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<div class="section" id="pyfts-partitioners-package">
<h1>pyFTS.partitioners package<a class="headerlink" href="#pyfts-partitioners-package" title="Permalink to this headline"></a></h1>
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<div class="section" id="module-pyFTS.partitioners">
<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-pyFTS.partitioners" title="Permalink to this headline"></a></h2>
<p>Module for pyFTS Universe of Discourse partitioners.</p>
</div>
<div class="section" id="submodules">
<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline"></a></h2>
</div>
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<div class="section" id="module-pyFTS.partitioners.partitioner">
<span id="pyfts-partitioners-partitioner-module"></span><h2>pyFTS.partitioners.partitioner module<a class="headerlink" href="#module-pyFTS.partitioners.partitioner" title="Permalink to this headline"></a></h2>
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<dl class="py class">
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<dt id="pyFTS.partitioners.partitioner.Partitioner">
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<em class="property">class </em><code class="sig-prename descclassname">pyFTS.partitioners.partitioner.</code><code class="sig-name descname">Partitioner</code><span class="sig-paren">(</span><em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/partitioner.html#Partitioner"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner" title="Permalink to this definition"></a></dt>
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<dd><p>Bases: <a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.9)"><code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></a></p>
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<p>Universe of Discourse partitioner. Split data on several fuzzy sets</p>
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<dl class="py method">
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<dt id="pyFTS.partitioners.partitioner.Partitioner.build">
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<code class="sig-name descname">build</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/partitioner.html#Partitioner.build"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.build" title="Permalink to this definition"></a></dt>
<dd><p>Perform the partitioning of the Universe of Discourse</p>
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<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">
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<dt id="pyFTS.partitioners.partitioner.Partitioner.build_index">
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<code class="sig-name descname">build_index</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/partitioner.html#Partitioner.build_index"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.build_index" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
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<dl class="py method">
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<dt id="pyFTS.partitioners.partitioner.Partitioner.check_bounds">
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<code class="sig-name descname">check_bounds</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/partitioner.html#Partitioner.check_bounds"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.check_bounds" title="Permalink to this definition"></a></dt>
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<dd><p>Check if the input data is outside the known Universe of Discourse and, if it is, round it to the closest
fuzzy set.</p>
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<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>data</strong> input data to be verified</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>the index of the closest fuzzy set when data is outside de universe of discourse or None if</p>
</dd>
</dl>
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<p>the data is inside the UoD.</p>
</dd></dl>
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<dl class="py method">
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<dt id="pyFTS.partitioners.partitioner.Partitioner.defuzzyfy">
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<code class="sig-name descname">defuzzyfy</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">values</span></em>, <em class="sig-param"><span class="n">mode</span><span class="o">=</span><span class="default_value">'both'</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/partitioner.html#Partitioner.defuzzyfy"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.defuzzyfy" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
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<dl class="py method">
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<dt id="pyFTS.partitioners.partitioner.Partitioner.extractor">
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<code class="sig-name descname">extractor</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/partitioner.html#Partitioner.extractor"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.extractor" title="Permalink to this definition"></a></dt>
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<dd><p>Extract a single primitive type from an structured instance</p>
</dd></dl>
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<dl class="py method">
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<dt id="pyFTS.partitioners.partitioner.Partitioner.fuzzyfy">
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<code class="sig-name descname">fuzzyfy</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/partitioner.html#Partitioner.fuzzyfy"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.fuzzyfy" title="Permalink to this definition"></a></dt>
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<dd><p>Fuzzyfy the input data according to this partitioner fuzzy sets.</p>
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<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>
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</ul>
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</dd>
</dl>
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<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>
