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<section id="pyfts-common-transformations-package">
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<h1>pyFTS.common.transformations package<a class="headerlink" href="#pyfts-common-transformations-package" title="Permalink to this headline"></a></h1>
<section id="module-pyFTS.common.transformations">
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<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-pyFTS.common.transformations" title="Permalink to this headline"></a></h2>
</section>
<section id="submodules">
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<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline"></a></h2>
</section>
<section id="pyfts-common-transformations-adapativeexpectation-module">
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<h2>pyFTS.common.transformations.adapativeexpectation module<a class="headerlink" href="#pyfts-common-transformations-adapativeexpectation-module" title="Permalink to this headline"></a></h2>
</section>
<section id="module-pyFTS.common.transformations.boxcox">
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<span id="pyfts-common-transformations-boxcox-module"></span><h2>pyFTS.common.transformations.boxcox module<a class="headerlink" href="#module-pyFTS.common.transformations.boxcox" title="Permalink to this headline"></a></h2>
<dl class="py class">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.boxcox.BoxCox">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.common.transformations.boxcox.</span></span><span class="sig-name descname"><span class="pre">BoxCox</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">plambda</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/boxcox.html#BoxCox"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.boxcox.BoxCox" title="Permalink to this definition"></a></dt>
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<dd><p>Bases: <a class="reference internal" href="#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.transformations.transformation.Transformation</span></code></a></p>
<p>Box-Cox power transformation</p>
<p>y(t) = log( y(t) )
y(t) = exp( y(t) )</p>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.boxcox.BoxCox.apply">
<span class="sig-name descname"><span class="pre">apply</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/boxcox.html#BoxCox.apply"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.boxcox.BoxCox.apply" title="Permalink to this definition"></a></dt>
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<dd><p>Apply the transformation on input data</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> input data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with transformed data</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.boxcox.BoxCox.inverse">
<span class="sig-name descname"><span class="pre">inverse</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/boxcox.html#BoxCox.inverse"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.boxcox.BoxCox.inverse" title="Permalink to this definition"></a></dt>
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<dd><dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> transformed data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with inverse transformed data</p>
</dd>
</dl>
</dd></dl>
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<dl class="py property">
<dt class="sig sig-object py" id="pyFTS.common.transformations.boxcox.BoxCox.parameters">
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">parameters</span></span><a class="headerlink" href="#pyFTS.common.transformations.boxcox.BoxCox.parameters" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
</dd></dl>
</section>
<section id="module-pyFTS.common.transformations.differential">
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<span id="pyfts-common-transformations-differential-module"></span><h2>pyFTS.common.transformations.differential module<a class="headerlink" href="#module-pyFTS.common.transformations.differential" title="Permalink to this headline"></a></h2>
<dl class="py class">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.differential.Differential">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.common.transformations.differential.</span></span><span class="sig-name descname"><span class="pre">Differential</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">lag</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/differential.html#Differential"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.differential.Differential" title="Permalink to this definition"></a></dt>
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<dd><p>Bases: <a class="reference internal" href="#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.transformations.transformation.Transformation</span></code></a></p>
<p>Differentiation data transform</p>
<p>y(t) = y(t) - y(t-1)
y(t) = y(t-1) + y(t)</p>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.differential.Differential.apply">
<span class="sig-name descname"><span class="pre">apply</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/differential.html#Differential.apply"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.differential.Differential.apply" title="Permalink to this definition"></a></dt>
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<dd><p>Apply the transformation on input data</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> input data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with transformed data</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.differential.Differential.inverse">
<span class="sig-name descname"><span class="pre">inverse</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/differential.html#Differential.inverse"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.differential.Differential.inverse" title="Permalink to this definition"></a></dt>
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<dd><dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> transformed data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with inverse transformed data</p>
