <span class="nn">pyFTS.distributed</span> <span class="k">import</span> <span class="n">spark</span>
<span class="n">url</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;url&#39;</span><span class="p">,</span> <span class="s1">&#39;spark://127.0.0.1:7077&#39;</span><span class="p">)</span>
<span class="n">app</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;app&#39;</span><span class="p">,</span> <span class="s1">&#39;pyFTS&#39;</span><span class="p">)</span>
@ -481,7 +472,7 @@
<span class="n">rng</span> <span class="o">=</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">)</span>
<span class="k">if</span> <span class="n">dump</span> <span class="o">==</span> <span class="s1">&#39;tqdm&#39;</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">tqdm</span> <span class="kn">import</span> <span class="n">tqdm</span>
<span class="kn">from</span> <span class="nn">tqdm</span> <span class="k">import</span> <span class="n">tqdm</span>
<span class="n">rng</span> <span class="o">=</span> <span class="n">tqdm</span><span class="p">(</span><span class="n">rng</span><span class="p">)</span>
@ -630,7 +621,7 @@
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">data</span></div>
<div class="viewcode-block" id="FTS.get_UoD"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.get_UoD">[docs]</a> <span class="k">def</span> <span class="nf">get_UoD</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<div class="viewcode-block" id="FTS.get_UoD"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.get_UoD">[docs]</a> <span class="k">def</span> <span class="nf">get_UoD</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">set</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Returns the interval of the known bounds of the universe of discourse (UoD), i. e.,</span>
<span class="sd"> the known minimum and maximum values of the time series.</span>
@ -642,7 +633,7 @@
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">original_min</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_max</span><span class="p">)</span></div>
<div class="viewcode-block" id="FTS.offset"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.offset">[docs]</a> <span class="k">def</span> <span class="nf">offset</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<div class="viewcode-block" id="FTS.offset"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.offset">[docs]</a> <span class="k">def</span> <span class="nf">offset</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">int</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Returns the number of lags to skip in the input test data in order to synchronize it with</span>
<span class="sd"> the forecasted values given by the predict function. This is necessary due to the order of the</span>
@ -655,7 +646,7 @@
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="mi">1</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> String representation of the model</span>
@ -672,7 +663,7 @@
<span class="n">tmp</span> <span class="o">=</span> <span class="s2">&quot;</span><span class="si">{0}{1}</span><span class="se">\n</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">tmp</span><span class="p">,</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">r</span><span class="p">]))</span>
<span class="k">return</span> <span class="n">tmp</span>
<span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> The length (number of rules) of the model</span>
@ -718,7 +709,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
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<input type="submit" value="Go" />
</form>
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@ -737,14 +728,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.common.fts</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0"><script type="text/javascript">
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<title>pyFTS.common.tree &#8212; pyFTS 1.6 documentation</title>
<link rel="stylesheet" href="../../../_static/bizstyle.css" type="text/css" />
<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>pyFTS.common.tree &#8212; pyFTS 1.7 documentation</title>
<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css" />
<link rel="stylesheet" type="text/css" href="../../../_static/bizstyle.css" />
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.common.tree</a></li>
</ul>
@ -59,8 +47,8 @@
<span class="sd">Tree data structure</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="kn">import</span> <span class="o">*</span>
<span class="kn">from</span> <span class="nn">functools</span> <span class="kn">import</span> <span class="n">reduce</span>
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="k">import</span> <span class="o">*</span>
<span class="kn">from</span> <span class="nn">functools</span> <span class="k">import</span> <span class="n">reduce</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
@ -69,7 +57,7 @@
<span class="sd"> Tree node for</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">isRoot</span> <span class="o">=</span> <span class="kc">False</span>
<span class="bp">self</span><span class="o">.</span><span class="n">children</span> <span class="o">=</span> <span class="p">[]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">=</span> <span class="n">value</span>
@ -98,13 +86,13 @@
<span class="n">tmp</span> <span class="o">=</span> <span class="n">tmp</span> <span class="o">+</span> <span class="s2">&quot;</span><span class="se">\n</span><span class="s2">&quot;</span> <span class="o">+</span> <span class="n">child</span><span class="o">.</span><span class="n">getStr</span><span class="p">(</span><span class="n">k</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
<span class="k">return</span> <span class="n">tmp</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">getStr</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span></div>
<div class="viewcode-block" id="FLRGTree"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.tree.FLRGTree">[docs]</a><span class="k">class</span> <span class="nc">FLRGTree</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;Represents a FLRG set with a tree structure&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">root</span> <span class="o">=</span> <span class="n">FLRGTreeNode</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span></div>
@ -140,7 +128,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
<input type="text" name="q" aria-labelledby="searchlabel" autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false"/>
<input type="submit" value="Go" />
</form>
</div>
@ -159,14 +147,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.common.tree</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0"><script type="text/javascript">
var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-55120145-3']);
_gaq.push(['_trackPageview']);
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ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
})();
</script>
<title>pyFTS.data.AirPassengers &#8212; pyFTS 1.6 documentation</title>
<link rel="stylesheet" href="../../../_static/bizstyle.css" type="text/css" />
<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>pyFTS.data.AirPassengers &#8212; pyFTS 1.7 documentation</title>
<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css" />
<link rel="stylesheet" type="text/css" href="../../../_static/bizstyle.css" />
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<!--[if lt IE 9]>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.data.AirPassengers</a></li>
</ul>
@ -61,12 +49,12 @@
<span class="sd">Source: Hyndman, R.J., Time Series Data Library, http://www-personal.buseco.monash.edu.au/~hyndman/TSDL/.</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="kn">import</span> <span class="n">common</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.AirPassengers.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">():</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.AirPassengers.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get a simple univariate time series data.</span>
@ -76,7 +64,7 @@
<span class="n">dat</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="s2">&quot;Passengers&quot;</span><span class="p">])</span>
<span class="k">return</span> <span class="n">dat</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.AirPassengers.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.AirPassengers.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
@ -99,7 +87,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
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<input type="submit" value="Go" />
</form>
</div>
@ -118,14 +106,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.data.AirPassengers</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0"><script type="text/javascript">
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<title>pyFTS.data.Bitcoin &#8212; pyFTS 1.6 documentation</title>
<link rel="stylesheet" href="../../../_static/bizstyle.css" type="text/css" />
<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>pyFTS.data.Bitcoin &#8212; pyFTS 1.7 documentation</title>
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<script src="../../../_static/jquery.js"></script>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.data.Bitcoin</a></li>
</ul>
@ -64,12 +52,12 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="kn">import</span> <span class="n">common</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Bitcoin.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="o">=</span><span class="s1">&#39;AVG&#39;</span><span class="p">):</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Bitcoin.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="p">:</span><span class="nb">str</span><span class="o">=</span><span class="s1">&#39;AVG&#39;</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the univariate time series data.</span>
@ -79,7 +67,8 @@
<span class="n">dat</span> <span class="o">=</span> <span class="n">get_dataframe</span><span class="p">()</span>
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="n">field</span><span class="p">])</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Bitcoin.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Bitcoin.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
@ -102,7 +91,7 @@
<h3 id="searchlabel">Quick search</h3>
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@ -121,14 +110,14 @@
<li class="right" >
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
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Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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@ -5,31 +5,19 @@
<html>
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<title>pyFTS.data.DowJones &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
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@ -64,12 +52,12 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="kn">import</span> <span class="n">common</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.DowJones.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="o">=</span><span class="s1">&#39;AVG&#39;</span><span class="p">):</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.DowJones.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="p">:</span><span class="nb">str</span><span class="o">=</span><span class="s1">&#39;AVG&#39;</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the univariate time series data.</span>
@ -80,7 +68,7 @@
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="n">field</span><span class="p">])</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.DowJones.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.DowJones.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
@ -103,7 +91,7 @@
<h3 id="searchlabel">Quick search</h3>
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@ -122,14 +110,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
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@ -5,31 +5,19 @@
<html>
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<title>pyFTS.data.EURGBP &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
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>modules</a> |</li>
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<li class="nav-item nav-item-this"><a href="">pyFTS.data.EURGBP</a></li>
</ul>
@ -62,12 +50,12 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="kn">import</span> <span class="n">common</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.EURGBP.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="o">=</span><span class="s1">&#39;avg&#39;</span><span class="p">):</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.EURGBP.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="p">:</span><span class="nb">str</span><span class="o">=</span><span class="s1">&#39;avg&#39;</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the univariate time series data.</span>
@ -78,7 +66,7 @@
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="n">field</span><span class="p">])</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.EURGBP.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.EURGBP.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
@ -101,7 +89,7 @@
<h3 id="searchlabel">Quick search</h3>
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<form class="search" action="../../../search.html" method="get">
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@ -120,14 +108,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
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View File

@ -5,31 +5,19 @@
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<title>pyFTS.data.EURUSD &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.data.EURUSD</a></li>
</ul>
@ -62,12 +50,12 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="kn">import</span> <span class="n">common</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.EURUSD.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="o">=</span><span class="s1">&#39;avg&#39;</span><span class="p">):</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.EURUSD.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="p">:</span> <span class="nb">str</span><span class="o">=</span><span class="s1">&#39;avg&#39;</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the univariate time series data.</span>
@ -78,7 +66,7 @@
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="n">field</span><span class="p">])</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.EURUSD.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.EURUSD.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
@ -101,7 +89,7 @@
<h3 id="searchlabel">Quick search</h3>
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<form class="search" action="../../../search.html" method="get">
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@ -120,14 +108,14 @@
<li class="right" >
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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View File

@ -5,31 +5,19 @@
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<title>pyFTS.data.Enrollments &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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</ul>
@ -59,12 +47,12 @@
<span class="sd">Yearly University of Alabama enrollments from 1971 to 1992.</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="kn">import</span> <span class="n">common</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Enrollments.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">():</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Enrollments.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get a simple univariate time series data.</span>
@ -75,7 +63,7 @@
<span class="k">return</span> <span class="n">dat</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Enrollments.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Enrollments.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="n">dat</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">get_dataframe</span><span class="p">(</span><span class="s1">&#39;Enrollments.csv&#39;</span><span class="p">,</span>
<span class="s1">&#39;https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/Enrollments.csv&#39;</span><span class="p">,</span>
<span class="n">sep</span><span class="o">=</span><span class="s2">&quot;;&quot;</span><span class="p">)</span>
@ -92,7 +80,7 @@
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@ -111,14 +99,14 @@
<li class="right" >
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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@ -5,31 +5,19 @@
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<title>pyFTS.data.Ethereum &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
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@ -64,12 +52,12 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="kn">import</span> <span class="n">common</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Ethereum.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="o">=</span><span class="s1">&#39;AVG&#39;</span><span class="p">):</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Ethereum.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="p">:</span> <span class="nb">str</span><span class="o">=</span><span class="s1">&#39;AVG&#39;</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the univariate time series data.</span>
@ -80,7 +68,7 @@
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="n">field</span><span class="p">])</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Ethereum.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Ethereum.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
@ -103,7 +91,7 @@
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@ -122,14 +110,14 @@
<li class="right" >
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@ -5,31 +5,19 @@
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<title>pyFTS.data.GBPUSD &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-this"><a href="">pyFTS.data.GBPUSD</a></li>
</ul>
@ -62,12 +50,12 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="kn">import</span> <span class="n">common</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.GBPUSD.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="o">=</span><span class="s1">&#39;avg&#39;</span><span class="p">):</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.GBPUSD.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="p">:</span> <span class="nb">str</span><span class="o">=</span><span class="s1">&#39;avg&#39;</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the univariate time series data.</span>
@ -78,7 +66,7 @@
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="n">field</span><span class="p">])</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.GBPUSD.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.GBPUSD.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
@ -101,7 +89,7 @@
<h3 id="searchlabel">Quick search</h3>
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<li class="right" >
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
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&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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@ -5,31 +5,19 @@
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<title>pyFTS.data.INMET &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
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<li class="nav-item nav-item-this"><a href="">pyFTS.data.INMET</a></li>
</ul>
@ -63,11 +51,11 @@
<span class="sd">Source: http://www.inmet.gov.br</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="kn">import</span> <span class="n">common</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.INMET.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.INMET.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
@ -90,7 +78,7 @@
<h3 id="searchlabel">Quick search</h3>
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<form class="search" action="../../../search.html" method="get">
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@ -109,14 +97,14 @@
<li class="right" >
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@ -60,12 +48,12 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="kn">import</span> <span class="n">common</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Malaysia.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="o">=</span><span class="s1">&#39;load&#39;</span><span class="p">):</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Malaysia.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="p">:</span> <span class="nb">str</span><span class="o">=</span><span class="s1">&#39;load&#39;</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the univariate time series data.</span>
@ -76,7 +64,7 @@
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="n">field</span><span class="p">])</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Malaysia.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Malaysia.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
@ -100,7 +88,7 @@
<h3 id="searchlabel">Quick search</h3>
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@ -119,14 +107,14 @@
<li class="right" >
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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@ -5,31 +5,19 @@
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@ -43,7 +31,7 @@
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@ -63,12 +51,12 @@
<span class="sd">Source: http://www.nasdaq.com/aspx/flashquotes.aspx?symbol=IXIC&amp;selected=IXIC</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="kn">import</span> <span class="n">common</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.NASDAQ.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="o">=</span><span class="s2">&quot;avg&quot;</span><span class="p">):</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.NASDAQ.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="p">:</span> <span class="nb">str</span><span class="o">=</span><span class="s2">&quot;avg&quot;</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get a simple univariate time series data.</span>
@ -80,7 +68,7 @@
<span class="k">return</span> <span class="n">dat</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.NASDAQ.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.NASDAQ.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
@ -103,7 +91,7 @@
<h3 id="searchlabel">Quick search</h3>
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@ -122,14 +110,14 @@
<li class="right" >
