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<div class="section" id="pyfts-models-multivariate-package">
<h1>pyFTS.models.multivariate package<a class="headerlink" href="#pyfts-models-multivariate-package" title="Permalink to this headline"></a></h1>
<div class="section" id="module-pyFTS.models.multivariate">
<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-pyFTS.models.multivariate" title="Permalink to this headline"></a></h2>
<p>Multivariate Fuzzy Time Series methods</p>
</div>
<div class="section" id="submodules">
<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline"></a></h2>
</div>
<div class="section" id="module-pyFTS.models.multivariate.FLR">
<span id="pyfts-models-multivariate-flr-module"></span><h2>pyFTS.models.multivariate.FLR module<a class="headerlink" href="#module-pyFTS.models.multivariate.FLR" title="Permalink to this headline"></a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.FLR.FLR">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.multivariate.FLR.</span></span><span class="sig-name descname"><span class="pre">FLR</span></span><a class="reference internal" href="_modules/pyFTS/models/multivariate/FLR.html#FLR"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.FLR.FLR" 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 v3.10)"><code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></a></p>
<p>Multivariate Fuzzy Logical Relationship</p>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.FLR.FLR.set_lhs">
<span class="sig-name descname"><span class="pre">set_lhs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">var</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">set</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/FLR.html#FLR.set_lhs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.FLR.FLR.set_lhs" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.FLR.FLR.set_rhs">
<span class="sig-name descname"><span class="pre">set_rhs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">set</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/FLR.html#FLR.set_rhs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.FLR.FLR.set_rhs" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
</div>
<div class="section" id="module-pyFTS.models.multivariate.common">
<span id="pyfts-models-multivariate-common-module"></span><h2>pyFTS.models.multivariate.common module<a class="headerlink" href="#module-pyFTS.models.multivariate.common" title="Permalink to this headline"></a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.common.MultivariateFuzzySet">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.multivariate.common.</span></span><span class="sig-name descname"><span class="pre">MultivariateFuzzySet</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/models/multivariate/common.html#MultivariateFuzzySet"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.common.MultivariateFuzzySet" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.Composite.FuzzySet" title="pyFTS.common.Composite.FuzzySet"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.Composite.FuzzySet</span></code></a></p>
<p>Multivariate Composite Fuzzy Set</p>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.common.MultivariateFuzzySet.alpha">
<span class="sig-name descname"><span class="pre">alpha</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.common.MultivariateFuzzySet.alpha" title="Permalink to this definition"></a></dt>
<dd><p>The alpha cut value</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.common.MultivariateFuzzySet.append_set">
<span class="sig-name descname"><span class="pre">append_set</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">variable</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">set</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/common.html#MultivariateFuzzySet.append_set"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.common.MultivariateFuzzySet.append_set" title="Permalink to this definition"></a></dt>
<dd><p>Appends a new fuzzy set from a new variable</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>variable</strong> – an multivariate.variable instance</p></li>
<li><p><strong>set</strong> – an common.FuzzySet instance</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.common.MultivariateFuzzySet.centroid">
<span class="sig-name descname"><span class="pre">centroid</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.common.MultivariateFuzzySet.centroid" title="Permalink to this definition"></a></dt>
<dd><p>The fuzzy set center of mass (or midpoint)</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.common.MultivariateFuzzySet.membership">
<span class="sig-name descname"><span class="pre">membership</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/common.html#MultivariateFuzzySet.membership"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.common.MultivariateFuzzySet.membership" title="Permalink to this definition"></a></dt>
<dd><p>Calculate the membership value of a given input</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>x</strong> – input value</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>membership value of x at this fuzzy set</p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.common.MultivariateFuzzySet.name">
<span class="sig-name descname"><span class="pre">name</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.common.MultivariateFuzzySet.name" title="Permalink to this definition"></a></dt>
<dd><p>The fuzzy set name</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.common.MultivariateFuzzySet.parameters">
<span class="sig-name descname"><span class="pre">parameters</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.common.MultivariateFuzzySet.parameters" title="Permalink to this definition"></a></dt>
<dd><p>The parameters of the membership function</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.common.MultivariateFuzzySet.set_target_variable">
<span class="sig-name descname"><span class="pre">set_target_variable</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">variable</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/common.html#MultivariateFuzzySet.set_target_variable"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.common.MultivariateFuzzySet.set_target_variable" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.common.MultivariateFuzzySet.type">
<span class="sig-name descname"><span class="pre">type</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.common.MultivariateFuzzySet.type" title="Permalink to this definition"></a></dt>
<dd><p>The fuzzy set type (common, composite, nonstationary, etc)</p>
</dd></dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.common.fuzzyfy_instance">
<span class="sig-prename descclassname"><span class="pre">pyFTS.models.multivariate.common.</span></span><span class="sig-name descname"><span class="pre">fuzzyfy_instance</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data_point</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">var</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">tuples</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/common.html#fuzzyfy_instance"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.common.fuzzyfy_instance" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.common.fuzzyfy_instance_clustered">
<span class="sig-prename descclassname"><span class="pre">pyFTS.models.multivariate.common.</span></span><span class="sig-name descname"><span class="pre">fuzzyfy_instance_clustered</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">data_point</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">cluster</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/models/multivariate/common.html#fuzzyfy_instance_clustered"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.common.fuzzyfy_instance_clustered" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</div>
<div class="section" id="module-pyFTS.models.multivariate.variable">
<span id="pyfts-models-multivariate-variable-module"></span><h2>pyFTS.models.multivariate.variable module<a class="headerlink" href="#module-pyFTS.models.multivariate.variable" title="Permalink to this headline"></a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.variable.Variable">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.multivariate.variable.</span></span><span class="sig-name descname"><span class="pre">Variable</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">name</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/models/multivariate/variable.html#Variable"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable" 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 v3.10)"><code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></a></p>
<p>A variable of a fuzzy time series multivariate model. Each variable contains its own
transformations and partitioners.</p>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.variable.Variable.alias">
<span class="sig-name descname"><span class="pre">alias</span></span><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.alias" title="Permalink to this definition"></a></dt>
<dd><p>A string with the alias of the variable</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.variable.Variable.alpha_cut">
<span class="sig-name descname"><span class="pre">alpha_cut</span></span><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.alpha_cut" title="Permalink to this definition"></a></dt>
<dd><p>Minimal membership value to be considered on fuzzyfication process</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.variable.Variable.apply_inverse_transformations">
<span class="sig-name descname"><span class="pre">apply_inverse_transformations</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/models/multivariate/variable.html#Variable.apply_inverse_transformations"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.apply_inverse_transformations" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.variable.Variable.apply_transformations">
<span class="sig-name descname"><span class="pre">apply_transformations</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/models/multivariate/variable.html#Variable.apply_transformations"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.apply_transformations" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.variable.Variable.build">
<span class="sig-name descname"><span class="pre">build</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/models/multivariate/variable.html#Variable.build"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.build" title="Permalink to this definition"></a></dt>
<dd><dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>kwargs</strong> – </p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p></p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.variable.Variable.data_label">
