<spanid="module-contents"></span><h2>Module contents<aclass="headerlink"href="#module-pyFTS.common.transformations"title="Permalink to this headline">¶</a></h2>
<h2>pyFTS.common.transformations.adapativeexpectation module<aclass="headerlink"href="#pyfts-common-transformations-adapativeexpectation-module"title="Permalink to this headline">¶</a></h2>
<spanid="pyfts-common-transformations-boxcox-module"></span><h2>pyFTS.common.transformations.boxcox module<aclass="headerlink"href="#module-pyFTS.common.transformations.boxcox"title="Permalink to this headline">¶</a></h2>
<emclass="property">class </em><codeclass="sig-prename descclassname">pyFTS.common.transformations.boxcox.</code><codeclass="sig-name descname">BoxCox</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">plambda</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/boxcox.html#BoxCox"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.boxcox.BoxCox"title="Permalink to this definition">¶</a></dt>
<codeclass="sig-name descname">apply</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="n">param</span><spanclass="o">=</span><spanclass="default_value">None</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/boxcox.html#BoxCox.apply"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.boxcox.BoxCox.apply"title="Permalink to this definition">¶</a></dt>
<dd><p>Apply the transformation on input data</p>
<dlclass="field-list simple">
<dtclass="field-odd">Parameters</dt>
<ddclass="field-odd"><ulclass="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>
<dtclass="field-even">Returns</dt>
<ddclass="field-even"><p>numpy array with transformed data</p>
<codeclass="sig-name descname">inverse</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="n">param</span><spanclass="o">=</span><spanclass="default_value">None</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/boxcox.html#BoxCox.inverse"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.boxcox.BoxCox.inverse"title="Permalink to this definition">¶</a></dt>
<emclass="property">property </em><codeclass="sig-name descname">parameters</code><aclass="headerlink"href="#pyFTS.common.transformations.boxcox.BoxCox.parameters"title="Permalink to this definition">¶</a></dt>
<spanid="pyfts-common-transformations-differential-module"></span><h2>pyFTS.common.transformations.differential module<aclass="headerlink"href="#module-pyFTS.common.transformations.differential"title="Permalink to this headline">¶</a></h2>
<emclass="property">class </em><codeclass="sig-prename descclassname">pyFTS.common.transformations.differential.</code><codeclass="sig-name descname">Differential</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">lag</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/differential.html#Differential"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.differential.Differential"title="Permalink to this definition">¶</a></dt>
<codeclass="sig-name descname">apply</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="n">param</span><spanclass="o">=</span><spanclass="default_value">None</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/differential.html#Differential.apply"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.differential.Differential.apply"title="Permalink to this definition">¶</a></dt>
<dd><p>Apply the transformation on input data</p>
<dlclass="field-list simple">
<dtclass="field-odd">Parameters</dt>
<ddclass="field-odd"><ulclass="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>
<dtclass="field-even">Returns</dt>
<ddclass="field-even"><p>numpy array with transformed data</p>
<codeclass="sig-name descname">inverse</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="n">param</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/differential.html#Differential.inverse"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.differential.Differential.inverse"title="Permalink to this definition">¶</a></dt>
<emclass="property">property </em><codeclass="sig-name descname">parameters</code><aclass="headerlink"href="#pyFTS.common.transformations.differential.Differential.parameters"title="Permalink to this definition">¶</a></dt>
<spanid="pyfts-common-transformations-normalization-module"></span><h2>pyFTS.common.transformations.normalization module<aclass="headerlink"href="#module-pyFTS.common.transformations.normalization"title="Permalink to this headline">¶</a></h2>
<emclass="property">class </em><codeclass="sig-prename descclassname">pyFTS.common.transformations.normalization.</code><codeclass="sig-name descname">Normalization</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/normalization.html#Normalization"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.normalization.Normalization"title="Permalink to this definition">¶</a></dt>
<codeclass="sig-name descname">apply</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="n">param</span><spanclass="o">=</span><spanclass="default_value">None</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/normalization.html#Normalization.apply"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.normalization.Normalization.apply"title="Permalink to this definition">¶</a></dt>
<dd><p>Apply the transformation on input data</p>
<dlclass="field-list simple">
<dtclass="field-odd">Parameters</dt>
<ddclass="field-odd"><ulclass="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>
<dtclass="field-even">Returns</dt>