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
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View File

@ -5,31 +5,19 @@
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
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<li class="nav-item nav-item-this"><a href="">pyFTS.data.SONDA</a></li>
</ul>
@ -63,12 +51,12 @@
<span class="sd">Source: http://sonda.ccst.inpe.br/</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="kn">import</span> <span class="n">common</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.SONDA.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="p">):</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.SONDA.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="p">:</span><span class="nb">str</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get a simple univariate time series data.</span>
@ -80,7 +68,7 @@
<span class="k">return</span> <span class="n">dat</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.SONDA.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.SONDA.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
@ -104,7 +92,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
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<input type="submit" value="Go" />
</form>
</div>
@ -123,14 +111,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.data.SONDA</a></li>
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<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0"><script type="text/javascript">
var _gaq = _gaq || [];
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ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
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<title>pyFTS.data.SP500 &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-this"><a href="">pyFTS.data.SP500</a></li>
</ul>
@ -63,12 +51,12 @@
<span class="sd">Source: https://finance.yahoo.com/quote/%5EGSPC/history?p=%5EGSPC</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="kn">import</span> <span class="n">common</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.SP500.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">():</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.SP500.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the univariate time series data.</span>
@ -78,7 +66,7 @@
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="s2">&quot;Avg&quot;</span><span class="p">])</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.SP500.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.SP500.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
@ -101,7 +89,7 @@
<h3 id="searchlabel">Quick search</h3>
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@ -120,14 +108,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
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<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.data.SP500</a></li>
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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@ -5,31 +5,19 @@
<html>
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<title>pyFTS.data.TAIEX &#8212; pyFTS 1.6 documentation</title>
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<title>pyFTS.data.TAIEX &#8212; pyFTS 1.7 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
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@ -62,12 +50,12 @@
<span class="sd">Source: http://www.twse.com.tw/en/products/indices/Index_Series.php</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="kn">import</span> <span class="n">common</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.TAIEX.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">():</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.TAIEX.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the univariate time series data.</span>
@ -78,7 +66,7 @@
<span class="k">return</span> <span class="n">dat</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.TAIEX.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.TAIEX.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
@ -102,7 +90,7 @@
<h3 id="searchlabel">Quick search</h3>
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<form class="search" action="../../../search.html" method="get">
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<input type="submit" value="Go" />
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@ -121,14 +109,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
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<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.data.TAIEX</a></li>
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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@ -5,31 +5,19 @@
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<title>pyFTS.data.artificial &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.data.artificial</a></li>
</ul>
@ -67,13 +55,13 @@
<span class="sd"> Emulate a complex signal built from several additive and non-additive components</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">SignalEmulator</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
<span class="bp">self</span><span class="o">.</span><span class="n">components</span> <span class="o">=</span> <span class="p">[]</span>
<span class="sd">&quot;&quot;&quot;Components of the signal&quot;&quot;&quot;</span>
<div class="viewcode-block" id="SignalEmulator.stationary_gaussian"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.artificial.SignalEmulator.stationary_gaussian">[docs]</a> <span class="k">def</span> <span class="nf">stationary_gaussian</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">mu</span><span class="p">,</span> <span class="n">sigma</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<div class="viewcode-block" id="SignalEmulator.stationary_gaussian"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.artificial.SignalEmulator.stationary_gaussian">[docs]</a> <span class="k">def</span> <span class="nf">stationary_gaussian</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">mu</span><span class="p">:</span><span class="nb">float</span><span class="p">,</span> <span class="n">sigma</span><span class="p">:</span><span class="nb">float</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Creates a continuous Gaussian signal with mean mu and variance sigma.</span>
@ -93,7 +81,7 @@
<span class="s1">&#39;parameters&#39;</span><span class="p">:</span> <span class="n">parameters</span><span class="p">,</span> <span class="s1">&#39;args&#39;</span><span class="p">:</span> <span class="n">kwargs</span><span class="p">})</span>
<span class="k">return</span> <span class="bp">self</span></div>
<div class="viewcode-block" id="SignalEmulator.incremental_gaussian"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.artificial.SignalEmulator.incremental_gaussian">[docs]</a> <span class="k">def</span> <span class="nf">incremental_gaussian</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">mu</span><span class="p">,</span> <span class="n">sigma</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<div class="viewcode-block" id="SignalEmulator.incremental_gaussian"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.artificial.SignalEmulator.incremental_gaussian">[docs]</a> <span class="k">def</span> <span class="nf">incremental_gaussian</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">mu</span><span class="p">:</span><span class="nb">float</span><span class="p">,</span> <span class="n">sigma</span><span class="p">:</span><span class="nb">float</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Creates an additive gaussian interference on a previous signal</span>
@ -111,7 +99,7 @@
<span class="s1">&#39;parameters&#39;</span><span class="p">:</span> <span class="n">parameters</span><span class="p">,</span> <span class="s1">&#39;args&#39;</span><span class="p">:</span> <span class="n">kwargs</span><span class="p">})</span>
<span class="k">return</span> <span class="bp">self</span></div>
<div class="viewcode-block" id="SignalEmulator.periodic_gaussian"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.artificial.SignalEmulator.periodic_gaussian">[docs]</a> <span class="k">def</span> <span class="nf">periodic_gaussian</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="nb">type</span><span class="p">,</span> <span class="n">period</span><span class="p">,</span> <span class="n">mu_min</span><span class="p">,</span> <span class="n">sigma_min</span><span class="p">,</span> <span class="n">mu_max</span><span class="p">,</span> <span class="n">sigma_max</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<div class="viewcode-block" id="SignalEmulator.periodic_gaussian"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.artificial.SignalEmulator.periodic_gaussian">[docs]</a> <span class="k">def</span> <span class="nf">periodic_gaussian</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="nb">type</span><span class="p">:</span><span class="nb">str</span><span class="p">,</span> <span class="n">period</span><span class="p">:</span><span class="nb">int</span><span class="p">,</span> <span class="n">mu_min</span><span class="p">:</span><span class="nb">float</span><span class="p">,</span> <span class="n">sigma_min</span><span class="p">:</span><span class="nb">float</span><span class="p">,</span> <span class="n">mu_max</span><span class="p">:</span><span class="nb">float</span><span class="p">,</span> <span class="n">sigma_max</span><span class="p">:</span><span class="nb">float</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Creates an additive periodic gaussian interference on a previous signal</span>
@ -407,7 +395,7 @@
<h3 id="searchlabel">Quick search</h3>
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@ -426,14 +414,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
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<li class="nav-item nav-item-this"><a href="">pyFTS.data.artificial</a></li>
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<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
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<title>pyFTS.data.common &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
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<li class="nav-item nav-item-this"><a href="">pyFTS.data.common</a></li>
</ul>
@ -60,11 +48,11 @@
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">os</span>
<span class="kn">import</span> <span class="nn">pkg_resources</span>
<span class="kn">from</span> <span class="nn">pathlib</span> <span class="kn">import</span> <span class="n">Path</span>
<span class="kn">from</span> <span class="nn">urllib</span> <span class="kn">import</span> <span class="n">request</span>
<span class="kn">from</span> <span class="nn">pathlib</span> <span class="k">import</span> <span class="n">Path</span>
<span class="kn">from</span> <span class="nn">urllib</span> <span class="k">import</span> <span class="n">request</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.common.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">(</span><span class="n">filename</span><span class="p">,</span> <span class="n">url</span><span class="p">,</span> <span class="n">sep</span><span class="o">=</span><span class="s2">&quot;;&quot;</span><span class="p">,</span> <span class="n">compression</span><span class="o">=</span><span class="s1">&#39;infer&#39;</span><span class="p">):</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.common.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">(</span><span class="n">filename</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">url</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">sep</span><span class="p">:</span><span class="nb">str</span><span class="o">=</span><span class="s2">&quot;;&quot;</span><span class="p">,</span> <span class="n">compression</span><span class="p">:</span><span class="nb">str</span><span class="o">=</span><span class="s1">&#39;infer&#39;</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> This method check if filename already exists, read the file and return its data.</span>
<span class="sd"> If the file don&#39;t already exists, it will be downloaded and decompressed.</span>
@ -97,7 +85,7 @@
<h3 id="searchlabel">Quick search</h3>
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<input type="submit" value="Go" />
</form>
</div>
@ -116,14 +104,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.data.common</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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</html>

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@ -5,31 +5,19 @@
<html>
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<title>pyFTS.data.henon &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.data.henon</a></li>
</ul>
@ -66,7 +54,7 @@
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.henon.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">var</span><span class="p">,</span> <span class="n">a</span><span class="o">=</span><span class="mf">1.4</span><span class="p">,</span> <span class="n">b</span><span class="o">=</span><span class="mf">0.3</span><span class="p">,</span> <span class="n">initial_values</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">1000</span><span class="p">):</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.henon.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">var</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">a</span><span class="p">:</span><span class="nb">float</span><span class="o">=</span><span class="mf">1.4</span><span class="p">,</span> <span class="n">b</span><span class="p">:</span><span class="nb">float</span><span class="o">=</span><span class="mf">0.3</span><span class="p">,</span> <span class="n">initial_values</span><span class="p">:</span> <span class="nb">list</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">iterations</span><span class="p">:</span><span class="nb">int</span><span class="o">=</span><span class="mi">1000</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get a simple univariate time series data.</span>
@ -76,7 +64,7 @@
<span class="k">return</span> <span class="n">get_dataframe</span><span class="p">(</span><span class="n">a</span><span class="p">,</span><span class="n">b</span><span class="p">,</span> <span class="n">initial_values</span><span class="p">,</span> <span class="n">iterations</span><span class="p">)[</span><span class="n">var</span><span class="p">]</span><span class="o">.</span><span class="n">values</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.henon.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">(</span><span class="n">a</span><span class="o">=</span><span class="mf">1.4</span><span class="p">,</span> <span class="n">b</span><span class="o">=</span><span class="mf">0.3</span><span class="p">,</span> <span class="n">initial_values</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">1000</span><span class="p">):</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.henon.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">(</span><span class="n">a</span><span class="p">:</span><span class="nb">float</span><span class="o">=</span><span class="mf">1.4</span><span class="p">,</span> <span class="n">b</span><span class="p">:</span><span class="nb">float</span><span class="o">=</span><span class="mf">0.3</span><span class="p">,</span> <span class="n">initial_values</span><span class="p">:</span> <span class="nb">list</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">iterations</span><span class="p">:</span><span class="nb">int</span><span class="o">=</span><span class="mi">1000</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&#39;&#39;&#39;</span>
<span class="sd"> Return a dataframe with the bivariate Henon Map time series (x, y).</span>
@ -107,7 +95,7 @@
<h3 id="searchlabel">Quick search</h3>
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@ -126,14 +114,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.data.henon</a></li>
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<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
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<title>pyFTS.data.logistic_map &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.data.logistic_map</a></li>
</ul>
@ -65,7 +53,7 @@
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.logistic_map.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">r</span> <span class="o">=</span> <span class="mi">4</span><span class="p">,</span> <span class="n">initial_value</span> <span class="o">=</span> <span class="mf">0.3</span><span class="p">,</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">100</span><span class="p">):</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.logistic_map.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">r</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mi">4</span><span class="p">,</span> <span class="n">initial_value</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.3</span><span class="p">,</span> <span class="n">iterations</span><span class="p">:</span> <span class="nb">int</span><span class="o">=</span><span class="mi">100</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">:</span>
<span class="sd">&#39;&#39;&#39;</span>
<span class="sd"> Return a list with the logistic map chaotic time series.</span>
@ -91,7 +79,7 @@
<h3 id="searchlabel">Quick search</h3>
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<form class="search" action="../../../search.html" method="get">
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<input type="submit" value="Go" />
</form>
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@ -110,14 +98,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.data.logistic_map</a></li>
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</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
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<title>pyFTS.data.lorentz &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-this"><a href="">pyFTS.data.lorentz</a></li>
</ul>
@ -68,8 +56,8 @@
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.lorentz.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">var</span><span class="p">,</span> <span class="n">a</span> <span class="o">=</span> <span class="mf">10.0</span><span class="p">,</span> <span class="n">b</span> <span class="o">=</span> <span class="mf">28.0</span><span class="p">,</span> <span class="n">c</span> <span class="o">=</span> <span class="mf">8.0</span> <span class="o">/</span> <span class="mf">3.0</span><span class="p">,</span> <span class="n">dt</span> <span class="o">=</span> <span class="mf">0.01</span><span class="p">,</span>
<span class="n">initial_values</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.1</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">1000</span><span class="p">):</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.lorentz.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">var</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">a</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">10.0</span><span class="p">,</span> <span class="n">b</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">28.0</span><span class="p">,</span> <span class="n">c</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">8.0</span> <span class="o">/</span> <span class="mf">3.0</span><span class="p">,</span> <span class="n">dt</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.01</span><span class="p">,</span>
<span class="n">initial_values</span><span class="p">:</span> <span class="nb">list</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.1</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span> <span class="n">iterations</span><span class="p">:</span> <span class="nb">int</span><span class="o">=</span><span class="mi">1000</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get a simple univariate time series data.</span>
@ -79,8 +67,8 @@
<span class="k">return</span> <span class="n">get_dataframe</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">initial_values</span><span class="p">,</span> <span class="n">iterations</span><span class="p">)[</span><span class="n">var</span><span class="p">]</span><span class="o">.</span><span class="n">values</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.lorentz.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">(</span><span class="n">a</span> <span class="o">=</span> <span class="mf">10.0</span><span class="p">,</span> <span class="n">b</span> <span class="o">=</span> <span class="mf">28.0</span><span class="p">,</span> <span class="n">c</span> <span class="o">=</span> <span class="mf">8.0</span> <span class="o">/</span> <span class="mf">3.0</span><span class="p">,</span> <span class="n">dt</span> <span class="o">=</span> <span class="mf">0.01</span><span class="p">,</span>
<span class="n">initial_values</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.1</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">1000</span><span class="p">):</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.lorentz.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">(</span><span class="n">a</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">10.0</span><span class="p">,</span> <span class="n">b</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">28.0</span><span class="p">,</span> <span class="n">c</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">8.0</span> <span class="o">/</span> <span class="mf">3.0</span><span class="p">,</span> <span class="n">dt</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.01</span><span class="p">,</span>
<span class="n">initial_values</span><span class="p">:</span> <span class="nb">list</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.1</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span> <span class="n">iterations</span><span class="p">:</span> <span class="nb">int</span><span class="o">=</span><span class="mi">1000</span><span class="p">)</span><span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&#39;&#39;&#39;</span>
<span class="sd"> Return a dataframe with the multivariate Lorenz Map time series (x, y, z).</span>
@ -118,7 +106,7 @@
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@ -137,14 +125,14 @@
<li class="right" >
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
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Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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@ -5,31 +5,19 @@
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<title>pyFTS.data.mackey_glass &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