</dd>
</dl>
</dd></dl>
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<dl class="py property">
<dt class="sig sig-object py" id="pyFTS.common.transformations.differential.Differential.parameters">
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">parameters</span></span><a class="headerlink" href="#pyFTS.common.transformations.differential.Differential.parameters" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
</dd></dl>
</section>
<section id="module-pyFTS.common.transformations.normalization">
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<span id="pyfts-common-transformations-normalization-module"></span><h2>pyFTS.common.transformations.normalization module<a class="headerlink" href="#module-pyFTS.common.transformations.normalization" title="Permalink to this headline"></a></h2>
<dl class="py class">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.normalization.Normalization">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.common.transformations.normalization.</span></span><span class="sig-name descname"><span class="pre">Normalization</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/normalization.html#Normalization"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.normalization.Normalization" title="Permalink to this definition"></a></dt>
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<dd><p>Bases: <a class="reference internal" href="#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.transformations.transformation.Transformation</span></code></a></p>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.normalization.Normalization.apply">
<span class="sig-name descname"><span class="pre">apply</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/normalization.html#Normalization.apply"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.normalization.Normalization.apply" title="Permalink to this definition"></a></dt>
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<dd><p>Apply the transformation on input data</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> input data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with transformed data</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.normalization.Normalization.inverse">
<span class="sig-name descname"><span class="pre">inverse</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/normalization.html#Normalization.inverse"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.normalization.Normalization.inverse" title="Permalink to this definition"></a></dt>
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<dd><dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> transformed data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with inverse transformed data</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.normalization.Normalization.train">
<span class="sig-name descname"><span class="pre">train</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/normalization.html#Normalization.train"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.normalization.Normalization.train" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
</dd></dl>
</section>
<section id="module-pyFTS.common.transformations.roi">
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<span id="pyfts-common-transformations-roi-module"></span><h2>pyFTS.common.transformations.roi module<a class="headerlink" href="#module-pyFTS.common.transformations.roi" title="Permalink to this headline"></a></h2>
<dl class="py class">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.roi.ROI">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.common.transformations.roi.</span></span><span class="sig-name descname"><span class="pre">ROI</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/roi.html#ROI"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.roi.ROI" title="Permalink to this definition"></a></dt>
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<dd><p>Bases: <a class="reference internal" href="#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.transformations.transformation.Transformation</span></code></a></p>
<p>Return of Investment (ROI) transformation. Retrieved from Sadaei and Lee (2014) - Multilayer Stock
Forecasting Model Using Fuzzy Time Series</p>
<p>y(t) = ( y(t) - y(t-1) ) / y(t-1)
y(t) = ( y(t-1) * y(t) ) + y(t-1)</p>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.roi.ROI.apply">
<span class="sig-name descname"><span class="pre">apply</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/roi.html#ROI.apply"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.roi.ROI.apply" title="Permalink to this definition"></a></dt>
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<dd><p>Apply the transformation on input data</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> input data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with transformed data</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.roi.ROI.inverse">
<span class="sig-name descname"><span class="pre">inverse</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/roi.html#ROI.inverse"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.roi.ROI.inverse" title="Permalink to this definition"></a></dt>
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<dd><dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> transformed data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with inverse transformed data</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
<section id="module-pyFTS.common.transformations.scale">
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<span id="pyfts-common-transformations-scale-module"></span><h2>pyFTS.common.transformations.scale module<a class="headerlink" href="#module-pyFTS.common.transformations.scale" title="Permalink to this headline"></a></h2>
<dl class="py class">