<ddclass="field-even"><p>numpy array with transformed data</p>
<codeclass="sig-name descname">inverse</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="n">param</span><spanclass="o">=</span><spanclass="default_value">None</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/normalization.html#Normalization.inverse"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.normalization.Normalization.inverse"title="Permalink to this definition">¶</a></dt>
<codeclass="sig-name descname">train</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/normalization.html#Normalization.train"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.normalization.Normalization.train"title="Permalink to this definition">¶</a></dt>
<spanid="pyfts-common-transformations-roi-module"></span><h2>pyFTS.common.transformations.roi module<aclass="headerlink"href="#module-pyFTS.common.transformations.roi"title="Permalink to this headline">¶</a></h2>
<dlclass="py class">
<dtid="pyFTS.common.transformations.roi.ROI">
<emclass="property">class </em><codeclass="sig-prename descclassname">pyFTS.common.transformations.roi.</code><codeclass="sig-name descname">ROI</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/roi.html#ROI"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.roi.ROI"title="Permalink to this definition">¶</a></dt>
<codeclass="sig-name descname">apply</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="n">param</span><spanclass="o">=</span><spanclass="default_value">None</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/roi.html#ROI.apply"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.roi.ROI.apply"title="Permalink to this definition">¶</a></dt>
<dd><p>Apply the transformation on input data</p>
<dlclass="field-list simple">
<dtclass="field-odd">Parameters</dt>
<ddclass="field-odd"><ulclass="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>
<dtclass="field-even">Returns</dt>
<ddclass="field-even"><p>numpy array with transformed data</p>
<codeclass="sig-name descname">inverse</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="n">param</span><spanclass="o">=</span><spanclass="default_value">None</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/roi.html#ROI.inverse"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.roi.ROI.inverse"title="Permalink to this definition">¶</a></dt>
<spanid="pyfts-common-transformations-scale-module"></span><h2>pyFTS.common.transformations.scale module<aclass="headerlink"href="#module-pyFTS.common.transformations.scale"title="Permalink to this headline">¶</a></h2>
<dlclass="py class">
<dtid="pyFTS.common.transformations.scale.Scale">
<emclass="property">class </em><codeclass="sig-prename descclassname">pyFTS.common.transformations.scale.</code><codeclass="sig-name descname">Scale</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">min</span><spanclass="o">=</span><spanclass="default_value">0</span></em>, <emclass="sig-param"><spanclass="n">max</span><spanclass="o">=</span><spanclass="default_value">1</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/scale.html#Scale"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.scale.Scale"title="Permalink to this definition">¶</a></dt>
<codeclass="sig-name descname">apply</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="n">param</span><spanclass="o">=</span><spanclass="default_value">None</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/transformations/scale.html#Scale.apply"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.scale.Scale.apply"title="Permalink to this definition">¶</a></dt>
<dd><p>Apply the transformation on input data</p>
<dlclass="field-list simple">
<dtclass="field-odd">Parameters</dt>
<ddclass="field-odd"><ulclass="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>
<dtclass="field-even">Returns</dt>
<ddclass="field-even"><p>numpy array with transformed data</p>
<codeclass="sig-name descname">inverse</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="n">param</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/scale.html#Scale.inverse"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.scale.Scale.inverse"title="Permalink to this definition">¶</a></dt>
<emclass="property">property </em><codeclass="sig-name descname">parameters</code><aclass="headerlink"href="#pyFTS.common.transformations.scale.Scale.parameters"title="Permalink to this definition">¶</a></dt>
<spanid="pyfts-common-transformations-smoothing-module"></span><h2>pyFTS.common.transformations.smoothing module<aclass="headerlink"href="#module-pyFTS.common.transformations.smoothing"title="Permalink to this headline">¶</a></h2>
<emclass="property">class </em><codeclass="sig-prename descclassname">pyFTS.common.transformations.smoothing.</code><codeclass="sig-name descname">ExponentialSmoothing</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/smoothing.html#ExponentialSmoothing"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.smoothing.ExponentialSmoothing"title="Permalink to this definition">¶</a></dt>
<codeclass="sig-name descname">apply</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="n">param</span><spanclass="o">=</span><spanclass="default_value">None</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/smoothing.html#ExponentialSmoothing.apply"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.smoothing.ExponentialSmoothing.apply"title="Permalink to this definition">¶</a></dt>
<dd><p>Apply the transformation on input data</p>