<span class="sig-name descname"><span class="pre">data_label</span></span><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.data_label" title="Permalink to this definition"></a></dt>
<dd><p>A string with the column name on DataFrame</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.variable.Variable.data_type">
<span class="sig-name descname"><span class="pre">data_type</span></span><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.data_type" title="Permalink to this definition"></a></dt>
<dd><p>The type of the data column on Pandas Dataframe</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.variable.Variable.mask">
<span class="sig-name descname"><span class="pre">mask</span></span><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.mask" title="Permalink to this definition"></a></dt>
<dd><p>The mask for format the data column on Pandas Dataframe</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.variable.Variable.name">
<span class="sig-name descname"><span class="pre">name</span></span><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.name" title="Permalink to this definition"></a></dt>
<dd><p>A string with the name of the variable</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.variable.Variable.partitioner">
<span class="sig-name descname"><span class="pre">partitioner</span></span><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.partitioner" title="Permalink to this definition"></a></dt>
<dd><p>UoD partitioner for the variable data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.variable.Variable.transformation">
<span class="sig-name descname"><span class="pre">transformation</span></span><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.transformation" title="Permalink to this definition"></a></dt>
<dd><p>Pre processing transformation for the variable</p>
</dd></dl>
</dd></dl>
</div>
<div class="section" id="module-pyFTS.models.multivariate.flrg">
<span id="pyfts-models-multivariate-flrg-module"></span><h2>pyFTS.models.multivariate.flrg module<a class="headerlink" href="#module-pyFTS.models.multivariate.flrg" title="Permalink to this headline"></a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.flrg.FLRG">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.multivariate.flrg.</span></span><span class="sig-name descname"><span class="pre">FLRG</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/models/multivariate/flrg.html#FLRG"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.flrg.FLRG" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.flrg.FLRG" title="pyFTS.common.flrg.FLRG"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.flrg.FLRG</span></code></a></p>
<p>Multivariate Fuzzy Logical Rule Group</p>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.flrg.FLRG.append_rhs">
<span class="sig-name descname"><span class="pre">append_rhs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">fset</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/models/multivariate/flrg.html#FLRG.append_rhs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.flrg.FLRG.append_rhs" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.flrg.FLRG.get_lower">
<span class="sig-name descname"><span class="pre">get_lower</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sets</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/flrg.html#FLRG.get_lower"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.flrg.FLRG.get_lower" title="Permalink to this definition"></a></dt>
<dd><p>Returns the lower bound value for the RHS fuzzy sets</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>sets</strong> – fuzzy sets</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>lower bound value</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.flrg.FLRG.get_membership">
<span class="sig-name descname"><span class="pre">get_membership</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">variables</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/flrg.html#FLRG.get_membership"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.flrg.FLRG.get_membership" title="Permalink to this definition"></a></dt>
<dd><p>Returns the membership value of the FLRG for the 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>sets</strong> – fuzzy sets</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>the membership value</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.flrg.FLRG.get_upper">
<span class="sig-name descname"><span class="pre">get_upper</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sets</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/flrg.html#FLRG.get_upper"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.flrg.FLRG.get_upper" title="Permalink to this definition"></a></dt>
<dd><p>Returns the upper bound value for the RHS fuzzy sets</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>sets</strong> – fuzzy sets</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>upper bound value</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.flrg.FLRG.set_lhs">
<span class="sig-name descname"><span class="pre">set_lhs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">var</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">fset</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/flrg.html#FLRG.set_lhs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.flrg.FLRG.set_lhs" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
</div>
<div class="section" id="module-pyFTS.models.multivariate.partitioner">
<span id="pyfts-models-multivariate-partitioner-module"></span><h2>pyFTS.models.multivariate.partitioner module<a class="headerlink" href="#module-pyFTS.models.multivariate.partitioner" title="Permalink to this headline"></a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.partitioner.MultivariatePartitioner">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.multivariate.partitioner.</span></span><span class="sig-name descname"><span class="pre">MultivariatePartitioner</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/models/multivariate/partitioner.html#MultivariatePartitioner"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner" title="pyFTS.partitioners.partitioner.Partitioner"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.partitioners.partitioner.Partitioner</span></code></a></p>
<p>Base class for partitioners which use the MultivariateFuzzySet</p>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.partitioner.MultivariatePartitioner.append">
<span class="sig-name descname"><span class="pre">append</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">fset</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/partitioner.html#MultivariatePartitioner.append"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner.append" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.partitioner.MultivariatePartitioner.build">
<span class="sig-name descname"><span class="pre">build</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/models/multivariate/partitioner.html#MultivariatePartitioner.build"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner.build" title="Permalink to this definition"></a></dt>
<dd><p>Perform the partitioning of the Universe of Discourse</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>data</strong> – training data</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p></p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.partitioner.MultivariatePartitioner.build_index">
<span class="sig-name descname"><span class="pre">build_index</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/partitioner.html#MultivariatePartitioner.build_index"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner.build_index" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.partitioner.MultivariatePartitioner.change_target_variable">
<span class="sig-name descname"><span class="pre">change_target_variable</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">variable</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/partitioner.html#MultivariatePartitioner.change_target_variable"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner.change_target_variable" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.partitioner.MultivariatePartitioner.format_data">
<span class="sig-name descname"><span class="pre">format_data</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/models/multivariate/partitioner.html#MultivariatePartitioner.format_data"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner.format_data" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.partitioner.MultivariatePartitioner.fuzzyfy">
<span class="sig-name descname"><span class="pre">fuzzyfy</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/models/multivariate/partitioner.html#MultivariatePartitioner.fuzzyfy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner.fuzzyfy" title="Permalink to this definition"></a></dt>
<dd><p>Fuzzyfy the input data according to this partitioner fuzzy sets.</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 value to be fuzzyfied</p></li>
<li><p><strong>alpha_cut</strong> – the minimal membership value to be considered on fuzzyfication (only for mode=’sets’)</p></li>
<li><p><strong>method</strong> – the fuzzyfication method (fuzzy: all fuzzy memberships, maximum: only the maximum membership)</p></li>
<li><p><strong>mode</strong> – the fuzzyfication mode (sets: return the fuzzy sets names, vector: return a vector with the membership</p></li>
</ul>
</dd>
</dl>
<p>values for all fuzzy sets, both: return a list with tuples (fuzzy set, membership value) )</p>
<p>:returns a list with the fuzzyfied values, depending on the mode</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.partitioner.MultivariatePartitioner.prune">
<span class="sig-name descname"><span class="pre">prune</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/partitioner.html#MultivariatePartitioner.prune"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner.prune" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.partitioner.MultivariatePartitioner.search">
<span class="sig-name descname"><span class="pre">search</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/models/multivariate/partitioner.html#MultivariatePartitioner.search"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner.search" title="Permalink to this definition"></a></dt>
<dd><p>Perform a search for the nearest fuzzy sets of the point ‘data’. This function were designed to work with several
overlapped fuzzy sets.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – the value to search for the nearest fuzzy sets</p></li>
<li><p><strong>type</strong> – the return type: ‘index’ for the fuzzy set indexes or ‘name’ for fuzzy set names.</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the nearest fuzzy sets</p>
</dd>
</dl>
</dd></dl>
</dd></dl>