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@ -65,7 +53,7 @@
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.mackey_glass.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">b</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">c</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> <span class="n">tau</span><span class="o">=</span><span class="mi">17</span><span class="p">,</span> <span class="n">initial_values</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">1.5</span><span class="p">,</span> <span class="mi">18</span><span class="p">),</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">1000</span><span class="p">):</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.mackey_glass.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">b</span><span class="p">:</span> <span class="nb">float</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">c</span><span class="p">:</span> <span class="nb">float</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> <span class="n">tau</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span><span class="mi">17</span><span class="p">,</span> <span class="n">initial_values</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">1.5</span><span class="p">,</span> <span class="mi">18</span><span class="p">),</span> <span class="n">iterations</span><span class="p">:</span> <span class="nb">int</span><span class="o">=</span><span class="mi">1000</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">list</span><span class="p">:</span>
<span class="sd">&#39;&#39;&#39;</span>
<span class="sd"> Return a list with the Mackey-Glass chaotic time series.</span>
@ -94,7 +82,7 @@
<h3 id="searchlabel">Quick search</h3>
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@ -113,14 +101,14 @@
<li class="right" >
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<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.data.mackey_glass</a></li>
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

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@ -5,31 +5,19 @@
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<title>pyFTS.data.rossler &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
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</ul>
@ -68,8 +56,8 @@
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.rossler.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">var</span><span class="p">,</span> <span class="n">a</span> <span class="o">=</span> <span class="mf">0.2</span><span class="p">,</span> <span class="n">b</span> <span class="o">=</span> <span class="mf">0.2</span><span class="p">,</span> <span class="n">c</span> <span class="o">=</span> <span class="mf">5.7</span><span class="p">,</span> <span class="n">dt</span> <span class="o">=</span> <span class="mf">0.01</span><span class="p">,</span>
<span class="n">initial_values</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.001</span><span class="p">,</span> <span class="mf">0.001</span><span class="p">,</span> <span class="mf">0.001</span><span class="p">],</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">5000</span><span class="p">):</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.rossler.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">var</span><span class="p">:</span> <span class="nb">str</span><span class="p">,</span> <span class="n">a</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.2</span><span class="p">,</span> <span class="n">b</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.2</span><span class="p">,</span> <span class="n">c</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">5.7</span><span class="p">,</span> <span class="n">dt</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.01</span><span class="p">,</span>
<span class="n">initial_values</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.001</span><span class="p">,</span> <span class="mf">0.001</span><span class="p">,</span> <span class="mf">0.001</span><span class="p">],</span> <span class="n">iterations</span><span class="p">:</span> <span class="nb">int</span><span class="o">=</span><span class="mi">5000</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get a simple univariate time series data.</span>
@ -79,8 +67,8 @@
<span class="k">return</span> <span class="n">get_dataframe</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">initial_values</span><span class="p">,</span> <span class="n">iterations</span><span class="p">)[</span><span class="n">var</span><span class="p">]</span><span class="o">.</span><span class="n">values</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.rossler.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">(</span><span class="n">a</span> <span class="o">=</span> <span class="mf">0.2</span><span class="p">,</span> <span class="n">b</span> <span class="o">=</span> <span class="mf">0.2</span><span class="p">,</span> <span class="n">c</span> <span class="o">=</span> <span class="mf">5.7</span><span class="p">,</span> <span class="n">dt</span> <span class="o">=</span> <span class="mf">0.01</span><span class="p">,</span>
<span class="n">initial_values</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.001</span><span class="p">,</span> <span class="mf">0.001</span><span class="p">,</span> <span class="mf">0.001</span><span class="p">],</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">5000</span><span class="p">):</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.rossler.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">(</span><span class="n">a</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.2</span><span class="p">,</span> <span class="n">b</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.2</span><span class="p">,</span> <span class="n">c</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">5.7</span><span class="p">,</span> <span class="n">dt</span><span class="p">:</span> <span class="nb">float</span> <span class="o">=</span> <span class="mf">0.01</span><span class="p">,</span>
<span class="n">initial_values</span><span class="p">:</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.001</span><span class="p">,</span> <span class="mf">0.001</span><span class="p">,</span> <span class="mf">0.001</span><span class="p">],</span> <span class="n">iterations</span><span class="p">:</span> <span class="nb">int</span><span class="o">=</span><span class="mi">5000</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&#39;&#39;&#39;</span>
<span class="sd"> Return a dataframe with the multivariate Rössler Map time series (x, y, z).</span>
@ -118,7 +106,7 @@
<h3 id="searchlabel">Quick search</h3>
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@ -137,14 +125,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
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<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.data.rossler</a></li>
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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@ -5,31 +5,19 @@
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.data.sunspots</a></li>
</ul>
@ -61,11 +49,11 @@
<span class="sd">Source: https://www.esrl.noaa.gov/psd/gcos_wgsp/Timeseries/SUNSPOT/</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="kn">import</span> <span class="n">common</span>
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.sunspots.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">():</span>
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.sunspots.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get a simple univariate time series data.</span>
@ -75,7 +63,7 @@
<span class="n">dat</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="s2">&quot;SUNACTIVITY&quot;</span><span class="p">])</span>
<span class="k">return</span> <span class="n">dat</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.sunspots.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.sunspots.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">()</span> <span class="o">-&gt;</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">:</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
@ -98,7 +86,7 @@
<h3 id="searchlabel">Quick search</h3>
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<input type="submit" value="Go" />
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@ -117,14 +105,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.data.sunspots</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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@ -5,31 +5,19 @@
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<title>pyFTS.hyperparam.Evolutionary &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.hyperparam.Evolutionary</a></li>
</ul>
@ -63,16 +51,16 @@
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">math</span>
<span class="kn">import</span> <span class="nn">time</span>
<span class="kn">from</span> <span class="nn">functools</span> <span class="kn">import</span> <span class="n">reduce</span>
<span class="kn">from</span> <span class="nn">operator</span> <span class="kn">import</span> <span class="n">itemgetter</span>
<span class="kn">from</span> <span class="nn">functools</span> <span class="k">import</span> <span class="n">reduce</span>
<span class="kn">from</span> <span class="nn">operator</span> <span class="k">import</span> <span class="n">itemgetter</span>
<span class="kn">import</span> <span class="nn">random</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">Util</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="kn">import</span> <span class="n">Measures</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span> <span class="c1"># , Huarng</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">Membership</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">ifts</span><span class="p">,</span> <span class="n">pwfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.hyperparam</span> <span class="kn">import</span> <span class="n">Util</span> <span class="k">as</span> <span class="n">hUtil</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Util</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span> <span class="c1"># , Huarng</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Membership</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">ifts</span><span class="p">,</span> <span class="n">pwfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.hyperparam</span> <span class="k">import</span> <span class="n">Util</span> <span class="k">as</span> <span class="n">hUtil</span>
<span class="n">__measures</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;f1&#39;</span><span class="p">,</span> <span class="s1">&#39;f2&#39;</span><span class="p">,</span> <span class="s1">&#39;rmse&#39;</span><span class="p">,</span> <span class="s1">&#39;size&#39;</span><span class="p">]</span>
@ -144,7 +132,7 @@
<span class="sd"> :param parameters: dict with model specific arguments for fit method.</span>
<span class="sd"> :return: a fitted FTS model</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">ifts</span><span class="p">,</span> <span class="n">pwfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">ifts</span><span class="p">,</span> <span class="n">pwfts</span>
<span class="k">if</span> <span class="n">individual</span><span class="p">[</span><span class="s1">&#39;mf&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="n">mf</span> <span class="o">=</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span>
@ -182,10 +170,10 @@
<span class="sd"> :param parameters: dict with model specific arguments for fit method.</span>
<span class="sd"> :return: a tuple (len_lags, rmse) with the parsimony fitness value and the accuracy fitness value</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">ifts</span><span class="p">,</span> <span class="n">pwfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">Util</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="kn">import</span> <span class="n">Measures</span>
<span class="kn">from</span> <span class="nn">pyFTS.hyperparam.Evolutionary</span> <span class="kn">import</span> <span class="n">phenotype</span><span class="p">,</span> <span class="n">__measures</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">ifts</span><span class="p">,</span> <span class="n">pwfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Util</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span>
<span class="kn">from</span> <span class="nn">pyFTS.hyperparam.Evolutionary</span> <span class="k">import</span> <span class="n">phenotype</span><span class="p">,</span> <span class="n">__measures</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="n">window_size</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;window_size&#39;</span><span class="p">,</span> <span class="mi">800</span><span class="p">)</span>
@ -471,7 +459,7 @@
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">__measures</span><span class="p">:</span>
<span class="n">individual</span><span class="p">[</span><span class="n">key</span><span class="p">]</span> <span class="o">=</span> <span class="n">ret</span><span class="p">[</span><span class="n">key</span><span class="p">]</span>
<span class="k">elif</span> <span class="n">distributed</span><span class="o">==</span><span class="s1">&#39;dispy&#39;</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">pyFTS.distributed</span> <span class="kn">import</span> <span class="n">dispy</span> <span class="k">as</span> <span class="n">dUtil</span>
<span class="kn">from</span> <span class="nn">pyFTS.distributed</span> <span class="k">import</span> <span class="n">dispy</span> <span class="k">as</span> <span class="n">dUtil</span>
<span class="kn">import</span> <span class="nn">dispy</span>
<span class="n">jobs</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">individual</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">population</span><span class="p">):</span>
@ -660,7 +648,7 @@
<span class="n">shortname</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">fts_method</span><span class="o">.</span><span class="vm">__module__</span><span class="p">)</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;.&#39;</span><span class="p">)[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
<span class="k">if</span> <span class="n">distributed</span> <span class="o">==</span> <span class="s1">&#39;dispy&#39;</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">pyFTS.distributed</span> <span class="kn">import</span> <span class="n">dispy</span> <span class="k">as</span> <span class="n">dUtil</span>
<span class="kn">from</span> <span class="nn">pyFTS.distributed</span> <span class="k">import</span> <span class="n">dispy</span> <span class="k">as</span> <span class="n">dUtil</span>
<span class="n">nodes</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;nodes&#39;</span><span class="p">,</span> <span class="p">[</span><span class="s1">&#39;127.0.0.1&#39;</span><span class="p">])</span>
<span class="n">cluster</span><span class="p">,</span> <span class="n">http_server</span> <span class="o">=</span> <span class="n">dUtil</span><span class="o">.</span><span class="n">start_dispy_cluster</span><span class="p">(</span><span class="n">evaluate</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="n">nodes</span><span class="p">)</span>
<span class="n">kwargs</span><span class="p">[</span><span class="s1">&#39;cluster&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">cluster</span>
@ -693,7 +681,7 @@
<h3 id="searchlabel">Quick search</h3>
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<input type="submit" value="Go" />
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@ -712,14 +700,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.hyperparam.Evolutionary</a></li>
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</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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</body>
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@ -5,31 +5,19 @@
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<title>pyFTS.hyperparam.GridSearch &#8212; pyFTS 1.6 documentation</title>
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<title>pyFTS.hyperparam.GridSearch &#8212; pyFTS 1.7 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.hyperparam.GridSearch</a></li>
</ul>
@ -56,14 +44,14 @@
<h1>Source code for pyFTS.hyperparam.GridSearch</h1><div class="highlight"><pre>
<span></span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">Util</span><span class="p">,</span> <span class="n">Membership</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">hofts</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="kn">import</span> <span class="n">Measures</span>
<span class="kn">from</span> <span class="nn">pyFTS.hyperparam</span> <span class="kn">import</span> <span class="n">Util</span> <span class="k">as</span> <span class="n">hUtil</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Util</span><span class="p">,</span> <span class="n">Membership</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span>
<span class="kn">from</span> <span class="nn">pyFTS.hyperparam</span> <span class="k">import</span> <span class="n">Util</span> <span class="k">as</span> <span class="n">hUtil</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="kn">import</span> <span class="n">product</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="k">import</span> <span class="n">product</span>
<div class="viewcode-block" id="dict_individual"><a class="viewcode-back" href="../../../pyFTS.hyperparam.html#pyFTS.hyperparam.GridSearch.dict_individual">[docs]</a><span class="k">def</span> <span class="nf">dict_individual</span><span class="p">(</span><span class="n">mf</span><span class="p">,</span> <span class="n">partitioner</span><span class="p">,</span> <span class="n">partitions</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="n">lags</span><span class="p">,</span> <span class="n">alpha_cut</span><span class="p">):</span>
@ -78,10 +66,10 @@
<div class="viewcode-block" id="cluster_method"><a class="viewcode-back" href="../../../pyFTS.hyperparam.html#pyFTS.hyperparam.GridSearch.cluster_method">[docs]</a><span class="k">def</span> <span class="nf">cluster_method</span><span class="p">(</span><span class="n">individual</span><span class="p">,</span> <span class="n">dataset</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">Util</span><span class="p">,</span> <span class="n">Membership</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">hofts</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="kn">import</span> <span class="n">Measures</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Util</span><span class="p">,</span> <span class="n">Membership</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span>
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="k">if</span> <span class="n">individual</span><span class="p">[</span><span class="s1">&#39;mf&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
@ -129,7 +117,7 @@
<div class="viewcode-block" id="process_jobs"><a class="viewcode-back" href="../../../pyFTS.hyperparam.html#pyFTS.hyperparam.GridSearch.process_jobs">[docs]</a><span class="k">def</span> <span class="nf">process_jobs</span><span class="p">(</span><span class="n">jobs</span><span class="p">,</span> <span class="n">datasetname</span><span class="p">,</span> <span class="n">conn</span><span class="p">):</span>
<span class="kn">from</span> <span class="nn">pyFTS.distributed</span> <span class="kn">import</span> <span class="n">dispy</span> <span class="k">as</span> <span class="n">dUtil</span>
<span class="kn">from</span> <span class="nn">pyFTS.distributed</span> <span class="k">import</span> <span class="n">dispy</span> <span class="k">as</span> <span class="n">dUtil</span>
<span class="kn">import</span> <span class="nn">dispy</span>
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">job</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">jobs</span><span class="p">):</span>
<span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Processing job </span><span class="si">{}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">ct</span><span class="p">))</span>
@ -156,7 +144,7 @@
<div class="viewcode-block" id="execute"><a class="viewcode-back" href="../../../pyFTS.hyperparam.html#pyFTS.hyperparam.GridSearch.execute">[docs]</a><span class="k">def</span> <span class="nf">execute</span><span class="p">(</span><span class="n">hyperparams</span><span class="p">,</span> <span class="n">datasetname</span><span class="p">,</span> <span class="n">dataset</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="kn">from</span> <span class="nn">pyFTS.distributed</span> <span class="kn">import</span> <span class="n">dispy</span> <span class="k">as</span> <span class="n">dUtil</span>
<span class="kn">from</span> <span class="nn">pyFTS.distributed</span> <span class="k">import</span> <span class="n">dispy</span> <span class="k">as</span> <span class="n">dUtil</span>
<span class="kn">import</span> <span class="nn">dispy</span>
<span class="n">nodes</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;nodes&#39;</span><span class="p">,[</span><span class="s1">&#39;127.0.0.1&#39;</span><span class="p">])</span>
@ -240,7 +228,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
<input type="text" name="q" aria-labelledby="searchlabel" autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false"/>
<input type="submit" value="Go" />
</form>
</div>
@ -259,14 +247,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.hyperparam.GridSearch</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
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<meta name="viewport" content="width=device-width, initial-scale=1.0"><script type="text/javascript">
var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-55120145-3']);
_gaq.push(['_trackPageview']);
(function() {
var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
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</script>
<title>pyFTS.hyperparam.Util &#8212; pyFTS 1.6 documentation</title>
<link rel="stylesheet" href="../../../_static/bizstyle.css" type="text/css" />
<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>pyFTS.hyperparam.Util &#8212; pyFTS 1.7 documentation</title>
<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css" />
<link rel="stylesheet" type="text/css" href="../../../_static/bizstyle.css" />
<script id="documentation_options" data-url_root="../../../" src="../../../_static/documentation_options.js"></script>
<script data-url_root="../../../" id="documentation_options" src="../../../_static/documentation_options.js"></script>