<dlclass="field-list simple">
<dtclass="field-odd">Parameters</dt>
<ddclass="field-odd"><ulclass="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>
<dtclass="field-even">Returns</dt>
<ddclass="field-even"><p>numpy array with transformed data</p>
<codeclass="sig-name descname">inverse</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="n">param</span><spanclass="o">=</span><spanclass="default_value">None</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/smoothing.html#ExponentialSmoothing.inverse"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.smoothing.ExponentialSmoothing.inverse"title="Permalink to this definition">¶</a></dt>
<emclass="property">class </em><codeclass="sig-prename descclassname">pyFTS.common.transformations.smoothing.</code><codeclass="sig-name descname">MovingAverage</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/smoothing.html#MovingAverage"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.smoothing.MovingAverage"title="Permalink to this definition">¶</a></dt>
<codeclass="sig-name descname">apply</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="n">param</span><spanclass="o">=</span><spanclass="default_value">None</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/smoothing.html#MovingAverage.apply"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.smoothing.MovingAverage.apply"title="Permalink to this definition">¶</a></dt>
<dd><p>Apply the transformation on input data</p>
<dlclass="field-list simple">
<dtclass="field-odd">Parameters</dt>
<ddclass="field-odd"><ulclass="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>
<dtclass="field-even">Returns</dt>
<ddclass="field-even"><p>numpy array with transformed data</p>
<codeclass="sig-name descname">inverse</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="n">param</span><spanclass="o">=</span><spanclass="default_value">None</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/smoothing.html#MovingAverage.inverse"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.smoothing.MovingAverage.inverse"title="Permalink to this definition">¶</a></dt>
<spanid="pyfts-common-transformations-som-module"></span><h2>pyFTS.common.transformations.som module<aclass="headerlink"href="#module-pyFTS.common.transformations.som"title="Permalink to this headline">¶</a></h2>
<p>Kohonen Self Organizing Maps for Fuzzy Time Series</p>
<emclass="property">class </em><codeclass="sig-prename descclassname">pyFTS.common.transformations.som.</code><codeclass="sig-name descname">SOMTransformation</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">grid_dimension</span><spanclass="p">:</span><spanclass="n">Tuple</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/som.html#SOMTransformation"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.som.SOMTransformation"title="Permalink to this definition">¶</a></dt>
<codeclass="sig-name descname">apply</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span><spanclass="p">:</span><spanclass="n">pandas.core.frame.DataFrame</span></em>, <emclass="sig-param"><spanclass="n">param</span><spanclass="o">=</span><spanclass="default_value">None</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/som.html#SOMTransformation.apply"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.som.SOMTransformation.apply"title="Permalink to this definition">¶</a></dt>
<dd><p>Transform a M-dimensional dataset into a 3-dimensional dataset, where one dimension is the endogen variable
If endogen_variable = None, the last column will be the endogen_variable.
<codeclass="sig-name descname">save_net</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">filename</span><spanclass="p">:</span><spanclass="n"><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#str"title="(in Python v3.9)">str</a></span><spanclass="o">=</span><spanclass="default_value">'SomNet trained'</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/som.html#SOMTransformation.save_net"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.som.SOMTransformation.save_net"title="Permalink to this definition">¶</a></dt>
<codeclass="sig-name descname">show_grid</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">graph_type</span><spanclass="p">:</span><spanclass="n"><aclass="reference external"href="https://docs.python.org/3/library/stdtypes.html#str"title="(in Python v3.9)">str</a></span><spanclass="o">=</span><spanclass="default_value">'nodes_graph'</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/som.html#SOMTransformation.show_grid"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.som.SOMTransformation.show_grid"title="Permalink to this definition">¶</a></dt>
<spanid="pyfts-common-transformations-transformation-module"></span><h2>pyFTS.common.transformations.transformation module<aclass="headerlink"href="#module-pyFTS.common.transformations.transformation"title="Permalink to this headline">¶</a></h2>
<emclass="property">class </em><codeclass="sig-prename descclassname">pyFTS.common.transformations.transformation.</code><codeclass="sig-name descname">Transformation</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/transformation.html#Transformation"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.transformation.Transformation"title="Permalink to this definition">¶</a></dt>