</div>
<div class="section" id="module-pyFTS.models.multivariate.grid">
<span id="pyfts-models-multivariate-grid-module"></span><h2>pyFTS.models.multivariate.grid module<a class="headerlink" href="#module-pyFTS.models.multivariate.grid" title="Permalink to this headline"></a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.grid.GridCluster">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.multivariate.grid.</span></span><span class="sig-name descname"><span class="pre">GridCluster</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/models/multivariate/grid.html#GridCluster"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.grid.GridCluster" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner" title="pyFTS.models.multivariate.partitioner.MultivariatePartitioner"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.multivariate.partitioner.MultivariatePartitioner</span></code></a></p>
<p>A cartesian product of all fuzzy sets of all variables</p>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.grid.GridCluster.build">
<span class="sig-name descname"><span class="pre">build</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/models/multivariate/grid.html#GridCluster.build"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.grid.GridCluster.build" title="Permalink to this definition"></a></dt>
<dd><p>Perform the partitioning of the Universe of Discourse</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>data</strong> – training data</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p></p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.grid.GridCluster.defuzzyfy">
<span class="sig-name descname"><span class="pre">defuzzyfy</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">values</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">mode</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">'both'</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/grid.html#GridCluster.defuzzyfy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.grid.GridCluster.defuzzyfy" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.grid.IncrementalGridCluster">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.multivariate.grid.</span></span><span class="sig-name descname"><span class="pre">IncrementalGridCluster</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/models/multivariate/grid.html#IncrementalGridCluster"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.grid.IncrementalGridCluster" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.multivariate.partitioner.MultivariatePartitioner" title="pyFTS.models.multivariate.partitioner.MultivariatePartitioner"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.multivariate.partitioner.MultivariatePartitioner</span></code></a></p>
<p>Create combinations of fuzzy sets of the variables on demand, incrementally increasing the
multivariate fuzzy set base.</p>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.grid.IncrementalGridCluster.fuzzyfy">
<span class="sig-name descname"><span class="pre">fuzzyfy</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/models/multivariate/grid.html#IncrementalGridCluster.fuzzyfy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.grid.IncrementalGridCluster.fuzzyfy" title="Permalink to this definition"></a></dt>
<dd><p>Fuzzyfy the input data according to this partitioner fuzzy sets.</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 value to be fuzzyfied</p></li>
<li><p><strong>alpha_cut</strong> – the minimal membership value to be considered on fuzzyfication (only for mode=’sets’)</p></li>
<li><p><strong>method</strong> – the fuzzyfication method (fuzzy: all fuzzy memberships, maximum: only the maximum membership)</p></li>
<li><p><strong>mode</strong> – the fuzzyfication mode (sets: return the fuzzy sets names, vector: return a vector with the membership</p></li>
</ul>
</dd>
</dl>
<p>values for all fuzzy sets, both: return a list with tuples (fuzzy set, membership value) )</p>
<p>:returns a list with the fuzzyfied values, depending on the mode</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.grid.IncrementalGridCluster.incremental_search">
<span class="sig-name descname"><span class="pre">incremental_search</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/models/multivariate/grid.html#IncrementalGridCluster.incremental_search"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.grid.IncrementalGridCluster.incremental_search" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.grid.IncrementalGridCluster.prune">
<span class="sig-name descname"><span class="pre">prune</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/grid.html#IncrementalGridCluster.prune"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.grid.IncrementalGridCluster.prune" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
</div>
<div class="section" id="module-pyFTS.models.multivariate.mvfts">
<span id="pyfts-models-multivariate-mvfts-module"></span><h2>pyFTS.models.multivariate.mvfts module<a class="headerlink" href="#module-pyFTS.models.multivariate.mvfts" title="Permalink to this headline"></a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.multivariate.mvfts.</span></span><span class="sig-name descname"><span class="pre">MVFTS</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/models/multivariate/mvfts.html#MVFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.fts.FTS" title="pyFTS.common.fts.FTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.fts.FTS</span></code></a></p>
<p>Multivariate extension of Chen’s ConventionalFTS method</p>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.alpha_cut">
<span class="sig-name descname"><span class="pre">alpha_cut</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.alpha_cut" title="Permalink to this definition"></a></dt>
<dd><p>A float with the minimal membership to be considered on fuzzyfication process</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.append_transformation">
<span class="sig-name descname"><span class="pre">append_transformation</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">transformation</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/models/multivariate/mvfts.html#MVFTS.append_transformation"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.append_transformation" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.append_variable">
<span class="sig-name descname"><span class="pre">append_variable</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">var</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.append_variable"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.append_variable" title="Permalink to this definition"></a></dt>
<dd><p>Append a new endogenous variable to the model</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>var</strong> – variable object</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p></p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.apply_transformations">
<span class="sig-name descname"><span class="pre">apply_transformations</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">params</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="n"><span class="pre">updateUoD</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</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/models/multivariate/mvfts.html#MVFTS.apply_transformations"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.apply_transformations" title="Permalink to this definition"></a></dt>
<dd><p>Apply the data transformations for data preprocessing</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>params</strong> – transformation parameters</p></li>
<li><p><strong>updateUoD</strong> – </p></li>
<li><p><strong>kwargs</strong> – </p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>preprocessed data</p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.auto_update">
<span class="sig-name descname"><span class="pre">auto_update</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.auto_update" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating that model is incremental</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.benchmark_only">
<span class="sig-name descname"><span class="pre">benchmark_only</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.benchmark_only" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating a façade for external (non-FTS) model used on benchmarks or ensembles.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.clone_parameters">
<span class="sig-name descname"><span class="pre">clone_parameters</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">model</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.clone_parameters"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.clone_parameters" title="Permalink to this definition"></a></dt>
<dd><p>Import the parameters values from other model</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>model</strong> – a model to clone the parameters</p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.detail">
<span class="sig-name descname"><span class="pre">detail</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.detail" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model detailed information</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.dump">
<span class="sig-name descname"><span class="pre">dump</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.flrgs">
<span class="sig-name descname"><span class="pre">flrgs</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><span class="pre">dict</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.flrgs" title="Permalink to this definition"></a></dt>
<dd><p>The list of Fuzzy Logical Relationship Groups - FLRG</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.forecast">
<span class="sig-name descname"><span class="pre">forecast</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/models/multivariate/mvfts.html#MVFTS.forecast"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.forecast" title="Permalink to this definition"></a></dt>
<dd><p>Point forecast one step ahead</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>kwargs</strong> – model specific parameters</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the forecasted values</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.forecast_ahead">
<span class="sig-name descname"><span class="pre">forecast_ahead</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">steps</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/models/multivariate/mvfts.html#MVFTS.forecast_ahead"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.forecast_ahead" title="Permalink to this definition"></a></dt>
<dd><p>Point forecast from 1 to H steps ahead, where H is given by the steps parameter</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>steps</strong> – the number of steps ahead to forecast (default: 1)</p></li>