<script src="../../../_static/jquery.js"></script>
<script src="../../../_static/underscore.js"></script>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.hyperparam.Util</a></li>
</ul>
@ -137,7 +125,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
<input type="text" name="q" aria-labelledby="searchlabel" autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false"/>
<input type="submit" value="Go" />
</form>
</div>
@ -156,14 +144,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.hyperparam.Util</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
<head>
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0"><script type="text/javascript">
var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-55120145-3']);
_gaq.push(['_trackPageview']);
(function() {
var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
})();
</script>
<title>pyFTS.models.chen &#8212; pyFTS 1.6 documentation</title>
<link rel="stylesheet" href="../../../_static/bizstyle.css" type="text/css" />
<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>pyFTS.models.chen &#8212; pyFTS 1.7 documentation</title>
<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css" />
<link rel="stylesheet" type="text/css" href="../../../_static/bizstyle.css" />
<script id="documentation_options" data-url_root="../../../" src="../../../_static/documentation_options.js"></script>
<script data-url_root="../../../" id="documentation_options" src="../../../_static/documentation_options.js"></script>
<script src="../../../_static/jquery.js"></script>
<script src="../../../_static/underscore.js"></script>
<script src="../../../_static/doctools.js"></script>
<script src="../../../_static/language_data.js"></script>
<script src="../../../_static/bizstyle.js"></script>
<link rel="index" title="Index" href="../../../genindex.html" />
<link rel="search" title="Search" href="../../../search.html" />
<meta name="viewport" content="width=device-width,initial-scale=1.0">
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<!--[if lt IE 9]>
<script src="_static/css3-mediaqueries.js"></script>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.chen</a></li>
</ul>
@ -62,12 +50,12 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span>
<div class="viewcode-block" id="ConventionalFLRG"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.chen.ConventionalFLRG">[docs]</a><span class="k">class</span> <span class="nc">ConventionalFLRG</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;First Order Conventional Fuzzy Logical Relationship Group&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">ConventionalFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="n">LHS</span>
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span>
@ -78,7 +66,7 @@
<div class="viewcode-block" id="ConventionalFLRG.append_rhs"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.chen.ConventionalFLRG.append_rhs">[docs]</a> <span class="k">def</span> <span class="nf">append_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">c</span><span class="p">)</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">+</span> <span class="s2">&quot; -&gt; &quot;</span>
<span class="n">tmp2</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">s</span><span class="p">:</span> <span class="n">s</span><span class="p">):</span>
@ -90,7 +78,7 @@
<div class="viewcode-block" id="ConventionalFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.chen.ConventionalFTS">[docs]</a><span class="k">class</span> <span class="nc">ConventionalFTS</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Conventional Fuzzy Time Series&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">ConventionalFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Conventional FTS&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">&quot;Chen&quot;</span>
@ -157,7 +145,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
<input type="text" name="q" aria-labelledby="searchlabel" autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false"/>
<input type="submit" value="Go" />
</form>
</div>
@ -176,14 +164,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.chen</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
<head>
<meta charset="utf-8" />
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_gaq.push(['_trackPageview']);
(function() {
var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
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<title>pyFTS.models.cheng &#8212; pyFTS 1.6 documentation</title>
<link rel="stylesheet" href="../../../_static/bizstyle.css" type="text/css" />
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<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>pyFTS.models.cheng &#8212; pyFTS 1.7 documentation</title>
<link rel="stylesheet" type="text/css" href="../../../_static/pygments.css" />
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<script data-url_root="../../../" id="documentation_options" src="../../../_static/documentation_options.js"></script>
<script src="../../../_static/jquery.js"></script>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.cheng</a></li>
</ul>
@ -63,15 +51,15 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">yu</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">yu</span>
<div class="viewcode-block" id="TrendWeightedFLRG"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.cheng.TrendWeightedFLRG">[docs]</a><span class="k">class</span> <span class="nc">TrendWeightedFLRG</span><span class="p">(</span><span class="n">yu</span><span class="o">.</span><span class="n">WeightedFLRG</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> First Order Trend Weighted Fuzzy Logical Relationship Group</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">TrendWeightedFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="o">=</span> <span class="kc">None</span>
@ -102,7 +90,7 @@
<div class="viewcode-block" id="TrendWeightedFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.cheng.TrendWeightedFTS">[docs]</a><span class="k">class</span> <span class="nc">TrendWeightedFTS</span><span class="p">(</span><span class="n">yu</span><span class="o">.</span><span class="n">WeightedFTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;First Order Trend Weighted Fuzzy Time Series&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">TrendWeightedFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">&quot;TWFTS&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Trend Weighted FTS&quot;</span>
@ -128,7 +116,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
<input type="text" name="q" aria-labelledby="searchlabel" autocomplete="off" autocorrect="off" autocapitalize="off" spellcheck="false"/>
<input type="submit" value="Go" />
</form>
</div>
@ -147,14 +135,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.cheng</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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</html>

View File

@ -5,31 +5,19 @@
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<title>pyFTS.models.ensemble.ensemble &#8212; pyFTS 1.6 documentation</title>
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<title>pyFTS.models.ensemble.ensemble &#8212; pyFTS 1.7 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.ensemble.ensemble</a></li>
</ul>
@ -66,12 +54,12 @@
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">SortedCollection</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">tree</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">chen</span><span class="p">,</span> <span class="n">cheng</span><span class="p">,</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">hwang</span><span class="p">,</span> <span class="n">ismailefendi</span><span class="p">,</span> <span class="n">sadaei</span><span class="p">,</span> <span class="n">song</span><span class="p">,</span> <span class="n">yu</span>
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="kn">import</span> <span class="n">ProbabilityDistribution</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">SortedCollection</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">tree</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">chen</span><span class="p">,</span> <span class="n">cheng</span><span class="p">,</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">hwang</span><span class="p">,</span> <span class="n">ismailefendi</span><span class="p">,</span> <span class="n">sadaei</span><span class="p">,</span> <span class="n">song</span><span class="p">,</span> <span class="n">yu</span>
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">ProbabilityDistribution</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span>
<span class="kn">import</span> <span class="nn">scipy.stats</span> <span class="k">as</span> <span class="nn">st</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="kn">import</span> <span class="n">product</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="k">import</span> <span class="n">product</span>
<div class="viewcode-block" id="sampler"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.sampler">[docs]</a><span class="k">def</span> <span class="nf">sampler</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">quantiles</span><span class="p">,</span> <span class="n">bounds</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
@ -88,7 +76,7 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Ensemble FTS</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">EnsembleFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">&quot;EnsembleFTS&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Ensemble FTS&quot;</span>
@ -346,7 +334,7 @@
<span class="sd">&#39;&#39;&#39;</span>
<span class="sd"> An homogeneous FTS method ensemble with variations on partitionings and orders.</span>
<span class="sd"> &#39;&#39;&#39;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">SimpleEnsembleFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;fts_method&#39;</span><span class="p">,</span> <span class="n">hofts</span><span class="o">.</span><span class="n">WeightedHighOrderFTS</span><span class="p">)</span>
<span class="sd">&quot;&quot;&quot;FTS method class that will be used on internal models&quot;&quot;&quot;</span>
@ -376,7 +364,7 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Creates an EnsembleFTS with all point forecast methods, sharing the same partitioner</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">AllMethodEnsembleFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">min_order</span> <span class="o">=</span> <span class="mi">3</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span><span class="s2">&quot;Ensemble FTS&quot;</span>
@ -421,7 +409,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
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<input type="submit" value="Go" />
</form>
</div>
@ -440,14 +428,14 @@
<li class="right" >
<a href="../../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.ensemble.ensemble</a></li>
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</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
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<meta name="viewport" content="width=device-width, initial-scale=1.0"><script type="text/javascript">
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<title>pyFTS.models.ensemble.multiseasonal &#8212; pyFTS 1.6 documentation</title>
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<title>pyFTS.models.ensemble.multiseasonal &#8212; pyFTS 1.7 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-this"><a href="">pyFTS.models.ensemble.multiseasonal</a></li>
</ul>
@ -61,12 +49,12 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">Util</span> <span class="k">as</span> <span class="n">cUtil</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.ensemble</span> <span class="kn">import</span> <span class="n">ensemble</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.seasonal</span> <span class="kn">import</span> <span class="n">cmsfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="kn">import</span> <span class="n">ProbabilityDistribution</span>
<span class="kn">from</span> <span class="nn">copy</span> <span class="kn">import</span> <span class="n">deepcopy</span>
<span class="kn">from</span> <span class="nn">joblib</span> <span class="kn">import</span> <span class="n">Parallel</span><span class="p">,</span> <span class="n">delayed</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Util</span> <span class="k">as</span> <span class="n">cUtil</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.ensemble</span> <span class="k">import</span> <span class="n">ensemble</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.seasonal</span> <span class="k">import</span> <span class="n">cmsfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">ProbabilityDistribution</span>
<span class="kn">from</span> <span class="nn">copy</span> <span class="k">import</span> <span class="n">deepcopy</span>
<span class="kn">from</span> <span class="nn">joblib</span> <span class="k">import</span> <span class="n">Parallel</span><span class="p">,</span> <span class="n">delayed</span>
<span class="kn">import</span> <span class="nn">multiprocessing</span>
@ -87,7 +75,7 @@
<div class="viewcode-block" id="SeasonalEnsembleFTS"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS">[docs]</a><span class="k">class</span> <span class="nc">SeasonalEnsembleFTS</span><span class="p">(</span><span class="n">ensemble</span><span class="o">.</span><span class="n">EnsembleFTS</span><span class="p">):</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">SeasonalEnsembleFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;Seasonal Ensemble FTS&quot;</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">min_order</span> <span class="o">=</span> <span class="mi">1</span>
<span class="bp">self</span><span class="o">.</span><span class="n">indexers</span> <span class="o">=</span> <span class="p">[]</span>
@ -160,7 +148,7 @@
<h3 id="searchlabel">Quick search</h3>
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<title>pyFTS.models.hofts &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
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@ -63,13 +51,13 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="kn">import</span> <span class="n">product</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="k">import</span> <span class="n">product</span>
<div class="viewcode-block" id="HighOrderFLRG"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.HighOrderFLRG">[docs]</a><span class="k">class</span> <span class="nc">HighOrderFLRG</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Conventional High Order Fuzzy Logical Relationship Group&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">HighOrderFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="p">[]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">{}</span>
@ -86,7 +74,7 @@
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">c</span><span class="p">)</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
@ -95,14 +83,14 @@
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="o">+</span> <span class="s2">&quot; -&gt; &quot;</span> <span class="o">+</span> <span class="n">tmp</span>
<span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
<div class="viewcode-block" id="WeightedHighOrderFLRG"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFLRG">[docs]</a><span class="k">class</span> <span class="nc">WeightedHighOrderFLRG</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Weighted High Order Fuzzy Logical Relationship Group&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">WeightedHighOrderFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="p">[]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">{}</span>
@ -145,7 +133,7 @@
<span class="bp">self</span><span class="o">.</span><span class="n">upper</span> <span class="o">=</span> <span class="n">up</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">weights</span><span class="p">())</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">upper</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">_str</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
<span class="n">_str</span> <span class="o">+=</span> <span class="s2">&quot;, &quot;</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">_str</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="k">else</span> <span class="s2">&quot;&quot;</span>
@ -153,13 +141,13 @@
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="o">+</span> <span class="s2">&quot; -&gt; &quot;</span> <span class="o">+</span> <span class="n">_str</span>
<span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
<div class="viewcode-block" id="HighOrderFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.HighOrderFTS">[docs]</a><span class="k">class</span> <span class="nc">HighOrderFTS</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Conventional High Order Fuzzy Time Series&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">HighOrderFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;High Order FTS&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">&quot;HOFTS&quot;</span>
@ -223,7 +211,7 @@
<span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
<span class="n">rhs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">fuzzyfy</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">k</span><span class="o">+</span><span class="n">_tmp_steps</span><span class="p">],</span> <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;sets&quot;</span><span class="p">,</span> <span class="n">alpha_cut</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">alpha_cut</span><span class="p">)</span>
<span class="n">rhs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">fuzzyfy</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">k</span> <span class="o">+</span> <span class="n">_tmp_steps</span><span class="p">],</span> <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;sets&quot;</span><span class="p">,</span> <span class="n">alpha_cut</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">alpha_cut</span><span class="p">)</span>
<span class="n">flrgs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrg</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
@ -238,12 +226,12 @@
<div class="viewcode-block" id="HighOrderFTS.generate_flrg_fuzzyfied"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.HighOrderFTS.generate_flrg_fuzzyfied">[docs]</a> <span class="k">def</span> <span class="nf">generate_flrg_fuzzyfied</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
<span class="n">_tmp_steps</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">standard_horizon</span> <span class="o">-</span> <span class="mi">1</span>
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="n">l</span> <span class="o">-</span> <span class="n">_tmp_steps</span><span class="p">):</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dump</span><span class="p">:</span> <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;FLR: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">k</span><span class="p">))</span>
<span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
<span class="n">rhs</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span><span class="o">+</span><span class="n">_tmp_steps</span><span class="p">]</span>
<span class="n">rhs</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span> <span class="o">+</span> <span class="n">_tmp_steps</span><span class="p">]</span>
<span class="n">flrgs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrg_fuzzyfied</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
@ -326,7 +314,7 @@
<div class="viewcode-block" id="WeightedHighOrderFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFTS">[docs]</a><span class="k">class</span> <span class="nc">WeightedHighOrderFTS</span><span class="p">(</span><span class="n">HighOrderFTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Weighted High Order Fuzzy Time Series&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">WeightedHighOrderFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Weighted High Order FTS&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">&quot;WHOFTS&quot;</span>
@ -363,7 +351,7 @@
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@ -382,14 +370,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
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<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
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&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
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@ -5,31 +5,19 @@
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.hwang</a></li>
</ul>
@ -63,11 +51,11 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">Transformations</span><span class="p">,</span> <span class="n">fts</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span>
<div class="viewcode-block" id="HighOrderFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hwang.HighOrderFTS">[docs]</a><span class="k">class</span> <span class="nc">HighOrderFTS</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">HighOrderFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="kc">True</span>
<span class="bp">self</span><span class="o">.</span><span class="n">min_order</span> <span class="o">=</span> <span class="mi">2</span>
@ -84,7 +72,7 @@
<div class="viewcode-block" id="HighOrderFTS.forecast"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hwang.HighOrderFTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="p">)</span>
<span class="n">cn</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mf">0.0</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">l</span><span class="p">)])</span>
<span class="n">ow</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="mf">0.0</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">l</span><span class="p">)]</span> <span class="k">for</span> <span class="n">z</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)])</span>
@ -97,9 +85,9 @@
<span class="k">for</span> <span class="n">ix</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">l</span><span class="p">):</span>
<span class="n">s</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
<span class="n">cn</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">grant_bounds</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">t</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">))</span>
<span class="n">cn</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">grant_bounds</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">t</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">))</span>