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.common.transformations.scale.Scale">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.common.transformations.scale.</span></span><span class="sig-name descname"><span class="pre">Scale</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">min</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">max</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">1</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/scale.html#Scale"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.scale.Scale" title="Permalink to this definition"></a></dt>
2021-01-13 03:05:34 +04:00
<dd><p>Bases: <a class="reference internal" href="#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.transformations.transformation.Transformation</span></code></a></p>
<p>Scale data inside a interval [min, max]</p>
<dl class="py method">
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.common.transformations.scale.Scale.apply">
<span class="sig-name descname"><span class="pre">apply</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/scale.html#Scale.apply"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.scale.Scale.apply" title="Permalink to this definition"></a></dt>
2021-01-13 03:05:34 +04:00
<dd><p>Apply the transformation on input data</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> input data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with transformed data</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.common.transformations.scale.Scale.inverse">
<span class="sig-name descname"><span class="pre">inverse</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/scale.html#Scale.inverse"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.scale.Scale.inverse" title="Permalink to this definition"></a></dt>
2021-01-13 03:05:34 +04:00
<dd><dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> transformed data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with inverse transformed data</p>
</dd>
</dl>
</dd></dl>
2022-04-10 21:32:24 +04:00
<dl class="py property">
<dt class="sig sig-object py" id="pyFTS.common.transformations.scale.Scale.parameters">
<em class="property"><span class="pre">property</span><span class="w"> </span></em><span class="sig-name descname"><span class="pre">parameters</span></span><a class="headerlink" href="#pyFTS.common.transformations.scale.Scale.parameters" title="Permalink to this definition"></a></dt>
2021-01-13 03:05:34 +04:00
<dd></dd></dl>
</dd></dl>
</section>
<section id="module-pyFTS.common.transformations.smoothing">
2021-01-13 03:05:34 +04:00
<span id="pyfts-common-transformations-smoothing-module"></span><h2>pyFTS.common.transformations.smoothing module<a class="headerlink" href="#module-pyFTS.common.transformations.smoothing" title="Permalink to this headline"></a></h2>
<dl class="py class">
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.common.transformations.smoothing.AveragePooling">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.common.transformations.smoothing.</span></span><span class="sig-name descname"><span class="pre">AveragePooling</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/smoothing.html#AveragePooling"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.smoothing.AveragePooling" title="Permalink to this definition"></a></dt>
2021-01-13 03:05:34 +04:00
<dd><p>Bases: <a class="reference internal" href="#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.transformations.transformation.Transformation</span></code></a></p>
<dl class="py method">
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.common.transformations.smoothing.AveragePooling.apply">
<span class="sig-name descname"><span class="pre">apply</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/smoothing.html#AveragePooling.apply"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.smoothing.AveragePooling.apply" title="Permalink to this definition"></a></dt>
2021-01-13 03:05:34 +04:00
<dd><p>Apply the transformation on input data</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> input data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with transformed data</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.common.transformations.smoothing.AveragePooling.inverse">
<span class="sig-name descname"><span class="pre">inverse</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/smoothing.html#AveragePooling.inverse"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.smoothing.AveragePooling.inverse" title="Permalink to this definition"></a></dt>
2021-01-13 03:05:34 +04:00
<dd><dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> transformed data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with inverse transformed data</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
<dl class="py class">
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.common.transformations.smoothing.ExponentialSmoothing">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.common.transformations.smoothing.</span></span><span class="sig-name descname"><span class="pre">ExponentialSmoothing</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/smoothing.html#ExponentialSmoothing"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.smoothing.ExponentialSmoothing" title="Permalink to this definition"></a></dt>
2021-01-13 03:05:34 +04:00
<dd><p>Bases: <a class="reference internal" href="#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.transformations.transformation.Transformation</span></code></a></p>
<dl class="py method">
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.common.transformations.smoothing.ExponentialSmoothing.apply">
<span class="sig-name descname"><span class="pre">apply</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/smoothing.html#ExponentialSmoothing.apply"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.smoothing.ExponentialSmoothing.apply" title="Permalink to this definition"></a></dt>
2021-01-13 03:05:34 +04:00
<dd><p>Apply the transformation on input data</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> input data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with transformed data</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.common.transformations.smoothing.ExponentialSmoothing.inverse">