<li><p><strong>start_at</strong> – in the multi step forecasting, the index of the data where to start forecasting (default: 0)</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the forecasted values</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.forecast_ahead_interval">
<span class="sig-name descname"><span class="pre">forecast_ahead_interval</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">steps</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/models/multivariate/mvfts.html#MVFTS.forecast_ahead_interval"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.forecast_ahead_interval" title="Permalink to this definition"></a></dt>
<dd><p>Interval forecast from 1 to H steps ahead, where H is given by the steps parameter</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>steps</strong> – the number of steps ahead to forecast</p></li>
<li><p><strong>start_at</strong> – in the multi step forecasting, the index of the data where to start forecasting (default: 0)</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the forecasted intervals</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.forecast_interval">
<span class="sig-name descname"><span class="pre">forecast_interval</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/models/multivariate/mvfts.html#MVFTS.forecast_interval"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.forecast_interval" title="Permalink to this definition"></a></dt>
<dd><p>Interval forecast one step ahead</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>kwargs</strong> – model specific parameters</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the prediction intervals</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.format_data">
<span class="sig-name descname"><span class="pre">format_data</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/models/multivariate/mvfts.html#MVFTS.format_data"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.format_data" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.generate_flrg">
<span class="sig-name descname"><span class="pre">generate_flrg</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">flrs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.generate_flrg"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.generate_flrg" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.generate_flrs">
<span class="sig-name descname"><span class="pre">generate_flrs</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/models/multivariate/mvfts.html#MVFTS.generate_flrs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.generate_flrs" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.generate_lhs_flrs">
<span class="sig-name descname"><span class="pre">generate_lhs_flrs</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/models/multivariate/mvfts.html#MVFTS.generate_lhs_flrs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.generate_lhs_flrs" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.has_interval_forecasting">
<span class="sig-name descname"><span class="pre">has_interval_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.has_interval_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports interval forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.has_point_forecasting">
<span class="sig-name descname"><span class="pre">has_point_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.has_point_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports point forecasting, default: True</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.has_probability_forecasting">
<span class="sig-name descname"><span class="pre">has_probability_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.has_probability_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support probabilistic forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.has_seasonality">
<span class="sig-name descname"><span class="pre">has_seasonality</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.has_seasonality" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports seasonal indexers, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.is_clustered">
<span class="sig-name descname"><span class="pre">is_clustered</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.is_clustered" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), but works like
a monovariate method, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.is_high_order">
<span class="sig-name descname"><span class="pre">is_high_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.is_high_order" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support orders greater than 1, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.is_multivariate">
<span class="sig-name descname"><span class="pre">is_multivariate</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.is_multivariate" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.is_time_variant">
<span class="sig-name descname"><span class="pre">is_time_variant</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.is_time_variant" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if this model is time variant</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.is_wrapper">
<span class="sig-name descname"><span class="pre">is_wrapper</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.is_wrapper" title="Permalink to this definition"></a></dt>
<dd><p>Indicates that this model is a wrapper for other(s) method(s)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.lags">
<span class="sig-name descname"><span class="pre">lags</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.lags" title="Permalink to this definition"></a></dt>
<dd><p>The list of lag indexes for high order models</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.log">
<span class="sig-name descname"><span class="pre">log</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">pd.DataFrame</span></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.log" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.max_lag">
<span class="sig-name descname"><span class="pre">max_lag</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.max_lag" title="Permalink to this definition"></a></dt>
<dd><p>A integer indicating the largest lag used by the model. This value also indicates the minimum number of past lags
needed to forecast a single step ahead</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.min_order">
<span class="sig-name descname"><span class="pre">min_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.min_order" title="Permalink to this definition"></a></dt>
<dd><p>In high order models, this integer value indicates the minimal order supported for the model, default: 1</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.name">
<span class="sig-name descname"><span class="pre">name</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.name" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model name</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.order">
<span class="sig-name descname"><span class="pre">order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.order" title="Permalink to this definition"></a></dt>
<dd><p>A integer with the model order (number of past lags are used on forecasting)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.original_max">
<span class="sig-name descname"><span class="pre">original_max</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.original_max" title="Permalink to this definition"></a></dt>
<dd><p>A float with the upper limit of the Universe of Discourse, the maximal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.original_min">
<span class="sig-name descname"><span class="pre">original_min</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.original_min" title="Permalink to this definition"></a></dt>
<dd><p>A float with the lower limit of the Universe of Discourse, the minimal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.partitioner">
<span class="sig-name descname"><span class="pre">partitioner</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner" title="pyFTS.partitioners.partitioner.Partitioner"><span class="pre">partitioner.Partitioner</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.partitioner" title="Permalink to this definition"></a></dt>
<dd><p>A pyFTS.partitioners.Partitioner object with the Universe of Discourse partitioner used on the model. This is a mandatory dependecy.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.shortname">
<span class="sig-name descname"><span class="pre">shortname</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.shortname" title="Permalink to this definition"></a></dt>
<dd><p>A string with a short name or alias for the model</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.standard_horizon">
<span class="sig-name descname"><span class="pre">standard_horizon</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.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/models/multivariate/mvfts.html#MVFTS.train"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.train" title="Permalink to this definition"></a></dt>
<dd><p>Method specific parameter fitting</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – training time series data</p></li>
<li><p><strong>kwargs</strong> – Method specific parameters</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.transformations">
<span class="sig-name descname"><span class="pre">transformations</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><span class="pre">transformation.Transformation</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.transformations" title="Permalink to this definition"></a></dt>
<dd><p>A list with the data transformations (common.Transformations) applied on model pre and post processing, default: []</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.transformations_param">
<span class="sig-name descname"><span class="pre">transformations_param</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.transformations_param" title="Permalink to this definition"></a></dt>
<dd><p>A list with the specific parameters for each data transformation</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.MVFTS.uod_clip">
<span class="sig-name descname"><span class="pre">uod_clip</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.uod_clip" title="Permalink to this definition"></a></dt>
<dd><p>Flag indicating if the test data will be clipped inside the training Universe of Discourse</p>
</dd></dl>
</dd></dl>
<dl class="py function">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.mvfts.product_dict">