<span class="k">for</span> <span class="n">w</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="o">-</span><span class="mi">1</span><span class="p">):</span>
<span class="n">ow</span><span class="p">[</span><span class="n">w</span><span class="p">,</span> <span class="n">ix</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">FuzzySet</span><span class="o">.</span><span class="n">grant_bounds</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">t</span> <span class="o">-</span> <span class="n">w</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">))</span>
<span class="n">ow</span><span class="p">[</span><span class="n">w</span><span class="p">,</span> <span class="n">ix</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">FuzzySet</span><span class="o">.</span><span class="n">grant_bounds</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">t</span> <span class="o">-</span> <span class="n">w</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">))</span>
<span class="n">rn</span><span class="p">[</span><span class="n">w</span><span class="p">,</span> <span class="n">ix</span><span class="p">]</span> <span class="o">=</span> <span class="n">ow</span><span class="p">[</span><span class="n">w</span><span class="p">,</span> <span class="n">ix</span><span class="p">]</span> <span class="o">*</span> <span class="n">cn</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
<span class="n">ft</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">ft</span><span class="p">[</span><span class="n">ix</span><span class="p">],</span> <span class="n">rn</span><span class="p">[</span><span class="n">w</span><span class="p">,</span> <span class="n">ix</span><span class="p">])</span>
<span class="n">mft</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">ft</span><span class="p">)</span>
@ -108,17 +96,13 @@
<span class="k">for</span> <span class="n">ix</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">l</span><span class="p">):</span>
<span class="n">s</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
<span class="k">if</span> <span class="n">ft</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span> <span class="o">==</span> <span class="n">mft</span><span class="p">:</span>
<span class="n">out</span> <span class="o">=</span> <span class="n">out</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span>
<span class="n">out</span> <span class="o">=</span> <span class="n">out</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span>
<span class="n">count</span> <span class="o">+=</span> <span class="mf">1.0</span>
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">out</span> <span class="o">/</span> <span class="n">count</span><span class="p">)</span>
<span class="k">return</span> <span class="n">ret</span></div>
<div class="viewcode-block" id="HighOrderFTS.train"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hwang.HighOrderFTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">==</span> <span class="kc">None</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span>
<span class="bp">self</span><span class="o">.</span><span class="n">configure_lags</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div></div>
</pre></div>
@ -132,7 +116,7 @@
<h3 id="searchlabel">Quick search</h3>
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<input type="submit" value="Go" />
</form>
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@ -151,14 +135,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.hwang</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

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@ -5,31 +5,19 @@
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<title>pyFTS.models.ifts &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.ifts</a></li>
</ul>
@ -66,15 +54,15 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">tree</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">hofts</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">tree</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span>
<div class="viewcode-block" id="IntervalFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ifts.IntervalFTS">[docs]</a><span class="k">class</span> <span class="nc">IntervalFTS</span><span class="p">(</span><span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> High Order Interval Fuzzy Time Series</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">IntervalFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">&quot;IFTS&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Interval FTS&quot;</span>
@ -160,7 +148,7 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Weighted High Order Interval Fuzzy Time Series</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">WeightedIntervalFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">&quot;WIFTS&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Weighted Interval FTS&quot;</span>
@ -253,7 +241,7 @@
<h3 id="searchlabel">Quick search</h3>
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<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
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<input type="submit" value="Go" />
</form>
</div>
@ -272,14 +260,14 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.ifts</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
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</html>

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@ -5,31 +5,19 @@
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<title>pyFTS.models.incremental.IncrementalEnsemble &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.incremental.IncrementalEnsemble</a></li>
</ul>
@ -62,17 +50,17 @@
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">hofts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.ensemble</span> <span class="kn">import</span> <span class="n">ensemble</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.ensemble</span> <span class="k">import</span> <span class="n">ensemble</span>
<div class="viewcode-block" id="IncrementalEnsembleFTS"><a class="viewcode-back" href="../../../../pyFTS.models.incremental.html#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS">[docs]</a><span class="k">class</span> <span class="nc">IncrementalEnsembleFTS</span><span class="p">(</span><span class="n">ensemble</span><span class="o">.</span><span class="n">EnsembleFTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Time Variant/Incremental Ensemble of FTS methods</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">IncrementalEnsembleFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">&quot;IncrementalEnsembleFTS&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Incremental Ensemble FTS&quot;</span>
@ -192,7 +180,7 @@
<h3 id="searchlabel">Quick search</h3>
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<form class="search" action="../../../../search.html" method="get">
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<input type="submit" value="Go" />
</form>
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@ -211,14 +199,14 @@
<li class="right" >
<a href="../../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.incremental.IncrementalEnsemble</a></li>
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<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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@ -5,31 +5,19 @@
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<title>pyFTS.models.incremental.TimeVariant &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.incremental.TimeVariant</a></li>
</ul>
@ -61,8 +49,8 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span>
<div class="viewcode-block" id="Retrainer"><a class="viewcode-back" href="../../../../pyFTS.models.incremental.html#pyFTS.models.incremental.TimeVariant.Retrainer">[docs]</a><span class="k">class</span> <span class="nc">Retrainer</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
@ -71,7 +59,7 @@
<span class="sd"> data windows controlled by the parameter &#39;batch_size&#39;, using as the training data a</span>
<span class="sd"> window of recent lags, whose size is controlled by the parameter &#39;window_length&#39;.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">Retrainer</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">partitioner_method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;partitioner_method&#39;</span><span class="p">,</span> <span class="n">Grid</span><span class="o">.</span><span class="n">GridPartitioner</span><span class="p">)</span>
@ -159,12 +147,12 @@
<div class="viewcode-block" id="Retrainer.offset"><a class="viewcode-back" href="../../../../pyFTS.models.incremental.html#pyFTS.models.incremental.TimeVariant.Retrainer.offset">[docs]</a> <span class="k">def</span> <span class="nf">offset</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;String representation of the model&quot;&quot;&quot;</span>
<span class="k">return</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> The length (number of rules) of the model</span>
@ -183,7 +171,7 @@
<h3 id="searchlabel">Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../../search.html" method="get">
<input type="text" name="q" aria-labelledby="searchlabel" />
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<input type="submit" value="Go" />
</form>
</div>
@ -202,14 +190,14 @@
<li class="right" >
<a href="../../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.incremental.TimeVariant</a></li>
</ul>
</div>
<div class="footer" role="contentinfo">
&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
</html>

View File

@ -5,31 +5,19 @@
<html>
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var _gaq = _gaq || [];
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_gaq.push(['_trackPageview']);
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ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
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<title>pyFTS.models.ismailefendi &#8212; pyFTS 1.6 documentation</title>
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<title>pyFTS.models.ismailefendi &#8212; pyFTS 1.7 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.ismailefendi</a></li>
</ul>
@ -63,12 +51,12 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span>
<div class="viewcode-block" id="ImprovedWeightedFLRG"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ismailefendi.ImprovedWeightedFLRG">[docs]</a><span class="k">class</span> <span class="nc">ImprovedWeightedFLRG</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;First Order Improved Weighted Fuzzy Logical Relationship Group&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">ImprovedWeightedFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="n">LHS</span>
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">{}</span>
@ -90,7 +78,7 @@
<span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">rhs_counts</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()])</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">w</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">+</span> <span class="s2">&quot; -&gt; &quot;</span>
<span class="n">tmp2</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()):</span>
@ -99,13 +87,13 @@
<span class="n">tmp2</span> <span class="o">=</span> <span class="n">tmp2</span> <span class="o">+</span> <span class="n">c</span> <span class="o">+</span> <span class="s2">&quot;(&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">rhs_counts</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">count</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span> <span class="o">+</span> <span class="s2">&quot;)&quot;</span>
<span class="k">return</span> <span class="n">tmp</span> <span class="o">+</span> <span class="n">tmp2</span>
<span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
<div class="viewcode-block" id="ImprovedWeightedFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ismailefendi.ImprovedWeightedFTS">[docs]</a><span class="k">class</span> <span class="nc">ImprovedWeightedFTS</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;First Order Improved Weighted Fuzzy Time Series&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">ImprovedWeightedFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;IWFTS&quot;</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Improved Weighted FTS&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">&quot;Ismail &amp; Efendi&quot;</span>
@ -179,7 +167,7 @@
<h3 id="searchlabel">Quick search</h3>
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@ -198,14 +186,14 @@
<li class="right" >
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<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.ismailefendi</a></li>
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
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<title>pyFTS.models.multivariate.FLR &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
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@ -60,7 +48,7 @@
<div class="viewcode-block" id="FLR"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.FLR.FLR">[docs]</a><span class="k">class</span> <span class="nc">FLR</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Multivariate Fuzzy Logical Relationship&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Creates a Fuzzy Logical Relationship</span>
<span class="sd"> :param LHS: Left Hand Side fuzzy set</span>
@ -75,7 +63,7 @@
<div class="viewcode-block" id="FLR.set_rhs"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.FLR.FLR.set_rhs">[docs]</a> <span class="k">def</span> <span class="nf">set_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="nb">set</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="nb">set</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="s2">&quot;</span><span class="si">{}</span><span class="s2"> -&gt; </span><span class="si">{}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">([</span><span class="n">k</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">values</span><span class="p">()],</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
@ -92,7 +80,7 @@
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@ -111,14 +99,14 @@
<li class="right" >
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<li class="nav-item nav-item-1"><a href="../../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.multivariate.FLR</a></li>
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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@ -5,31 +5,19 @@
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<title>pyFTS.models.multivariate.cmvfts &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
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<li class="nav-item nav-item-1"><a href="../../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.multivariate.cmvfts</a></li>
</ul>
@ -58,17 +46,17 @@
<span></span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">hofts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="kn">import</span> <span class="n">mvfts</span><span class="p">,</span> <span class="n">grid</span><span class="p">,</span> <span class="n">common</span>
<span class="kn">from</span> <span class="nn">types</span> <span class="kn">import</span> <span class="n">LambdaType</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="k">import</span> <span class="n">mvfts</span><span class="p">,</span> <span class="n">grid</span><span class="p">,</span> <span class="n">common</span>
<span class="kn">from</span> <span class="nn">types</span> <span class="k">import</span> <span class="n">LambdaType</span>
<div class="viewcode-block" id="ClusteredMVFTS"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS">[docs]</a><span class="k">class</span> <span class="nc">ClusteredMVFTS</span><span class="p">(</span><span class="n">mvfts</span><span class="o">.</span><span class="n">MVFTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Meta model for high order, clustered multivariate FTS</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">ClusteredMVFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">fts_method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;fts_method&#39;</span><span class="p">,</span> <span class="n">hofts</span><span class="o">.</span><span class="n">WeightedHighOrderFTS</span><span class="p">)</span>
@ -260,11 +248,11 @@
<span class="k">return</span> <span class="n">ret</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;String representation of the model&quot;&quot;&quot;</span>
<span class="k">return</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">)</span>
<span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> The length (number of rules) of the model</span>
@ -284,7 +272,7 @@
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@ -303,14 +291,14 @@
<li class="right" >
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<li class="nav-item nav-item-1"><a href="../../../index.html" >Module code</a> &#187;</li>
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
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@ -5,31 +5,19 @@
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<title>pyFTS.models.multivariate.common &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
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>modules</a> |</li>
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</ul>
@ -57,14 +45,14 @@
<h1>Source code for pyFTS.models.multivariate.common</h1><div class="highlight"><pre>
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">Composite</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">Composite</span>
<div class="viewcode-block" id="MultivariateFuzzySet"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.common.MultivariateFuzzySet">[docs]</a><span class="k">class</span> <span class="nc">MultivariateFuzzySet</span><span class="p">(</span><span class="n">Composite</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Multivariate Composite Fuzzy Set</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Create an empty composite fuzzy set</span>
<span class="sd"> :param name: fuzzy set name</span>
@ -144,7 +132,7 @@
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@ -57,7 +45,7 @@
<h1>Source code for pyFTS.models.multivariate.flrg</h1><div class="highlight"><pre>
<span></span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">flrg</span> <span class="k">as</span> <span class="n">flg</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">flrg</span> <span class="k">as</span> <span class="n">flg</span>
<div class="viewcode-block" id="FLRG"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.flrg.FLRG">[docs]</a><span class="k">class</span> <span class="nc">FLRG</span><span class="p">(</span><span class="n">flg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">):</span>
@ -65,7 +53,7 @@
<span class="sd"> Multivariate Fuzzy Logical Rule Group</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">FLRG</span><span class="p">,</span><span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;order&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;lhs&#39;</span><span class="p">,</span> <span class="p">{})</span>
@ -102,7 +90,7 @@
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">upper</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">_str</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">:</span>
<span class="n">_str</span> <span class="o">+=</span> <span class="s2">&quot;,&quot;</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">_str</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="k">else</span> <span class="s2">&quot;&quot;</span>
@ -121,7 +109,7 @@
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@ -55,8 +43,8 @@
<div class="body" role="main">
<h1>Source code for pyFTS.models.multivariate.granular</h1><div class="highlight"><pre>
<span></span><span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="kn">import</span> <span class="n">cmvfts</span><span class="p">,</span> <span class="n">grid</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">hofts</span>
<span></span><span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="k">import</span> <span class="n">cmvfts</span><span class="p">,</span> <span class="n">grid</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span>
<div class="viewcode-block" id="GranularWMVFTS"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.granular.GranularWMVFTS">[docs]</a><span class="k">class</span> <span class="nc">GranularWMVFTS</span><span class="p">(</span><span class="n">cmvfts</span><span class="o">.</span><span class="n">ClusteredMVFTS</span><span class="p">):</span>
@ -64,7 +52,7 @@
<span class="sd"> Granular multivariate weighted high order FTS</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">GranularWMVFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">fts_method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;fts_method&#39;</span><span class="p">,</span> <span class="n">hofts</span><span class="o">.</span><span class="n">WeightedHighOrderFTS</span><span class="p">)</span>
@ -95,7 +83,7 @@
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@ -43,7 +31,7 @@
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@ -55,10 +43,10 @@
<div class="body" role="main">
<h1>Source code for pyFTS.models.multivariate.grid</h1><div class="highlight"><pre>
<span></span><span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="kn">import</span> <span class="n">partitioner</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate.common</span> <span class="kn">import</span> <span class="n">MultivariateFuzzySet</span><span class="p">,</span> <span class="n">fuzzyfy_instance_clustered</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="kn">import</span> <span class="n">product</span>
<span class="kn">from</span> <span class="nn">scipy.spatial</span> <span class="kn">import</span> <span class="n">KDTree</span>
<span></span><span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="k">import</span> <span class="n">partitioner</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate.common</span> <span class="k">import</span> <span class="n">MultivariateFuzzySet</span><span class="p">,</span> <span class="n">fuzzyfy_instance_clustered</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="k">import</span> <span class="n">product</span>
<span class="kn">from</span> <span class="nn">scipy.spatial</span> <span class="k">import</span> <span class="n">KDTree</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
@ -68,7 +56,7 @@