<span class="sig-name descname"><span class="pre">inverse</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/smoothing.html#ExponentialSmoothing.inverse"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.smoothing.ExponentialSmoothing.inverse" title="Permalink to this definition"></a></dt>
<dd><dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> transformed data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with inverse transformed data</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="pyFTS.common.transformations.smoothing.MaxPooling">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.common.transformations.smoothing.</span></span><span class="sig-name descname"><span class="pre">MaxPooling</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/smoothing.html#MaxPooling"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.smoothing.MaxPooling" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.transformations.transformation.Transformation</span></code></a></p>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.common.transformations.smoothing.MaxPooling.apply">
<span class="sig-name descname"><span class="pre">apply</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/smoothing.html#MaxPooling.apply"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.smoothing.MaxPooling.apply" title="Permalink to this definition"></a></dt>
<dd><p>Apply the transformation on input data</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> input data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with transformed data</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.common.transformations.smoothing.MaxPooling.inverse">
<span class="sig-name descname"><span class="pre">inverse</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/smoothing.html#MaxPooling.inverse"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.smoothing.MaxPooling.inverse" title="Permalink to this definition"></a></dt>
<dd><dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> transformed data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with inverse transformed data</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="pyFTS.common.transformations.smoothing.MovingAverage">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.common.transformations.smoothing.</span></span><span class="sig-name descname"><span class="pre">MovingAverage</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/smoothing.html#MovingAverage"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.smoothing.MovingAverage" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.transformations.transformation.Transformation</span></code></a></p>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.common.transformations.smoothing.MovingAverage.apply">
<span class="sig-name descname"><span class="pre">apply</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/smoothing.html#MovingAverage.apply"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.smoothing.MovingAverage.apply" title="Permalink to this definition"></a></dt>
<dd><p>Apply the transformation on input data</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> input data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with transformed data</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.common.transformations.smoothing.MovingAverage.inverse">
<span class="sig-name descname"><span class="pre">inverse</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/smoothing.html#MovingAverage.inverse"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.smoothing.MovingAverage.inverse" title="Permalink to this definition"></a></dt>
2021-01-13 03:05:34 +04:00
<dd><dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> transformed data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with inverse transformed data</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</section>
<section id="module-pyFTS.common.transformations.som">
2021-01-13 03:10:49 +04:00
<span id="pyfts-common-transformations-som-module"></span><h2>pyFTS.common.transformations.som module<a class="headerlink" href="#module-pyFTS.common.transformations.som" title="Permalink to this headline"></a></h2>
<p>Kohonen Self Organizing Maps for Fuzzy Time Series</p>
<dl class="py class">
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.common.transformations.som.SOMTransformation">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.common.transformations.som.</span></span><span class="sig-name descname"><span class="pre">SOMTransformation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">grid_dimension</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">Tuple</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/som.html#SOMTransformation"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.som.SOMTransformation" title="Permalink to this definition"></a></dt>
2021-01-13 03:10:49 +04:00
<dd><p>Bases: <a class="reference internal" href="#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.transformations.transformation.Transformation</span></code></a></p>
<dl class="py method">
2022-04-10 21:32:24 +04:00
<dt class="sig sig-object py" id="pyFTS.common.transformations.som.SOMTransformation.apply">
<span class="sig-name descname"><span class="pre">apply</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">pandas.core.frame.DataFrame</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/som.html#SOMTransformation.apply"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.som.SOMTransformation.apply" title="Permalink to this definition"></a></dt>
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<dd><p>Transform a M-dimensional dataset into a 3-dimensional dataset, where one dimension is the endogen variable
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If endogen_variable = None, the last column will be the endogen_variable.</p>
<dl>
<dt>Args:</dt><dd><p>data (pd.DataFrame): M-Dimensional dataset
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endogen_variable (str): column of dataset
names (Tuple): names for new columns created by SOM Transformation.