<span class="sig-prename descclassname"><span class="pre">pyFTS.models.multivariate.mvfts.</span></span><span class="sig-name descname"><span class="pre">product_dict</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/models/multivariate/mvfts.html#product_dict"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.product_dict" title="Permalink to this definition"></a></dt>
<dd><p>Code by Seth Johnson
:param kwargs:
:return:</p>
</dd></dl>
</div>
<div class="section" id="module-pyFTS.models.multivariate.wmvfts">
<span id="pyfts-models-multivariate-wmvfts-module"></span><h2>pyFTS.models.multivariate.wmvfts module<a class="headerlink" href="#module-pyFTS.models.multivariate.wmvfts" title="Permalink to this headline"></a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedFLRG">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.multivariate.wmvfts.</span></span><span class="sig-name descname"><span class="pre">WeightedFLRG</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/models/multivariate/wmvfts.html#WeightedFLRG"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedFLRG" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.multivariate.flrg.FLRG" title="pyFTS.models.multivariate.flrg.FLRG"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.multivariate.flrg.FLRG</span></code></a></p>
<p>Weighted Multivariate Fuzzy Logical Rule Group</p>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedFLRG.append_rhs">
<span class="sig-name descname"><span class="pre">append_rhs</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">fset</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/models/multivariate/wmvfts.html#WeightedFLRG.append_rhs"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedFLRG.append_rhs" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_lower">
<span class="sig-name descname"><span class="pre">get_lower</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sets</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/wmvfts.html#WeightedFLRG.get_lower"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_lower" title="Permalink to this definition"></a></dt>
<dd><p>Returns the lower bound value for the RHS fuzzy sets</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>sets</strong> – fuzzy sets</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>lower bound value</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_midpoint">
<span class="sig-name descname"><span class="pre">get_midpoint</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sets</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/wmvfts.html#WeightedFLRG.get_midpoint"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_midpoint" title="Permalink to this definition"></a></dt>
<dd><p>Returns the midpoint value for the RHS fuzzy sets</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>sets</strong> – fuzzy sets</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>the midpoint value</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_upper">
<span class="sig-name descname"><span class="pre">get_upper</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">sets</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/wmvfts.html#WeightedFLRG.get_upper"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_upper" title="Permalink to this definition"></a></dt>
<dd><p>Returns the upper bound value for the RHS fuzzy sets</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>sets</strong> – fuzzy sets</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>upper bound value</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedFLRG.weights">
<span class="sig-name descname"><span class="pre">weights</span></span><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/wmvfts.html#WeightedFLRG.weights"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedFLRG.weights" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.multivariate.wmvfts.</span></span><span class="sig-name descname"><span class="pre">WeightedMVFTS</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/models/multivariate/wmvfts.html#WeightedMVFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.multivariate.mvfts.MVFTS" title="pyFTS.models.multivariate.mvfts.MVFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.multivariate.mvfts.MVFTS</span></code></a></p>
<p>Weighted Multivariate FTS</p>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.alpha_cut">
<span class="sig-name descname"><span class="pre">alpha_cut</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.alpha_cut" title="Permalink to this definition"></a></dt>
<dd><p>A float with the minimal membership to be considered on fuzzyfication process</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.auto_update">
<span class="sig-name descname"><span class="pre">auto_update</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.auto_update" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating that model is incremental</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.benchmark_only">
<span class="sig-name descname"><span class="pre">benchmark_only</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.benchmark_only" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating a façade for external (non-FTS) model used on benchmarks or ensembles.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.detail">
<span class="sig-name descname"><span class="pre">detail</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.detail" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model detailed information</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.dump">
<span class="sig-name descname"><span class="pre">dump</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.flrgs">
<span class="sig-name descname"><span class="pre">flrgs</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><span class="pre">dict</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.flrgs" title="Permalink to this definition"></a></dt>
<dd><p>The list of Fuzzy Logical Relationship Groups - FLRG</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.generate_flrg">
<span class="sig-name descname"><span class="pre">generate_flrg</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">flrs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/wmvfts.html#WeightedMVFTS.generate_flrg"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.generate_flrg" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.has_interval_forecasting">
<span class="sig-name descname"><span class="pre">has_interval_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.has_interval_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports interval forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.has_point_forecasting">
<span class="sig-name descname"><span class="pre">has_point_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.has_point_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports point forecasting, default: True</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.has_probability_forecasting">
<span class="sig-name descname"><span class="pre">has_probability_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.has_probability_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support probabilistic forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.has_seasonality">
<span class="sig-name descname"><span class="pre">has_seasonality</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.has_seasonality" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports seasonal indexers, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.is_clustered">
<span class="sig-name descname"><span class="pre">is_clustered</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.is_clustered" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), but works like
a monovariate method, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.is_high_order">
<span class="sig-name descname"><span class="pre">is_high_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.is_high_order" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support orders greater than 1, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.is_multivariate">
<span class="sig-name descname"><span class="pre">is_multivariate</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.is_multivariate" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.is_time_variant">
<span class="sig-name descname"><span class="pre">is_time_variant</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.is_time_variant" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if this model is time variant</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.is_wrapper">
<span class="sig-name descname"><span class="pre">is_wrapper</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.is_wrapper" title="Permalink to this definition"></a></dt>
<dd><p>Indicates that this model is a wrapper for other(s) method(s)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.lags">
<span class="sig-name descname"><span class="pre">lags</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.lags" title="Permalink to this definition"></a></dt>
<dd><p>The list of lag indexes for high order models</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.log">
<span class="sig-name descname"><span class="pre">log</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">pd.DataFrame</span></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.log" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.max_lag">
<span class="sig-name descname"><span class="pre">max_lag</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.max_lag" title="Permalink to this definition"></a></dt>
<dd><p>A integer indicating the largest lag used by the model. This value also indicates the minimum number of past lags
needed to forecast a single step ahead</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.min_order">
<span class="sig-name descname"><span class="pre">min_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.min_order" title="Permalink to this definition"></a></dt>
<dd><p>In high order models, this integer value indicates the minimal order supported for the model, default: 1</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.name">
<span class="sig-name descname"><span class="pre">name</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.name" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model name</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.order">
<span class="sig-name descname"><span class="pre">order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.order" title="Permalink to this definition"></a></dt>
<dd><p>A integer with the model order (number of past lags are used on forecasting)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.original_max">
<span class="sig-name descname"><span class="pre">original_max</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.original_max" title="Permalink to this definition"></a></dt>