<span class="sd"> A cartesian product of all fuzzy sets of all variables</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">GridCluster</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;GridCluster&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">build</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
@ -123,7 +111,7 @@
<span class="sd"> multivariate fuzzy set base.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">IncrementalGridCluster</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;IncrementalGridCluster&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">build</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
@ -205,7 +193,7 @@
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@ -224,14 +212,14 @@
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@ -43,7 +31,7 @@
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@ -55,12 +43,12 @@
<div class="body" role="main">
<h1>Source code for pyFTS.models.multivariate.mvfts</h1><div class="highlight"><pre>
<span></span><span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">fts</span><span class="p">,</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">Membership</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="kn">import</span> <span class="n">FLR</span> <span class="k">as</span> <span class="n">MVFLR</span><span class="p">,</span> <span class="n">common</span><span class="p">,</span> <span class="n">flrg</span> <span class="k">as</span> <span class="n">mvflrg</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="kn">import</span> <span class="n">product</span>
<span class="kn">from</span> <span class="nn">types</span> <span class="kn">import</span> <span class="n">LambdaType</span>
<span class="kn">from</span> <span class="nn">copy</span> <span class="kn">import</span> <span class="n">deepcopy</span>
<span></span><span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">fts</span><span class="p">,</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">Membership</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="k">import</span> <span class="n">FLR</span> <span class="k">as</span> <span class="n">MVFLR</span><span class="p">,</span> <span class="n">common</span><span class="p">,</span> <span class="n">flrg</span> <span class="k">as</span> <span class="n">mvflrg</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="k">import</span> <span class="n">product</span>
<span class="kn">from</span> <span class="nn">types</span> <span class="k">import</span> <span class="n">LambdaType</span>
<span class="kn">from</span> <span class="nn">copy</span> <span class="k">import</span> <span class="n">deepcopy</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
@ -82,7 +70,7 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Multivariate extension of Chen&#39;s ConventionalFTS method</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">MVFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">explanatory_variables</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;explanatory_variables&#39;</span><span class="p">,[])</span>
<span class="bp">self</span><span class="o">.</span><span class="n">target_variable</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;target_variable&#39;</span><span class="p">,</span><span class="kc">None</span><span class="p">)</span>
@ -375,7 +363,7 @@
<span class="bp">self</span><span class="o">.</span><span class="n">explanatory_variables</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">explanatory_variables</span>
<span class="bp">self</span><span class="o">.</span><span class="n">target_variable</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">target_variable</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">_str</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">+</span> <span class="s2">&quot;:</span><span class="se">\n</span><span class="s2">&quot;</span>
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
<span class="n">_str</span> <span class="o">+=</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">k</span><span class="p">])</span> <span class="o">+</span> <span class="s2">&quot;</span><span class="se">\n</span><span class="s2">&quot;</span>
@ -395,7 +383,7 @@
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@ -55,10 +43,10 @@
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<h1>Source code for pyFTS.models.multivariate.partitioner</h1><div class="highlight"><pre>
<span></span><span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">partitioner</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate.common</span> <span class="kn">import</span> <span class="n">MultivariateFuzzySet</span><span class="p">,</span> <span class="n">fuzzyfy_instance_clustered</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="kn">import</span> <span class="n">product</span>
<span class="kn">from</span> <span class="nn">scipy.spatial</span> <span class="kn">import</span> <span class="n">KDTree</span>
<span></span><span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">partitioner</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate.common</span> <span class="k">import</span> <span class="n">MultivariateFuzzySet</span><span class="p">,</span> <span class="n">fuzzyfy_instance_clustered</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="k">import</span> <span class="n">product</span>
<span class="kn">from</span> <span class="nn">scipy.spatial</span> <span class="k">import</span> <span class="n">KDTree</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
@ -68,7 +56,7 @@
<span class="sd"> Base class for partitioners which use the MultivariateFuzzySet</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">MultivariatePartitioner</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">&quot;MultivariatePartitioner&quot;</span><span class="p">,</span> <span class="n">preprocess</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">=</span> <span class="s1">&#39;multivariate&#39;</span>
@ -187,7 +175,7 @@
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@ -56,9 +44,9 @@
<h1>Source code for pyFTS.models.multivariate.variable</h1><div class="highlight"><pre>
<span></span><span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">fts</span><span class="p">,</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">tree</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="kn">import</span> <span class="n">FLR</span> <span class="k">as</span> <span class="n">MVFLR</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">fts</span><span class="p">,</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">tree</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="k">import</span> <span class="n">FLR</span> <span class="k">as</span> <span class="n">MVFLR</span>
<div class="viewcode-block" id="Variable"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.variable.Variable">[docs]</a><span class="k">class</span> <span class="nc">Variable</span><span class="p">:</span>
@ -66,7 +54,7 @@
<span class="sd"> A variable of a fuzzy time series multivariate model. Each variable contains its own</span>
<span class="sd"> transformations and partitioners.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> :param name:</span>
@ -104,11 +92,11 @@
<span class="sd"> :param kwargs:</span>
<span class="sd"> :return:</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">fs</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;partitioner&#39;</span><span class="p">,</span> <span class="n">Grid</span><span class="o">.</span><span class="n">GridPartitioner</span><span class="p">)</span>
<span class="n">mf</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;func&#39;</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">)</span>
<span class="n">np</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;npart&#39;</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
<span class="n">fs</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">&#39;partitioner&#39;</span><span class="p">,</span> <span class="n">Grid</span><span class="o">.</span><span class="n">GridPartitioner</span><span class="p">)</span>
<span class="n">mf</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">&#39;func&#39;</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">)</span>
<span class="n">np</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">&#39;npart&#39;</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
<span class="n">data</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;data&#39;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="n">kw</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;partitioner_specific&#39;</span><span class="p">,</span> <span class="p">{})</span>
<span class="n">kw</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">&#39;partitioner_specific&#39;</span><span class="p">,</span> <span class="p">{})</span>
<span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span> <span class="o">=</span> <span class="n">fs</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">data_label</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">npart</span><span class="o">=</span><span class="n">np</span><span class="p">,</span> <span class="n">func</span><span class="o">=</span><span class="n">mf</span><span class="p">,</span>
<span class="n">transformation</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">transformation</span><span class="p">,</span> <span class="n">prefix</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">alias</span><span class="p">,</span>
<span class="n">variable</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="o">**</span><span class="n">kw</span><span class="p">)</span>
@ -135,7 +123,7 @@
<span class="k">return</span> <span class="n">data</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span></div>
</pre></div>
@ -149,7 +137,7 @@
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<title>pyFTS.models.multivariate.wmvfts &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
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@ -55,9 +43,9 @@
<div class="body" role="main">
<h1>Source code for pyFTS.models.multivariate.wmvfts</h1><div class="highlight"><pre>
<span></span><span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">fts</span><span class="p">,</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">tree</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="kn">import</span> <span class="n">mvfts</span><span class="p">,</span> <span class="n">FLR</span> <span class="k">as</span> <span class="n">MVFLR</span><span class="p">,</span> <span class="n">common</span><span class="p">,</span> <span class="n">flrg</span> <span class="k">as</span> <span class="n">mvflrg</span>
<span></span><span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">fts</span><span class="p">,</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">tree</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="k">import</span> <span class="n">mvfts</span><span class="p">,</span> <span class="n">FLR</span> <span class="k">as</span> <span class="n">MVFLR</span><span class="p">,</span> <span class="n">common</span><span class="p">,</span> <span class="n">flrg</span> <span class="k">as</span> <span class="n">mvflrg</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
@ -68,7 +56,7 @@
<span class="sd"> Weighted Multivariate Fuzzy Logical Rule Group</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">WeightedFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;order&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;lhs&#39;</span><span class="p">,</span> <span class="p">{})</span>
@ -108,7 +96,7 @@
<span class="bp">self</span><span class="o">.</span><span class="n">upper</span> <span class="o">=</span> <span class="n">up</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">weights</span><span class="p">())</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">upper</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">_str</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
<span class="n">_str</span> <span class="o">+=</span> <span class="s2">&quot;, &quot;</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">_str</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="k">else</span> <span class="s2">&quot;&quot;</span>
@ -121,7 +109,7 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Weighted Multivariate FTS</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">WeightedMVFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">&quot;WeightedMVFTS&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Weighted Multivariate FTS&quot;</span>
@ -146,7 +134,7 @@
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@ -165,14 +153,14 @@
<li class="right" >
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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@ -5,31 +5,19 @@
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<title>pyFTS.models.nonstationary.common &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
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@ -63,10 +51,10 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="kn">import</span> <span class="o">*</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span> <span class="k">as</span> <span class="n">FS</span><span class="p">,</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">FLR</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">partitioner</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="kn">import</span> <span class="n">perturbation</span>
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="k">import</span> <span class="o">*</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span> <span class="k">as</span> <span class="n">FS</span><span class="p">,</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">FLR</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">partitioner</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="k">import</span> <span class="n">perturbation</span>
<div class="viewcode-block" id="FuzzySet"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.common.FuzzySet">[docs]</a><span class="k">class</span> <span class="nc">FuzzySet</span><span class="p">(</span><span class="n">FS</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">):</span>
@ -74,7 +62,7 @@
<span class="sd"> Non Stationary Fuzzy Sets</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">mf</span><span class="p">,</span> <span class="n">parameters</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">mf</span><span class="p">,</span> <span class="n">parameters</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Constructor</span>
<span class="sd"> &quot;&quot;&quot;</span>
@ -229,7 +217,7 @@
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">param</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">location</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">tmp</span> <span class="o">+=</span> <span class="s2">&quot;Location: &quot;</span>
@ -309,7 +297,7 @@
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@ -328,14 +316,14 @@
<li class="right" >
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<title>pyFTS.models.nonstationary.cvfts &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
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</ul>
@ -56,14 +44,14 @@
<h1>Source code for pyFTS.models.nonstationary.cvfts</h1><div class="highlight"><pre>
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">hofts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="kn">import</span> <span class="n">common</span><span class="p">,</span><span class="n">nsfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">flrg</span><span class="p">,</span> <span class="n">tree</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="k">import</span> <span class="n">common</span><span class="p">,</span><span class="n">nsfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">flrg</span><span class="p">,</span> <span class="n">tree</span>
<div class="viewcode-block" id="HighOrderNonstationaryFLRG"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.HighOrderNonstationaryFLRG">[docs]</a><span class="k">class</span> <span class="nc">HighOrderNonstationaryFLRG</span><span class="p">(</span><span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Conventional High Order Fuzzy Logical Relationship Group&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">HighOrderNonstationaryFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="p">[]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">{}</span>
@ -76,7 +64,7 @@
<div class="viewcode-block" id="HighOrderNonstationaryFLRG.append_lhs"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.HighOrderNonstationaryFLRG.append_lhs">[docs]</a> <span class="k">def</span> <span class="nf">append_lhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">c</span><span class="p">)</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">):</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
@ -85,12 +73,12 @@
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="o">+</span> <span class="s2">&quot; -&gt; &quot;</span> <span class="o">+</span> <span class="n">tmp</span>
<span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
<div class="viewcode-block" id="ConditionalVarianceFTS"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS">[docs]</a><span class="k">class</span> <span class="nc">ConditionalVarianceFTS</span><span class="p">(</span><span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">):</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">ConditionalVarianceFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Conditional Variance FTS&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">&quot;CVFTS &quot;</span>
@ -339,7 +327,7 @@
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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</ul>
@ -56,8 +44,8 @@
<h1>Source code for pyFTS.models.nonstationary.flrg</h1><div class="highlight"><pre>
<span></span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">flrg</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="kn">import</span> <span class="n">common</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">flrg</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="k">import</span> <span class="n">common</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
@ -75,7 +63,7 @@
<span class="k">return</span> <span class="p">(</span><span class="n">sets</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">w</span><span class="p">)</span></div>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">NonStationaryFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="n">LHS</span>
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span>
@ -140,7 +128,7 @@
<h3 id="searchlabel">Quick search</h3>
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<form class="search" action="../../../../search.html" method="get">
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<input type="submit" value="Go" />
</form>
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@ -159,14 +147,14 @@
<li class="right" >
<a href="../../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.nonstationary.flrg</a></li>
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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@ -5,31 +5,19 @@
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<title>pyFTS.models.nonstationary.honsfts &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
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>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.nonstationary.honsfts</a></li>
</ul>
@ -56,15 +44,15 @@
<h1>Source code for pyFTS.models.nonstationary.honsfts</h1><div class="highlight"><pre>
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">hofts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="kn">import</span> <span class="n">common</span><span class="p">,</span> <span class="n">flrg</span><span class="p">,</span> <span class="n">nsfts</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="kn">import</span> <span class="n">product</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="k">import</span> <span class="n">common</span><span class="p">,</span> <span class="n">flrg</span><span class="p">,</span> <span class="n">nsfts</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="k">import</span> <span class="n">product</span>
<div class="viewcode-block" id="HighOrderNonStationaryFLRG"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.honsfts.HighOrderNonStationaryFLRG">[docs]</a><span class="k">class</span> <span class="nc">HighOrderNonStationaryFLRG</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">NonStationaryFLRG</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;First Order NonStationary Fuzzy Logical Relationship Group&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">HighOrderNonStationaryFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="p">[]</span>
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">{}</span>
@ -103,7 +91,7 @@
<span class="n">upper</span> <span class="o">=</span> <span class="n">up</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">weights</span><span class="p">())</span>
<span class="k">return</span> <span class="n">upper</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">_str</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
<span class="n">_str</span> <span class="o">+=</span> <span class="s2">&quot;, &quot;</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">_str</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="k">else</span> <span class="s2">&quot;&quot;</span>
@ -111,13 +99,13 @@
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="o">+</span> <span class="s2">&quot; -&gt; &quot;</span> <span class="o">+</span> <span class="n">_str</span>
<span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
<div class="viewcode-block" id="HighOrderNonStationaryFTS"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.honsfts.HighOrderNonStationaryFTS">[docs]</a><span class="k">class</span> <span class="nc">HighOrderNonStationaryFTS</span><span class="p">(</span><span class="n">nsfts</span><span class="o">.</span><span class="n">NonStationaryFTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;NonStationaryFTS Fuzzy Time Series&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">HighOrderNonStationaryFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;High Order Non Stationary FTS&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">&quot;HONSFTS&quot;</span>
@ -308,7 +296,7 @@
<span class="k">return</span> <span class="n">ret</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">+</span> <span class="s2">&quot;:</span><span class="se">\n</span><span class="s2">&quot;</span>