<codeclass="sig-name descname">apply</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="n">param</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/transformation.html#Transformation.apply"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.transformation.Transformation.apply"title="Permalink to this definition">¶</a></dt>
<dd><p>Apply the transformation on input data</p>
<dlclass="field-list simple">
<dtclass="field-odd">Parameters</dt>
<ddclass="field-odd"><ulclass="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>
<dtclass="field-even">Returns</dt>
<ddclass="field-even"><p>numpy array with transformed data</p>
<codeclass="sig-name descname">inverse</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="n">param</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/transformation.html#Transformation.inverse"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.transformation.Transformation.inverse"title="Permalink to this definition">¶</a></dt>
<codeclass="sig-name descname">is_multivariate</code><aclass="headerlink"href="#pyFTS.common.transformations.transformation.Transformation.is_multivariate"title="Permalink to this definition">¶</a></dt>
<dd><p>detemine if this transformation can be applied to multivariate data</p>
<spanid="pyfts-common-transformations-trend-module"></span><h2>pyFTS.common.transformations.trend module<aclass="headerlink"href="#module-pyFTS.common.transformations.trend"title="Permalink to this headline">¶</a></h2>
<emclass="property">class </em><codeclass="sig-prename descclassname">pyFTS.common.transformations.trend.</code><codeclass="sig-name descname">LinearTrend</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/trend.html#LinearTrend"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.trend.LinearTrend"title="Permalink to this definition">¶</a></dt>
<codeclass="sig-name descname">apply</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="n">param</span><spanclass="o">=</span><spanclass="default_value">None</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/trend.html#LinearTrend.apply"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.trend.LinearTrend.apply"title="Permalink to this definition">¶</a></dt>
<dd><p>Apply the transformation on input data</p>
<dlclass="field-list simple">
<dtclass="field-odd">Parameters</dt>
<ddclass="field-odd"><ulclass="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>
<dtclass="field-even">Returns</dt>
<ddclass="field-even"><p>numpy array with transformed data</p>
<codeclass="sig-name descname">data_field</code><aclass="headerlink"href="#pyFTS.common.transformations.trend.LinearTrend.data_field"title="Permalink to this definition">¶</a></dt>
<dd><p>The Pandas Dataframe column to use as data</p>
<codeclass="sig-name descname">datetime_mask</code><aclass="headerlink"href="#pyFTS.common.transformations.trend.LinearTrend.datetime_mask"title="Permalink to this definition">¶</a></dt>
<dd><p>The Pandas Dataframe mask for datetime indexes</p>
<codeclass="sig-name descname">generate_indexes</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="n">value</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/trend.html#LinearTrend.generate_indexes"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.trend.LinearTrend.generate_indexes"title="Permalink to this definition">¶</a></dt>
<codeclass="sig-name descname">increment</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">value</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/trend.html#LinearTrend.increment"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.trend.LinearTrend.increment"title="Permalink to this definition">¶</a></dt>
<codeclass="sig-name descname">index_field</code><aclass="headerlink"href="#pyFTS.common.transformations.trend.LinearTrend.index_field"title="Permalink to this definition">¶</a></dt>
<dd><p>The Pandas Dataframe column to use as index</p>
<codeclass="sig-name descname">index_type</code><aclass="headerlink"href="#pyFTS.common.transformations.trend.LinearTrend.index_type"title="Permalink to this definition">¶</a></dt>
<dd><p>The type of the time index used to train the regression coefficients. Available types are: field, datetime</p>
<codeclass="sig-name descname">inverse</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="n">param</span><spanclass="o">=</span><spanclass="default_value">None</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/trend.html#LinearTrend.inverse"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.trend.LinearTrend.inverse"title="Permalink to this definition">¶</a></dt>
<codeclass="sig-name descname">model</code><aclass="headerlink"href="#pyFTS.common.transformations.trend.LinearTrend.model"title="Permalink to this definition">¶</a></dt>
<codeclass="sig-name descname">train</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em>, <emclass="sig-param"><spanclass="o">**</span><spanclass="n">kwargs</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/trend.html#LinearTrend.train"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.trend.LinearTrend.train"title="Permalink to this definition">¶</a></dt>
<codeclass="sig-name descname">trend</code><spanclass="sig-paren">(</span><emclass="sig-param"><spanclass="n">data</span></em><spanclass="sig-paren">)</span><aclass="reference internal"href="_modules/pyFTS/common/transformations/trend.html#LinearTrend.trend"><spanclass="viewcode-link">[source]</span></a><aclass="headerlink"href="#pyFTS.common.transformations.trend.LinearTrend.trend"title="Permalink to this definition">¶</a></dt>