<dd><p>A float with the upper limit of the Universe of Discourse, the maximal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.original_min">
<span class="sig-name descname"><span class="pre">original_min</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.original_min" title="Permalink to this definition"></a></dt>
<dd><p>A float with the lower limit of the Universe of Discourse, the minimal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.partitioner">
<span class="sig-name descname"><span class="pre">partitioner</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner" title="pyFTS.partitioners.partitioner.Partitioner"><span class="pre">partitioner.Partitioner</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.partitioner" title="Permalink to this definition"></a></dt>
<dd><p>A pyFTS.partitioners.Partitioner object with the Universe of Discourse partitioner used on the model. This is a mandatory dependecy.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.shortname">
<span class="sig-name descname"><span class="pre">shortname</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.shortname" title="Permalink to this definition"></a></dt>
<dd><p>A string with a short name or alias for the model</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.standard_horizon">
<span class="sig-name descname"><span class="pre">standard_horizon</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.transformations">
<span class="sig-name descname"><span class="pre">transformations</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><span class="pre">transformation.Transformation</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.transformations" title="Permalink to this definition"></a></dt>
<dd><p>A list with the data transformations (common.Transformations) applied on model pre and post processing, default: []</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.transformations_param">
<span class="sig-name descname"><span class="pre">transformations_param</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.transformations_param" title="Permalink to this definition"></a></dt>
<dd><p>A list with the specific parameters for each data transformation</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.uod_clip">
<span class="sig-name descname"><span class="pre">uod_clip</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.uod_clip" title="Permalink to this definition"></a></dt>
<dd><p>Flag indicating if the test data will be clipped inside the training Universe of Discourse</p>
</dd></dl>
</dd></dl>
</div>
<div class="section" id="module-pyFTS.models.multivariate.cmvfts">
<span id="pyfts-models-multivariate-cmvfts-module"></span><h2>pyFTS.models.multivariate.cmvfts module<a class="headerlink" href="#module-pyFTS.models.multivariate.cmvfts" title="Permalink to this headline"></a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.multivariate.cmvfts.</span></span><span class="sig-name descname"><span class="pre">ClusteredMVFTS</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/models/multivariate/cmvfts.html#ClusteredMVFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.multivariate.mvfts.MVFTS" title="pyFTS.models.multivariate.mvfts.MVFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.multivariate.mvfts.MVFTS</span></code></a></p>
<p>Meta model for high order, clustered multivariate FTS</p>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.alpha_cut">
<span class="sig-name descname"><span class="pre">alpha_cut</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.alpha_cut" title="Permalink to this definition"></a></dt>
<dd><p>A float with the minimal membership to be considered on fuzzyfication process</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.auto_update">
<span class="sig-name descname"><span class="pre">auto_update</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.auto_update" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating that model is incremental</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.benchmark_only">
<span class="sig-name descname"><span class="pre">benchmark_only</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.benchmark_only" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating a façade for external (non-FTS) model used on benchmarks or ensembles.</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.check_data">
<span class="sig-name descname"><span class="pre">check_data</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/models/multivariate/cmvfts.html#ClusteredMVFTS.check_data"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.check_data" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.detail">
<span class="sig-name descname"><span class="pre">detail</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.detail" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model detailed information</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.dump">
<span class="sig-name descname"><span class="pre">dump</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.flrgs">
<span class="sig-name descname"><span class="pre">flrgs</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><span class="pre">dict</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.flrgs" title="Permalink to this definition"></a></dt>
<dd><p>The list of Fuzzy Logical Relationship Groups - FLRG</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast">
<span class="sig-name descname"><span class="pre">forecast</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/models/multivariate/cmvfts.html#ClusteredMVFTS.forecast"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast" title="Permalink to this definition"></a></dt>
<dd><p>Point forecast one step ahead</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>kwargs</strong> – model specific parameters</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the forecasted values</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_ahead_distribution">
<span class="sig-name descname"><span class="pre">forecast_ahead_distribution</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">steps</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/models/multivariate/cmvfts.html#ClusteredMVFTS.forecast_ahead_distribution"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_ahead_distribution" title="Permalink to this definition"></a></dt>
<dd><p>Probabilistic forecast from 1 to H steps ahead, where H is given by the steps parameter</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>steps</strong> – the number of steps ahead to forecast</p></li>
<li><p><strong>start_at</strong> – in the multi step forecasting, the index of the data where to start forecasting (default: 0)</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the forecasted Probability Distributions</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_ahead_multivariate">
<span class="sig-name descname"><span class="pre">forecast_ahead_multivariate</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">steps</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/models/multivariate/cmvfts.html#ClusteredMVFTS.forecast_ahead_multivariate"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_ahead_multivariate" title="Permalink to this definition"></a></dt>
<dd><p>Multivariate forecast n step ahead</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – Pandas dataframe with one column for each variable and with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>steps</strong> – the number of steps ahead to forecast</p></li>
<li><p><strong>start_at</strong> – in the multi step forecasting, the index of the data where to start forecasting (default: 0)</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a Pandas Dataframe object representing the forecasted values for each variable</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_distribution">
<span class="sig-name descname"><span class="pre">forecast_distribution</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/models/multivariate/cmvfts.html#ClusteredMVFTS.forecast_distribution"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_distribution" title="Permalink to this definition"></a></dt>
<dd><p>Probabilistic forecast one step ahead</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>kwargs</strong> – model specific parameters</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with probabilistic.ProbabilityDistribution objects representing the forecasted Probability Distributions</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_interval">
<span class="sig-name descname"><span class="pre">forecast_interval</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/models/multivariate/cmvfts.html#ClusteredMVFTS.forecast_interval"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_interval" title="Permalink to this definition"></a></dt>
<dd><p>Interval forecast one step ahead</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>kwargs</strong> – model specific parameters</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the prediction intervals</p>
</dd>
</dl>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_multivariate">
<span class="sig-name descname"><span class="pre">forecast_multivariate</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/models/multivariate/cmvfts.html#ClusteredMVFTS.forecast_multivariate"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast_multivariate" title="Permalink to this definition"></a></dt>
<dd><p>Multivariate forecast one step ahead</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – Pandas dataframe with one column for each variable and with the minimal length equal to the max_lag of the model</p></li>
<li><p><strong>kwargs</strong> – model specific parameters</p></li>
</ul>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a Pandas Dataframe object representing the forecasted values for each variable</p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.fts_method">
<span class="sig-name descname"><span class="pre">fts_method</span></span><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.fts_method" title="Permalink to this definition"></a></dt>
<dd><p>The FTS method to be called when a new model is build</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.fts_params">
<span class="sig-name descname"><span class="pre">fts_params</span></span><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.fts_params" title="Permalink to this definition"></a></dt>
<dd><p>The FTS method specific parameters</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.fuzzyfy">
<span class="sig-name descname"><span class="pre">fuzzyfy</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/models/multivariate/cmvfts.html#ClusteredMVFTS.fuzzyfy"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.fuzzyfy" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.has_interval_forecasting">