<span class="k">for</span> <span class="n">r</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="s2">&quot;</span><span class="si">{0}{1}</span><span class="se">\n</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">tmp</span><span class="p">,</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">r</span><span class="p">]))</span>
@ -325,7 +313,7 @@
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<title>pyFTS.models.nonstationary.nsfts &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
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<li class="nav-item nav-item-1"><a href="../../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.nonstationary.nsfts</a></li>
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@ -56,14 +44,14 @@
<h1>Source code for pyFTS.models.nonstationary.nsfts</h1><div class="highlight"><pre>
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="kn">import</span> <span class="n">common</span><span class="p">,</span> <span class="n">flrg</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="k">import</span> <span class="n">common</span><span class="p">,</span> <span class="n">flrg</span>
<div class="viewcode-block" id="ConventionalNonStationaryFLRG"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.nsfts.ConventionalNonStationaryFLRG">[docs]</a><span class="k">class</span> <span class="nc">ConventionalNonStationaryFLRG</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">NonStationaryFLRG</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;First Order NonStationary Fuzzy Logical Relationship Group&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">ConventionalNonStationaryFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="n">LHS</span>
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span>
@ -74,7 +62,7 @@
<div class="viewcode-block" id="ConventionalNonStationaryFLRG.append_rhs"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.nsfts.ConventionalNonStationaryFLRG.append_rhs">[docs]</a> <span class="k">def</span> <span class="nf">append_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">c</span><span class="p">)</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">+</span> <span class="s2">&quot; -&gt; &quot;</span>
<span class="n">tmp2</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">):</span>
@ -87,7 +75,7 @@
<div class="viewcode-block" id="WeightedNonStationaryFLRG"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.nsfts.WeightedNonStationaryFLRG">[docs]</a><span class="k">class</span> <span class="nc">WeightedNonStationaryFLRG</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">NonStationaryFLRG</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;First Order NonStationary Fuzzy Logical Relationship Group&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">WeightedNonStationaryFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="n">LHS</span>
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">{}</span>
@ -115,7 +103,7 @@
<span class="n">midpoint</span> <span class="o">=</span> <span class="n">mp</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">weights</span><span class="p">())</span>
<span class="k">return</span> <span class="n">midpoint</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">_str</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
<span class="n">_str</span> <span class="o">+=</span> <span class="s2">&quot;, &quot;</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">_str</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="k">else</span> <span class="s2">&quot;&quot;</span>
@ -126,7 +114,7 @@
<div class="viewcode-block" id="NonStationaryFTS"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.nsfts.NonStationaryFTS">[docs]</a><span class="k">class</span> <span class="nc">NonStationaryFTS</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;NonStationaryFTS Fuzzy Time Series&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">NonStationaryFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Non Stationary FTS&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">&quot;NSFTS&quot;</span>
@ -367,7 +355,7 @@
<span class="k">return</span> <span class="n">ret</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">+</span> <span class="s2">&quot;:</span><span class="se">\n</span><span class="s2">&quot;</span>
<span class="k">for</span> <span class="n">r</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="s2">&quot;</span><span class="si">{0}{1}</span><span class="se">\n</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">tmp</span><span class="p">,</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">r</span><span class="p">]))</span>
@ -376,7 +364,7 @@
<div class="viewcode-block" id="WeightedNonStationaryFTS"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.nsfts.WeightedNonStationaryFTS">[docs]</a><span class="k">class</span> <span class="nc">WeightedNonStationaryFTS</span><span class="p">(</span><span class="n">NonStationaryFTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Weighted NonStationaryFTS Fuzzy Time Series&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">WeightedNonStationaryFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Weighted Non Stationary FTS&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">&quot;WNSFTS&quot;</span>
@ -426,7 +414,7 @@
<h3 id="searchlabel">Quick search</h3>
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@ -445,14 +433,14 @@
<li class="right" >
<a href="../../../../py-modindex.html" title="Python Module Index"
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<title>pyFTS.models.nonstationary.partitioners &#8212; pyFTS 1.6 documentation</title>
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@ -56,9 +44,9 @@
<h1>Source code for pyFTS.models.nonstationary.partitioners</h1><div class="highlight"><pre>
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">partitioner</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="kn">import</span> <span class="n">common</span><span class="p">,</span> <span class="n">perturbation</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span> <span class="k">as</span> <span class="n">stationary_fs</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">partitioner</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="k">import</span> <span class="n">common</span><span class="p">,</span> <span class="n">perturbation</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span> <span class="k">as</span> <span class="n">stationary_fs</span>
<div class="viewcode-block" id="PolynomialNonStationaryPartitioner"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.partitioners.PolynomialNonStationaryPartitioner">[docs]</a><span class="k">class</span> <span class="nc">PolynomialNonStationaryPartitioner</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="n">Partitioner</span><span class="p">):</span>
@ -66,7 +54,7 @@
<span class="sd"> Non Stationary Universe of Discourse Partitioner</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">part</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">part</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;&quot;&quot;&quot;</span>
<span class="nb">super</span><span class="p">(</span><span class="n">PolynomialNonStationaryPartitioner</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">,</span> <span class="n">npart</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">partitions</span><span class="p">,</span>
<span class="n">func</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">membership_function</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">setnames</span><span class="p">,</span>
@ -171,7 +159,7 @@
<span class="sd"> Non Stationary Universe of Discourse Partitioner</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">part</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">part</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;&quot;&quot;&quot;</span>
<span class="nb">super</span><span class="p">(</span><span class="n">SimpleNonStationaryPartitioner</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">,</span> <span class="n">npart</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">partitions</span><span class="p">,</span>
<span class="n">func</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">membership_function</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">setnames</span><span class="p">,</span>
@ -193,8 +181,8 @@
<div class="viewcode-block" id="simplenonstationary_gridpartitioner_builder"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.partitioners.simplenonstationary_gridpartitioner_builder">[docs]</a><span class="k">def</span> <span class="nf">simplenonstationary_gridpartitioner_builder</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">npart</span><span class="p">,</span> <span class="n">transformation</span><span class="p">):</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">Grid</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="kn">import</span> <span class="n">perturbation</span><span class="p">,</span> <span class="n">partitioners</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="k">import</span> <span class="n">perturbation</span><span class="p">,</span> <span class="n">partitioners</span>
<span class="n">tmp_fs</span> <span class="o">=</span> <span class="n">Grid</span><span class="o">.</span><span class="n">GridPartitioner</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">,</span> <span class="n">npart</span><span class="o">=</span><span class="n">npart</span><span class="p">,</span> <span class="n">transformation</span><span class="o">=</span><span class="n">transformation</span><span class="p">)</span>
<span class="n">fs</span> <span class="o">=</span> <span class="n">partitioners</span><span class="o">.</span><span class="n">SimpleNonStationaryPartitioner</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">tmp_fs</span><span class="p">,</span>
@ -217,7 +205,7 @@
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@ -236,14 +224,14 @@
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&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
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@ -43,7 +31,7 @@
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@ -60,8 +48,8 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="kn">import</span> <span class="o">*</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">Membership</span>
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="k">import</span> <span class="o">*</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">Membership</span>
<div class="viewcode-block" id="linear"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.perturbation.linear">[docs]</a><span class="k">def</span> <span class="nf">linear</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">parameters</span><span class="p">):</span>
@ -90,7 +78,7 @@
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@ -109,14 +97,14 @@
<li class="right" >
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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@ -43,7 +31,7 @@
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@ -60,7 +48,7 @@
<span class="kn">import</span> <span class="nn">matplotlib</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">import</span> <span class="nn">matplotlib.colors</span> <span class="k">as</span> <span class="nn">pltcolors</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">Util</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">Util</span>
<div class="viewcode-block" id="plot_sets"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.util.plot_sets">[docs]</a><span class="k">def</span> <span class="nf">plot_sets</span><span class="p">(</span><span class="n">partitioner</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">step</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">tam</span><span class="o">=</span><span class="p">[</span><span class="mi">5</span><span class="p">,</span> <span class="mi">5</span><span class="p">],</span> <span class="n">colors</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
@ -162,7 +150,7 @@
<h3 id="searchlabel">Quick search</h3>
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@ -181,14 +169,14 @@
<li class="right" >
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<li class="nav-item nav-item-0"><a href="../../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../../index.html" >Module code</a> &#187;</li>
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
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<title>pyFTS.models.pwfts &#8212; pyFTS 1.6 documentation</title>
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<title>pyFTS.models.pwfts &#8212; pyFTS 1.7 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.pwfts</a></li>
</ul>
@ -61,16 +49,16 @@
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">math</span>
<span class="kn">from</span> <span class="nn">operator</span> <span class="kn">import</span> <span class="n">itemgetter</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">FuzzySet</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">ifts</span>
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="kn">import</span> <span class="n">ProbabilityDistribution</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="kn">import</span> <span class="n">product</span>
<span class="kn">from</span> <span class="nn">operator</span> <span class="k">import</span> <span class="n">itemgetter</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">FuzzySet</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">ifts</span>
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">ProbabilityDistribution</span>
<span class="kn">from</span> <span class="nn">itertools</span> <span class="k">import</span> <span class="n">product</span>
<div class="viewcode-block" id="ProbabilisticWeightedFLRG"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFLRG">[docs]</a><span class="k">class</span> <span class="nc">ProbabilisticWeightedFLRG</span><span class="p">(</span><span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFLRG</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;High Order Probabilistic Weighted Fuzzy Logical Relationship Group&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">ProbabilisticWeightedFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">frequency_count</span> <span class="o">=</span> <span class="mf">0.0</span>
@ -149,7 +137,7 @@
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">lower</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">tmp2</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()):</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">tmp2</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
@ -160,7 +148,7 @@
<div class="viewcode-block" id="ProbabilisticWeightedFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS">[docs]</a><span class="k">class</span> <span class="nc">ProbabilisticWeightedFTS</span><span class="p">(</span><span class="n">ifts</span><span class="o">.</span><span class="n">IntervalFTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;High Order Probabilistic Weighted Fuzzy Time Series&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">ProbabilisticWeightedFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">&quot;PWFTS&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Probabilistic FTS&quot;</span>
@ -194,8 +182,9 @@
<span class="bp">self</span><span class="o">.</span><span class="n">generate_flrg_fuzzyfied</span><span class="p">(</span><span class="n">fuzz</span><span class="p">)</span></div>
<div class="viewcode-block" id="ProbabilisticWeightedFTS.generate_flrg_fuzzyfied"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_flrg_fuzzyfied">[docs]</a> <span class="k">def</span> <span class="nf">generate_flrg_fuzzyfied</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
<span class="n">_tmp_steps</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">standard_horizon</span> <span class="o">-</span> <span class="mi">1</span>
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="n">l</span> <span class="o">-</span> <span class="n">_tmp_steps</span><span class="p">):</span>
<span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
<span class="n">set_sample</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">instance</span> <span class="ow">in</span> <span class="n">sample</span><span class="p">:</span>
@ -211,8 +200,8 @@
<span class="n">lhs_mv</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">pwflrg_lhs_memberhip_fuzzyfied</span><span class="p">(</span><span class="n">flrg</span><span class="p">,</span> <span class="n">sample</span><span class="p">)</span>
<span class="n">mvs</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">inst</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span><span class="p">]</span>
<span class="k">for</span> <span class="nb">set</span><span class="p">,</span> <span class="n">mv</span> <span class="ow">in</span> <span class="n">inst</span><span class="p">:</span>
<span class="n">rhs</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span> <span class="o">+</span> <span class="n">_tmp_steps</span><span class="p">]</span>
<span class="k">for</span> <span class="nb">set</span><span class="p">,</span> <span class="n">mv</span> <span class="ow">in</span> <span class="n">rhs</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="nb">set</span><span class="p">,</span> <span class="n">count</span><span class="o">=</span><span class="n">lhs_mv</span> <span class="o">*</span> <span class="n">mv</span><span class="p">)</span>
<span class="n">mvs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mv</span><span class="p">)</span>
@ -260,8 +249,9 @@
<span class="k">return</span> <span class="n">flrgs</span></div>
<div class="viewcode-block" id="ProbabilisticWeightedFTS.generate_flrg"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_flrg">[docs]</a> <span class="k">def</span> <span class="nf">generate_flrg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
<span class="n">_tmp_steps</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">standard_horizon</span> <span class="o">-</span> <span class="mi">1</span>
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="n">l</span> <span class="o">-</span> <span class="n">_tmp_steps</span><span class="p">):</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dump</span><span class="p">:</span> <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;FLR: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">k</span><span class="p">))</span>
<span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
@ -275,7 +265,7 @@
<span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span> <span class="o">=</span> <span class="n">flrg</span><span class="p">;</span>
<span class="n">fuzzyfied</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">fuzzyfy</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="n">mode</span><span class="o">=</span><span class="s1">&#39;both&#39;</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s1">&#39;fuzzy&#39;</span><span class="p">,</span>
<span class="n">fuzzyfied</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">fuzzyfy</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">k</span><span class="o">+</span><span class="n">_tmp_steps</span><span class="p">],</span> <span class="n">mode</span><span class="o">=</span><span class="s1">&#39;both&#39;</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s1">&#39;fuzzy&#39;</span><span class="p">,</span>
<span class="n">alpha_cut</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">alpha_cut</span><span class="p">)</span>
<span class="n">mvs</span> <span class="o">=</span> <span class="p">[]</span>
@ -708,7 +698,7 @@
<span class="k">return</span> <span class="n">dist</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">+</span> <span class="s2">&quot;:</span><span class="se">\n</span><span class="s2">&quot;</span>
<span class="k">for</span> <span class="n">r</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="o">.</span><span class="n">keys</span><span class="p">()):</span>
<span class="n">p</span> <span class="o">=</span> <span class="nb">round</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">r</span><span class="p">]</span><span class="o">.</span><span class="n">frequency_count</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">global_frequency_count</span><span class="p">,</span> <span class="mi">3</span><span class="p">)</span>
@ -716,22 +706,29 @@
<span class="k">return</span> <span class="n">tmp</span></div>
<div class="viewcode-block" id="visualize_distributions"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.visualize_distributions">[docs]</a><span class="k">def</span> <span class="nf">visualize_distributions</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">from</span> <span class="nn">matplotlib</span> <span class="kn">import</span> <span class="n">gridspec</span>
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</span>
<div class="viewcode-block" id="highorder_fuzzy_markov_chain"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.highorder_fuzzy_markov_chain">[docs]</a><span class="k">def</span> <span class="nf">highorder_fuzzy_markov_chain</span><span class="p">(</span><span class="n">model</span><span class="p">):</span>
<span class="n">ordered_sets</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span>
<span class="n">ftpg_keys</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="o">.</span><span class="n">keys</span><span class="p">(),</span> <span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">x</span><span class="p">]</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">sets</span><span class="p">))</span>
<span class="n">lhs_probs</span> <span class="o">=</span> <span class="p">[</span><span class="n">model</span><span class="o">.</span><span class="n">flrg_lhs_unconditional_probability</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">k</span><span class="p">])</span>
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">ftpg_keys</span><span class="p">]</span>
<span class="n">lhs_probs</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">model</span><span class="o">.</span><span class="n">flrg_lhs_unconditional_probability</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">k</span><span class="p">])</span>
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">ftpg_keys</span><span class="p">])</span>
<span class="n">mat</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="nb">len</span><span class="p">(</span><span class="n">ftpg_keys</span><span class="p">),</span> <span class="nb">len</span><span class="p">(</span><span class="n">ordered_sets</span><span class="p">)))</span>