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<dl class="py method">
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<dt id="pyFTS.partitioners.partitioner.Partitioner.get_name">
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<code class="sig-name descname">get_name</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">counter</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/partitioner.html#Partitioner.get_name"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.get_name" title="Permalink to this definition"></a></dt>
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<dd><p>Find the name of the fuzzy set given its counter id.</p>
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<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>counter</strong> The number of the fuzzy set</p>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>String</p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt id="pyFTS.partitioners.partitioner.Partitioner.kdtree">
<code class="sig-name descname">kdtree</code><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.kdtree" title="Permalink to this definition"></a></dt>
<dd><p>A spatial index to help in fuzzyfication</p>
</dd></dl>
<dl class="py attribute">
<dt id="pyFTS.partitioners.partitioner.Partitioner.lower_margin">
<code class="sig-name descname">lower_margin</code><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.lower_margin" title="Permalink to this definition"></a></dt>
<dd><p>Specific lower exceeding margins for the known UoD. The default value is the self.margin parameter</p>
</dd></dl>
<dl class="py method">
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<dt id="pyFTS.partitioners.partitioner.Partitioner.lower_set">
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<code class="sig-name descname">lower_set</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/partitioner.html#Partitioner.lower_set"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.lower_set" title="Permalink to this definition"></a></dt>
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<dd><p>Return the fuzzy set on lower bound of the universe of discourse.</p>
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<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p>Fuzzy Set</p>
</dd>
</dl>
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</dd></dl>
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<dl class="py attribute">
<dt id="pyFTS.partitioners.partitioner.Partitioner.margin">
<code class="sig-name descname">margin</code><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.margin" title="Permalink to this definition"></a></dt>
<dd><p>The upper and lower exceeding margins for the known UoD. The default value is .1</p>
</dd></dl>
<dl class="py attribute">
<dt id="pyFTS.partitioners.partitioner.Partitioner.membership_function">
<code class="sig-name descname">membership_function</code><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.membership_function" title="Permalink to this definition"></a></dt>
<dd><p>Fuzzy membership function (pyFTS.common.Membership)</p>
</dd></dl>
<dl class="py attribute">
<dt id="pyFTS.partitioners.partitioner.Partitioner.name">
<code class="sig-name descname">name</code><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.name" title="Permalink to this definition"></a></dt>
<dd><p>partitioner name</p>
</dd></dl>
<dl class="py attribute">
<dt id="pyFTS.partitioners.partitioner.Partitioner.ordered_sets">
<code class="sig-name descname">ordered_sets</code><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.ordered_sets" title="Permalink to this definition"></a></dt>
<dd><p>A ordered list of the fuzzy sets names, sorted by their middle point</p>
</dd></dl>
<dl class="py attribute">
<dt id="pyFTS.partitioners.partitioner.Partitioner.partitions">
<code class="sig-name descname">partitions</code><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.partitions" title="Permalink to this definition"></a></dt>
<dd><p>The number of universe of discourse partitions, i.e., the number of fuzzy sets that will be created</p>
</dd></dl>
<dl class="py method">
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<dt id="pyFTS.partitioners.partitioner.Partitioner.plot">
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<code class="sig-name descname">plot</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">ax</span></em>, <em class="sig-param"><span class="n">rounding</span><span class="o">=</span><span class="default_value">0</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/partitioner.html#Partitioner.plot"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.plot" title="Permalink to this definition"></a></dt>
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<dd><p>Plot the partitioning using the Matplotlib axis ax</p>
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<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><p><strong>ax</strong> Matplotlib axis</p>
</dd>
</dl>
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</dd></dl>
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<dl class="py method">
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<dt id="pyFTS.partitioners.partitioner.Partitioner.plot_set">
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<code class="sig-name descname">plot_set</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">ax</span></em>, <em class="sig-param"><span class="n">s</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/partitioner.html#Partitioner.plot_set"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.plot_set" title="Permalink to this definition"></a></dt>
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<dd><p>Plot an isolate fuzzy set on Matplotlib axis</p>
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<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>ax</strong> Matplotlib axis</p></li>
<li><p><strong>s</strong> Fuzzy Set</p></li>
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</ul>
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</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt id="pyFTS.partitioners.partitioner.Partitioner.prefix">
<code class="sig-name descname">prefix</code><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.prefix" title="Permalink to this definition"></a></dt>