<span class="sig-name descname"><span class="pre">has_interval_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.has_interval_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports interval forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.has_point_forecasting">
<span class="sig-name descname"><span class="pre">has_point_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.has_point_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports point forecasting, default: True</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.has_probability_forecasting">
<span class="sig-name descname"><span class="pre">has_probability_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.has_probability_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support probabilistic forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.has_seasonality">
<span class="sig-name descname"><span class="pre">has_seasonality</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.has_seasonality" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports seasonal indexers, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.is_clustered">
<span class="sig-name descname"><span class="pre">is_clustered</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.is_clustered" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), but works like
a monovariate method, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.is_high_order">
<span class="sig-name descname"><span class="pre">is_high_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.is_high_order" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support orders greater than 1, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.is_multivariate">
<span class="sig-name descname"><span class="pre">is_multivariate</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.is_multivariate" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.is_time_variant">
<span class="sig-name descname"><span class="pre">is_time_variant</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.is_time_variant" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if this model is time variant</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.is_wrapper">
<span class="sig-name descname"><span class="pre">is_wrapper</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.is_wrapper" title="Permalink to this definition"></a></dt>
<dd><p>Indicates that this model is a wrapper for other(s) method(s)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.lags">
<span class="sig-name descname"><span class="pre">lags</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.lags" title="Permalink to this definition"></a></dt>
<dd><p>The list of lag indexes for high order models</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.log">
<span class="sig-name descname"><span class="pre">log</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">pd.DataFrame</span></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.log" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.max_lag">
<span class="sig-name descname"><span class="pre">max_lag</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.max_lag" title="Permalink to this definition"></a></dt>
<dd><p>A integer indicating the largest lag used by the model. This value also indicates the minimum number of past lags
needed to forecast a single step ahead</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.min_order">
<span class="sig-name descname"><span class="pre">min_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.min_order" title="Permalink to this definition"></a></dt>
<dd><p>In high order models, this integer value indicates the minimal order supported for the model, default: 1</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.model">
<span class="sig-name descname"><span class="pre">model</span></span><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.model" title="Permalink to this definition"></a></dt>
<dd><p>The most recent trained model</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.name">
<span class="sig-name descname"><span class="pre">name</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.name" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model name</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.order">
<span class="sig-name descname"><span class="pre">order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.order" title="Permalink to this definition"></a></dt>
<dd><p>A integer with the model order (number of past lags are used on forecasting)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.original_max">
<span class="sig-name descname"><span class="pre">original_max</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.original_max" title="Permalink to this definition"></a></dt>
<dd><p>A float with the upper limit of the Universe of Discourse, the maximal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.original_min">
<span class="sig-name descname"><span class="pre">original_min</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.original_min" title="Permalink to this definition"></a></dt>
<dd><p>A float with the lower limit of the Universe of Discourse, the minimal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.partitioner">
<span class="sig-name descname"><span class="pre">partitioner</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner" title="pyFTS.partitioners.partitioner.Partitioner"><span class="pre">partitioner.Partitioner</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.partitioner" title="Permalink to this definition"></a></dt>
<dd><p>A pyFTS.partitioners.Partitioner object with the Universe of Discourse partitioner used on the model. This is a mandatory dependecy.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.shortname">
<span class="sig-name descname"><span class="pre">shortname</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.shortname" title="Permalink to this definition"></a></dt>
<dd><p>A string with a short name or alias for the model</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.standard_horizon">
<span class="sig-name descname"><span class="pre">standard_horizon</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.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/models/multivariate/cmvfts.html#ClusteredMVFTS.train"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.train" title="Permalink to this definition"></a></dt>
<dd><p>Method specific parameter fitting</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – training time series data</p></li>
<li><p><strong>kwargs</strong> – Method specific parameters</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.transformations">
<span class="sig-name descname"><span class="pre">transformations</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><span class="pre">transformation.Transformation</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.transformations" title="Permalink to this definition"></a></dt>
<dd><p>A list with the data transformations (common.Transformations) applied on model pre and post processing, default: []</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.transformations_param">
<span class="sig-name descname"><span class="pre">transformations_param</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.transformations_param" title="Permalink to this definition"></a></dt>
<dd><p>A list with the specific parameters for each data transformation</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.uod_clip">
<span class="sig-name descname"><span class="pre">uod_clip</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.uod_clip" title="Permalink to this definition"></a></dt>
<dd><p>Flag indicating if the test data will be clipped inside the training Universe of Discourse</p>
</dd></dl>
</dd></dl>
</div>
<div class="section" id="module-pyFTS.models.multivariate.granular">
<span id="pyfts-models-multivariate-granular-module"></span><h2>pyFTS.models.multivariate.granular module<a class="headerlink" href="#module-pyFTS.models.multivariate.granular" title="Permalink to this headline"></a></h2>
<dl class="py class">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">pyFTS.models.multivariate.granular.</span></span><span class="sig-name descname"><span class="pre">GranularWMVFTS</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/models/multivariate/granular.html#GranularWMVFTS"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS" title="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.multivariate.cmvfts.ClusteredMVFTS</span></code></a></p>
<p>Granular multivariate weighted high order FTS</p>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.alpha_cut">
<span class="sig-name descname"><span class="pre">alpha_cut</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.alpha_cut" title="Permalink to this definition"></a></dt>
<dd><p>A float with the minimal membership to be considered on fuzzyfication process</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.auto_update">
<span class="sig-name descname"><span class="pre">auto_update</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.auto_update" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating that model is incremental</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.benchmark_only">
<span class="sig-name descname"><span class="pre">benchmark_only</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.benchmark_only" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating a façade for external (non-FTS) model used on benchmarks or ensembles.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.detail">
<span class="sig-name descname"><span class="pre">detail</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.detail" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model detailed information</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.dump">
<span class="sig-name descname"><span class="pre">dump</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.dump" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.flrgs">
<span class="sig-name descname"><span class="pre">flrgs</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#dict" title="(in Python v3.10)"><span class="pre">dict</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.flrgs" title="Permalink to this definition"></a></dt>
<dd><p>The list of Fuzzy Logical Relationship Groups - FLRG</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.has_interval_forecasting">
<span class="sig-name descname"><span class="pre">has_interval_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.has_interval_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports interval forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.has_point_forecasting">