param:
<a href="#id1"><span class="problematic" id="id2">**</span></a>kwargs: params of SOMs train process</p>
<blockquote>
<div><p>percentage_train (float). Percentage of dataset that will be used for train SOM network. default: 0.7
leaning_rate (float): leaning rate of SOM network. default: 0.01
epochs: epochs of SOM network. default: 10000</p>
</div></blockquote>
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</dd>
</dl>
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<p>Returns:</p>
</dd></dl>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.som.SOMTransformation.save_net">
<span class="sig-name descname"><span class="pre">save_net</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">filename</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.11)"><span class="pre">str</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'SomNet</span> <span class="pre">trained'</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/som.html#SOMTransformation.save_net"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.som.SOMTransformation.save_net" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.som.SOMTransformation.show_grid">
<span class="sig-name descname"><span class="pre">show_grid</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">graph_type</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.11)"><span class="pre">str</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">'nodes_graph'</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/som.html#SOMTransformation.show_grid"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.som.SOMTransformation.show_grid" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.som.SOMTransformation.train">
<span class="sig-name descname"><span class="pre">train</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><span class="pre">pandas.core.frame.DataFrame</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">percentage_train</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.11)"><span class="pre">float</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.7</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">leaning_rate</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.11)"><span class="pre">float</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">0.01</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">epochs</span></span><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="n"><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.11)"><span class="pre">int</span></a></span><span class="w"> </span><span class="o"><span class="pre">=</span></span><span class="w"> </span><span class="default_value"><span class="pre">10000</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/som.html#SOMTransformation.train"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.som.SOMTransformation.train" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
</dd></dl>
</section>
<section id="module-pyFTS.common.transformations.transformation">
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<span id="pyfts-common-transformations-transformation-module"></span><h2>pyFTS.common.transformations.transformation module<a class="headerlink" href="#module-pyFTS.common.transformations.transformation" title="Permalink to this headline"></a></h2>
<dl class="py class">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.transformation.Transformation">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.common.transformations.transformation.</span></span><span class="sig-name descname"><span class="pre">Transformation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/transformation.html#Transformation"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.transformation.Transformation" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.11)"><code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></a></p>
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<p>Data transformation used on pre and post processing of the FTS</p>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.transformation.Transformation.apply">
<span class="sig-name descname"><span class="pre">apply</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/transformation.html#Transformation.apply"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.transformation.Transformation.apply" title="Permalink to this definition"></a></dt>
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<dd><p>Apply the transformation on input data</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> input data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with transformed data</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.transformation.Transformation.inverse">
<span class="sig-name descname"><span class="pre">inverse</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">param</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/transformation.html#Transformation.inverse"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.common.transformations.transformation.Transformation.inverse" title="Permalink to this definition"></a></dt>
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<dd><dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> transformed data</p></li>
<li><p><strong>param</strong> </p></li>
<li><p><strong>kwargs</strong> </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>numpy array with inverse transformed data</p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
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<dt class="sig sig-object py" id="pyFTS.common.transformations.transformation.Transformation.is_multivariate">
<span class="sig-name descname"><span class="pre">is_multivariate</span></span><a class="headerlink" href="#pyFTS.common.transformations.transformation.Transformation.is_multivariate" title="Permalink to this definition"></a></dt>
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<dd><p>detemine if this transformation can be applied to multivariate data</p>
</dd></dl>
</dd></dl>
</section>
<section id="pyfts-common-transformations-trend-module">
<h2>pyFTS.common.transformations.trend module<a class="headerlink" href="#pyfts-common-transformations-trend-module" title="Permalink to this headline"></a></h2>
</section>
</section>
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<li><a class="reference internal" href="#">pyFTS.common.transformations package</a><ul>
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<li><a class="reference internal" href="#module-pyFTS.common.transformations">Module contents</a></li>
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<li><a class="reference internal" href="#pyfts-common-transformations-adapativeexpectation-module">pyFTS.common.transformations.adapativeexpectation module</a></li>
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<li><a class="reference internal" href="#module-pyFTS.common.transformations.boxcox">pyFTS.common.transformations.boxcox module</a></li>
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<li><a class="reference internal" href="#module-pyFTS.common.transformations.som">pyFTS.common.transformations.som module</a></li>
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<li><a class="reference internal" href="#module-pyFTS.common.transformations.transformation">pyFTS.common.transformations.transformation module</a></li>
<li><a class="reference internal" href="#pyfts-common-transformations-trend-module">pyFTS.common.transformations.trend module</a></li>
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