<span class="k">for</span> <span class="n">row</span><span class="p">,</span> <span class="n">w</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">ftpg_keys</span><span class="p">):</span>
<span class="k">for</span> <span class="n">col</span><span class="p">,</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">ordered_sets</span><span class="p">):</span>
<span class="k">if</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">w</span><span class="p">]</span><span class="o">.</span><span class="n">RHS</span><span class="p">:</span>
<span class="n">mat</span><span class="p">[</span><span class="n">row</span><span class="p">,</span> <span class="n">col</span><span class="p">]</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">w</span><span class="p">]</span><span class="o">.</span><span class="n">rhs_unconditional_probability</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
<span class="k">return</span> <span class="n">ftpg_keys</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="p">,</span> <span class="n">lhs_probs</span><span class="p">,</span> <span class="n">mat</span></div>
<div class="viewcode-block" id="visualize_distributions"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.visualize_distributions">[docs]</a><span class="k">def</span> <span class="nf">visualize_distributions</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">from</span> <span class="nn">matplotlib</span> <span class="k">import</span> <span class="n">gridspec</span>
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</span>
<span class="n">ftpg_keys</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="p">,</span> <span class="n">lhs_probs</span><span class="p">,</span> <span class="n">mat</span> <span class="o">=</span> <span class="n">highorder_fuzzy_markov_chain</span><span class="p">(</span><span class="n">model</span><span class="p">)</span>
<span class="n">size</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;size&#39;</span><span class="p">,</span> <span class="p">(</span><span class="mi">5</span><span class="p">,</span><span class="mi">10</span><span class="p">))</span>
@ -750,6 +747,8 @@
<span class="n">ax</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">(</span><span class="n">ordered_sets</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">grid</span><span class="p">(</span><span class="kc">True</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">xaxis</span><span class="o">.</span><span class="n">set_tick_params</span><span class="p">(</span><span class="n">rotation</span><span class="o">=</span><span class="mi">90</span><span class="p">)</span></div>
</pre></div>
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@ -762,7 +761,7 @@
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<title>pyFTS.models.sadaei &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
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>modules</a> |</li>
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<li class="nav-item nav-item-this"><a href="">pyFTS.models.sadaei</a></li>
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@ -63,14 +51,14 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span><span class="p">,</span><span class="n">FLR</span><span class="p">,</span><span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span><span class="n">FLR</span><span class="p">,</span><span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span>
<span class="n">default_c</span> <span class="o">=</span> <span class="mf">1.1</span>
<div class="viewcode-block" id="ExponentialyWeightedFLRG"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.sadaei.ExponentialyWeightedFLRG">[docs]</a><span class="k">class</span> <span class="nc">ExponentialyWeightedFLRG</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;First Order Exponentialy Weighted Fuzzy Logical Relationship Group&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">ExponentialyWeightedFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="n">LHS</span>
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">[]</span>
@ -90,7 +78,7 @@
<span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">k</span> <span class="o">/</span> <span class="n">tot</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">wei</span><span class="p">])</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">w</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">+</span> <span class="s2">&quot; -&gt; &quot;</span>
<span class="n">tmp2</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
<span class="n">cc</span> <span class="o">=</span> <span class="mi">0</span>
@ -103,13 +91,13 @@
<span class="n">cc</span> <span class="o">=</span> <span class="n">cc</span> <span class="o">+</span> <span class="mi">1</span>
<span class="k">return</span> <span class="n">tmp</span> <span class="o">+</span> <span class="n">tmp2</span>
<span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
<div class="viewcode-block" id="ExponentialyWeightedFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.sadaei.ExponentialyWeightedFTS">[docs]</a><span class="k">class</span> <span class="nc">ExponentialyWeightedFTS</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;First Order Exponentialy Weighted Fuzzy Time Series&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">ExponentialyWeightedFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">&quot;EWFTS&quot;</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Exponentialy Weighted FTS&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">&quot;Sadaei&quot;</span>
@ -183,7 +171,7 @@
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<title>pyFTS.models.seasonal.SeasonalIndexer &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
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<li class="nav-item nav-item-this"><a href="">pyFTS.models.seasonal.SeasonalIndexer</a></li>
</ul>
@ -57,14 +45,14 @@
<h1>Source code for pyFTS.models.seasonal.SeasonalIndexer</h1><div class="highlight"><pre>
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.seasonal</span> <span class="kn">import</span> <span class="n">common</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.seasonal</span> <span class="k">import</span> <span class="n">common</span>
<div class="viewcode-block" id="SeasonalIndexer"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.SeasonalIndexer">[docs]</a><span class="k">class</span> <span class="nc">SeasonalIndexer</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Seasonal Indexer. Responsible to find the seasonal index of a data point inside its data set</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">num_seasons</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">num_seasons</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="bp">self</span><span class="o">.</span><span class="n">num_seasons</span> <span class="o">=</span> <span class="n">num_seasons</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;name&quot;</span><span class="p">,</span><span class="s2">&quot;&quot;</span><span class="p">)</span>
@ -89,7 +77,7 @@
<div class="viewcode-block" id="LinearSeasonalIndexer"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.LinearSeasonalIndexer">[docs]</a><span class="k">class</span> <span class="nc">LinearSeasonalIndexer</span><span class="p">(</span><span class="n">SeasonalIndexer</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Use the data array/list position to index the seasonality &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">seasons</span><span class="p">,</span> <span class="n">units</span><span class="p">,</span> <span class="n">ignore</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">seasons</span><span class="p">,</span> <span class="n">units</span><span class="p">,</span> <span class="n">ignore</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Indexer for array/list position</span>
<span class="sd"> :param seasons: A list with the season group (i.e: 7 for week, 30 for month, etc)</span>
@ -147,7 +135,7 @@
<div class="viewcode-block" id="DataFrameSeasonalIndexer"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.DataFrameSeasonalIndexer">[docs]</a><span class="k">class</span> <span class="nc">DataFrameSeasonalIndexer</span><span class="p">(</span><span class="n">SeasonalIndexer</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Use the Pandas.DataFrame index position to index the seasonality &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">index_fields</span><span class="p">,</span><span class="n">index_seasons</span><span class="p">,</span> <span class="n">data_field</span><span class="p">,</span><span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">index_fields</span><span class="p">,</span><span class="n">index_seasons</span><span class="p">,</span> <span class="n">data_field</span><span class="p">,</span><span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> :param index_fields: DataFrame field to use as index</span>
@ -199,7 +187,7 @@
<div class="viewcode-block" id="DateTimeSeasonalIndexer"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.DateTimeSeasonalIndexer">[docs]</a><span class="k">class</span> <span class="nc">DateTimeSeasonalIndexer</span><span class="p">(</span><span class="n">SeasonalIndexer</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Use a Pandas.DataFrame date field to index the seasonality &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">date_field</span><span class="p">,</span> <span class="n">index_fields</span><span class="p">,</span> <span class="n">index_seasons</span><span class="p">,</span> <span class="n">data_field</span><span class="p">,</span><span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">date_field</span><span class="p">,</span> <span class="n">index_fields</span><span class="p">,</span> <span class="n">index_seasons</span><span class="p">,</span> <span class="n">data_field</span><span class="p">,</span><span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> :param date_field: DataFrame field that contains the datetime field used on index</span>
@ -269,7 +257,7 @@
<h3 id="searchlabel">Quick search</h3>
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@ -288,14 +276,14 @@
<li class="right" >
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<li class="nav-item nav-item-1"><a href="../../../index.html" >Module code</a> &#187;</li>
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
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@ -5,31 +5,19 @@
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<title>pyFTS.models.seasonal.cmsfts &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
<a href="../../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
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<li class="nav-item nav-item-1"><a href="../../../index.html" accesskey="U">Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.seasonal.cmsfts</a></li>
</ul>
@ -56,16 +44,16 @@
<h1>Source code for pyFTS.models.seasonal.cmsfts</h1><div class="highlight"><pre>
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.seasonal</span> <span class="kn">import</span> <span class="n">sfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">import</span> <span class="n">chen</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.seasonal</span> <span class="k">import</span> <span class="n">sfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">chen</span>
<div class="viewcode-block" id="ContextualSeasonalFLRG"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.cmsfts.ContextualSeasonalFLRG">[docs]</a><span class="k">class</span> <span class="nc">ContextualSeasonalFLRG</span><span class="p">(</span><span class="n">sfts</span><span class="o">.</span><span class="n">SeasonalFLRG</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Contextual Seasonal Fuzzy Logical Relationship Group</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">seasonality</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">seasonality</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">ContextualSeasonalFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">seasonality</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">{}</span>
@ -76,7 +64,7 @@
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span> <span class="o">=</span> <span class="n">chen</span><span class="o">.</span><span class="n">ConventionalFLRG</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
<span class="k">def</span> <span class="fm">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">+</span> <span class="s2">&quot;: </span><span class="se">\n</span><span class="s2"> &quot;</span>
<span class="n">tmp2</span> <span class="o">=</span> <span class="s2">&quot;</span><span class="se">\t</span><span class="s2">&quot;</span>
<span class="k">for</span> <span class="n">r</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">):</span>
@ -88,7 +76,7 @@
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Contextual Multi-Seasonal Fuzzy Time Series</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">ContextualMultiSeasonalFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Contextual Multi Seasonal FTS&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">&quot;CMSFTS &quot;</span>
@ -177,7 +165,7 @@
<h3 id="searchlabel">Quick search</h3>
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@ -196,14 +184,14 @@
<li class="right" >
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<li class="nav-item nav-item-1"><a href="../../../index.html" >Module code</a> &#187;</li>
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
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@ -5,31 +5,19 @@
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<title>pyFTS.models.seasonal.common &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
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</ul>
@ -57,10 +45,10 @@
<h1>Source code for pyFTS.models.seasonal.common</h1><div class="highlight"><pre>
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">from</span> <span class="nn">enum</span> <span class="kn">import</span> <span class="n">Enum</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">Membership</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">partitioner</span><span class="p">,</span> <span class="n">Grid</span>
<span class="kn">from</span> <span class="nn">datetime</span> <span class="kn">import</span> <span class="n">date</span> <span class="k">as</span> <span class="n">dt</span><span class="p">,</span> <span class="n">datetime</span> <span class="k">as</span> <span class="n">dtm</span>
<span class="kn">from</span> <span class="nn">enum</span> <span class="k">import</span> <span class="n">Enum</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">Membership</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">partitioner</span><span class="p">,</span> <span class="n">Grid</span>
<span class="kn">from</span> <span class="nn">datetime</span> <span class="k">import</span> <span class="n">date</span> <span class="k">as</span> <span class="n">dt</span><span class="p">,</span> <span class="n">datetime</span> <span class="k">as</span> <span class="n">dtm</span>
<div class="viewcode-block" id="DateTime"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.common.DateTime">[docs]</a><span class="k">class</span> <span class="nc">DateTime</span><span class="p">(</span><span class="n">Enum</span><span class="p">):</span>
@ -156,7 +144,7 @@
<span class="sd"> Temporal/Seasonal Fuzzy Set</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">datepart</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">mf</span><span class="p">,</span> <span class="n">parameters</span><span class="p">,</span> <span class="n">centroid</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">datepart</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">mf</span><span class="p">,</span> <span class="n">parameters</span><span class="p">,</span> <span class="n">centroid</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">FuzzySet</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="n">mf</span><span class="p">,</span> <span class="n">parameters</span><span class="p">,</span> <span class="n">centroid</span><span class="p">,</span> <span class="n">alpha</span><span class="p">,</span>
<span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">datepart</span> <span class="o">=</span> <span class="n">datepart</span>
@ -181,7 +169,7 @@
<h3 id="searchlabel">Quick search</h3>
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@ -200,14 +188,14 @@
<li class="right" >
<a href="../../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
<li class="nav-item nav-item-0"><a href="../../../../index.html">pyFTS 1.7 documentation</a> &#187;</li>
<li class="nav-item nav-item-1"><a href="../../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.seasonal.common</a></li>
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</div>
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
</div>
</body>
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@ -5,31 +5,19 @@
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@ -43,7 +31,7 @@
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@ -56,15 +44,15 @@
<h1>Source code for pyFTS.models.seasonal.msfts</h1><div class="highlight"><pre>
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FLR</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.seasonal</span> <span class="kn">import</span> <span class="n">sfts</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FLR</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.seasonal</span> <span class="k">import</span> <span class="n">sfts</span>
<div class="viewcode-block" id="MultiSeasonalFTS"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.msfts.MultiSeasonalFTS">[docs]</a><span class="k">class</span> <span class="nc">MultiSeasonalFTS</span><span class="p">(</span><span class="n">sfts</span><span class="o">.</span><span class="n">SeasonalFTS</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Multi-Seasonal Fuzzy Time Series</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">indexer</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">indexer</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">MultiSeasonalFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="s2">&quot;MSFTS&quot;</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Multi Seasonal FTS&quot;</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">&quot;MSFTS &quot;</span> <span class="o">+</span> <span class="n">name</span>
@ -133,7 +121,7 @@
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@ -152,14 +140,14 @@
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
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&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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<title>pyFTS.models.seasonal.partitioner &#8212; pyFTS 1.6 documentation</title>
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@ -43,7 +31,7 @@
<li class="right" >
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@ -55,19 +43,19 @@
<div class="body" role="main">
<h1>Source code for pyFTS.models.seasonal.partitioner</h1><div class="highlight"><pre>
<span></span><span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">FuzzySet</span> <span class="k">as</span> <span class="n">FS</span>
<span class="kn">from</span> <span class="nn">pyFTS.common.Composite</span> <span class="kn">import</span> <span class="n">FuzzySet</span> <span class="k">as</span> <span class="n">Composite</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="kn">import</span> <span class="n">partitioner</span><span class="p">,</span> <span class="n">Grid</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.seasonal.common</span> <span class="kn">import</span> <span class="n">DateTime</span><span class="p">,</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">strip_datepart</span>
<span></span><span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">FuzzySet</span> <span class="k">as</span> <span class="n">FS</span>
<span class="kn">from</span> <span class="nn">pyFTS.common.Composite</span> <span class="k">import</span> <span class="n">FuzzySet</span> <span class="k">as</span> <span class="n">Composite</span>
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">partitioner</span><span class="p">,</span> <span class="n">Grid</span>
<span class="kn">from</span> <span class="nn">pyFTS.models.seasonal.common</span> <span class="k">import</span> <span class="n">DateTime</span><span class="p">,</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">strip_datepart</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">import</span> <span class="nn">matplotlib.pylab</span> <span class="k">as</span> <span class="nn">plt</span>
<span class="kn">from</span> <span class="nn">scipy.spatial</span> <span class="kn">import</span> <span class="n">KDTree</span>
<span class="kn">from</span> <span class="nn">scipy.spatial</span> <span class="k">import</span> <span class="n">KDTree</span>
<div class="viewcode-block" id="TimeGridPartitioner"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.partitioner.TimeGridPartitioner">[docs]</a><span class="k">class</span> <span class="nc">TimeGridPartitioner</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="n">Partitioner</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;Even Length DateTime Grid Partitioner&quot;&quot;&quot;</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Even Length Grid Partitioner</span>
<span class="sd"> :param seasonality: Time granularity, from pyFTS.models.seasonal.common.DateTime</span>
@ -270,7 +258,7 @@
<h3 id="searchlabel">Quick search</h3>
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<form class="search" action="../../../../search.html" method="get">
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<input type="submit" value="Go" />
</form>
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@ -289,14 +277,14 @@
<li class="right" >
<a href="../../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../../index.html">pyFTS 1.6 documentation</a> &#187;</li>
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<li class="nav-item nav-item-1"><a href="../../../index.html" >Module code</a> &#187;</li>
<li class="nav-item nav-item-this"><a href="">pyFTS.models.seasonal.partitioner</a></li>
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&#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
&#169; Copyright 2022, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 4.5.0.
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