<span class="sig-name descname"><span class="pre">has_point_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.has_point_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports point forecasting, default: True</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.has_probability_forecasting">
<span class="sig-name descname"><span class="pre">has_probability_forecasting</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.has_probability_forecasting" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support probabilistic forecasting, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.has_seasonality">
<span class="sig-name descname"><span class="pre">has_seasonality</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.has_seasonality" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model supports seasonal indexers, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.is_clustered">
<span class="sig-name descname"><span class="pre">is_clustered</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.is_clustered" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), but works like
a monovariate method, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.is_high_order">
<span class="sig-name descname"><span class="pre">is_high_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.is_high_order" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support orders greater than 1, default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.is_multivariate">
<span class="sig-name descname"><span class="pre">is_multivariate</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.is_multivariate" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if the model support multivariate time series (Pandas DataFrame), default: False</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.is_time_variant">
<span class="sig-name descname"><span class="pre">is_time_variant</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.is_time_variant" title="Permalink to this definition"></a></dt>
<dd><p>A boolean value indicating if this model is time variant</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.is_wrapper">
<span class="sig-name descname"><span class="pre">is_wrapper</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.is_wrapper" title="Permalink to this definition"></a></dt>
<dd><p>Indicates that this model is a wrapper for other(s) method(s)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.lags">
<span class="sig-name descname"><span class="pre">lags</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.lags" title="Permalink to this definition"></a></dt>
<dd><p>The list of lag indexes for high order models</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.log">
<span class="sig-name descname"><span class="pre">log</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><span class="pre">pd.DataFrame</span></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.log" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.max_lag">
<span class="sig-name descname"><span class="pre">max_lag</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.max_lag" title="Permalink to this definition"></a></dt>
<dd><p>A integer indicating the largest lag used by the model. This value also indicates the minimum number of past lags
needed to forecast a single step ahead</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.min_order">
<span class="sig-name descname"><span class="pre">min_order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.min_order" title="Permalink to this definition"></a></dt>
<dd><p>In high order models, this integer value indicates the minimal order supported for the model, default: 1</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.model">
<span class="sig-name descname"><span class="pre">model</span></span><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.model" title="Permalink to this definition"></a></dt>
<dd><p>The most recent trained model</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.name">
<span class="sig-name descname"><span class="pre">name</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.name" title="Permalink to this definition"></a></dt>
<dd><p>A string with the model name</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.order">
<span class="sig-name descname"><span class="pre">order</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.order" title="Permalink to this definition"></a></dt>
<dd><p>A integer with the model order (number of past lags are used on forecasting)</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.original_max">
<span class="sig-name descname"><span class="pre">original_max</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.original_max" title="Permalink to this definition"></a></dt>
<dd><p>A float with the upper limit of the Universe of Discourse, the maximal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.original_min">
<span class="sig-name descname"><span class="pre">original_min</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.10)"><span class="pre">float</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.original_min" title="Permalink to this definition"></a></dt>
<dd><p>A float with the lower limit of the Universe of Discourse, the minimal value found on training data</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.partitioner">
<span class="sig-name descname"><span class="pre">partitioner</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference internal" href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner" title="pyFTS.partitioners.partitioner.Partitioner"><span class="pre">partitioner.Partitioner</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.partitioner" title="Permalink to this definition"></a></dt>
<dd><p>A pyFTS.partitioners.Partitioner object with the Universe of Discourse partitioner used on the model. This is a mandatory dependecy.</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.shortname">
<span class="sig-name descname"><span class="pre">shortname</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.10)"><span class="pre">str</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.shortname" title="Permalink to this definition"></a></dt>
<dd><p>A string with a short name or alias for the model</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.standard_horizon">
<span class="sig-name descname"><span class="pre">standard_horizon</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.10)"><span class="pre">int</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.standard_horizon" title="Permalink to this definition"></a></dt>
<dd><p>Standard forecasting horizon (Default: 1)</p>
</dd></dl>
<dl class="py method">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.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/models/multivariate/granular.html#GranularWMVFTS.train"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.train" title="Permalink to this definition"></a></dt>
<dd><p>Method specific parameter fitting</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>data</strong> – training time series data</p></li>
<li><p><strong>kwargs</strong> – Method specific parameters</p></li>
</ul>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.transformations">
<span class="sig-name descname"><span class="pre">transformations</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a><span class="p"><span class="pre">[</span></span><a class="reference internal" href="pyFTS.common.transformations.html#pyFTS.common.transformations.transformation.Transformation" title="pyFTS.common.transformations.transformation.Transformation"><span class="pre">transformation.Transformation</span></a><span class="p"><span class="pre">]</span></span></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.transformations" title="Permalink to this definition"></a></dt>
<dd><p>A list with the data transformations (common.Transformations) applied on model pre and post processing, default: []</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.transformations_param">
<span class="sig-name descname"><span class="pre">transformations_param</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#list" title="(in Python v3.10)"><span class="pre">list</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.transformations_param" title="Permalink to this definition"></a></dt>
<dd><p>A list with the specific parameters for each data transformation</p>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="pyFTS.models.multivariate.granular.GranularWMVFTS.uod_clip">
<span class="sig-name descname"><span class="pre">uod_clip</span></span><em class="property"><span class="p"><span class="pre">:</span></span><span class="w"> </span><a class="reference external" href="https://docs.python.org/3/library/functions.html#bool" title="(in Python v3.10)"><span class="pre">bool</span></a></em><a class="headerlink" href="#pyFTS.models.multivariate.granular.GranularWMVFTS.uod_clip" title="Permalink to this definition"></a></dt>
<dd><p>Flag indicating if the test data will be clipped inside the training Universe of Discourse</p>
</dd></dl>
</dd></dl>
</div>
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<h3><a href="index.html">Table of Contents</a></h3>
<ul>
<li><a class="reference internal" href="#">pyFTS.models.multivariate package</a><ul>
<li><a class="reference internal" href="#module-pyFTS.models.multivariate">Module contents</a></li>
<li><a class="reference internal" href="#submodules">Submodules</a></li>
<li><a class="reference internal" href="#module-pyFTS.models.multivariate.FLR">pyFTS.models.multivariate.FLR module</a></li>
<li><a class="reference internal" href="#module-pyFTS.models.multivariate.common">pyFTS.models.multivariate.common module</a></li>
<li><a class="reference internal" href="#module-pyFTS.models.multivariate.variable">pyFTS.models.multivariate.variable module</a></li>
<li><a class="reference internal" href="#module-pyFTS.models.multivariate.flrg">pyFTS.models.multivariate.flrg module</a></li>
<li><a class="reference internal" href="#module-pyFTS.models.multivariate.partitioner">pyFTS.models.multivariate.partitioner module</a></li>
<li><a class="reference internal" href="#module-pyFTS.models.multivariate.grid">pyFTS.models.multivariate.grid module</a></li>
<li><a class="reference internal" href="#module-pyFTS.models.multivariate.mvfts">pyFTS.models.multivariate.mvfts module</a></li>
<li><a class="reference internal" href="#module-pyFTS.models.multivariate.wmvfts">pyFTS.models.multivariate.wmvfts module</a></li>
<li><a class="reference internal" href="#module-pyFTS.models.multivariate.cmvfts">pyFTS.models.multivariate.cmvfts module</a></li>
<li><a class="reference internal" href="#module-pyFTS.models.multivariate.granular">pyFTS.models.multivariate.granular module</a></li>
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