<dd><p>prefix of auto generated partition names</p>
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</dd></dl>
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<dl class="py method">
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<dt id="pyFTS.partitioners.partitioner.Partitioner.search">
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<code class="sig-name descname">search</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/partitioner.html#Partitioner.search"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.search" title="Permalink to this definition"></a></dt>
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<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>
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<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>
<li><p><strong>results</strong> the number of nearest fuzzy sets to return</p></li>
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</ul>
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</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the nearest fuzzy sets</p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt id="pyFTS.partitioners.partitioner.Partitioner.setnames">
<code class="sig-name descname">setnames</code><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.setnames" title="Permalink to this definition"></a></dt>
<dd><p>list of partitions names. If None is given the partitions will be auto named with prefix</p>
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</dd></dl>
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<dl class="py attribute">
<dt id="pyFTS.partitioners.partitioner.Partitioner.transformation">
<code class="sig-name descname">transformation</code><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.transformation" title="Permalink to this definition"></a></dt>
<dd><p>data transformation to be applied on data</p>
</dd></dl>
<dl class="py attribute">
<dt id="pyFTS.partitioners.partitioner.Partitioner.type">
<code class="sig-name descname">type</code><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.type" title="Permalink to this definition"></a></dt>
<dd><p>The type of fuzzy sets that are generated by this partitioner</p>
</dd></dl>
<dl class="py attribute">
<dt id="pyFTS.partitioners.partitioner.Partitioner.upper_margin">
<code class="sig-name descname">upper_margin</code><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.upper_margin" title="Permalink to this definition"></a></dt>
<dd><p>Specific upper exceeding margins for the known UoD. The default value is the self.margin parameter</p>
</dd></dl>
<dl class="py method">
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<dt id="pyFTS.partitioners.partitioner.Partitioner.upper_set">
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<code class="sig-name descname">upper_set</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/partitioner.html#Partitioner.upper_set"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.upper_set" title="Permalink to this definition"></a></dt>
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<dd><p>Return the fuzzy set on upper bound of the universe of discourse.</p>
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<dl class="field-list simple">
<dt class="field-odd">Returns</dt>
<dd class="field-odd"><p>Fuzzy Set</p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt id="pyFTS.partitioners.partitioner.Partitioner.variable">
<code class="sig-name descname">variable</code><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.variable" title="Permalink to this definition"></a></dt>
<dd><p>In a multivariate context, the variable that contains this partitioner</p>
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</dd></dl>
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</dd></dl>
</div>
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<div class="section" id="module-pyFTS.partitioners.CMeans">
<span id="pyfts-partitioners-cmeans-module"></span><h2>pyFTS.partitioners.CMeans module<a class="headerlink" href="#module-pyFTS.partitioners.CMeans" title="Permalink to this headline"></a></h2>
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<dl class="py class">
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<dt id="pyFTS.partitioners.CMeans.CMeansPartitioner">
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<em class="property">class </em><code class="sig-prename descclassname">pyFTS.partitioners.CMeans.</code><code class="sig-name descname">CMeansPartitioner</code><span class="sig-paren">(</span><em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/CMeans.html#CMeansPartitioner"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.CMeans.CMeansPartitioner" title="Permalink to this definition"></a></dt>
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<dd><p>Bases: <a class="reference internal" href="#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>
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<dl class="py method">
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<dt id="pyFTS.partitioners.CMeans.CMeansPartitioner.build">
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<code class="sig-name descname">build</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/CMeans.html#CMeansPartitioner.build"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.CMeans.CMeansPartitioner.build" title="Permalink to this definition"></a></dt>
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<dd><p>Perform the partitioning of the Universe of Discourse</p>
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<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>
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</dd></dl>
</dd></dl>
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<dl class="py function">
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<dt id="pyFTS.partitioners.CMeans.c_means">
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<code class="sig-prename descclassname">pyFTS.partitioners.CMeans.</code><code class="sig-name descname">c_means</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">k</span></em>, <em class="sig-param"><span class="n">dados</span></em>, <em class="sig-param"><span class="n">tam</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/CMeans.html#c_means"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.CMeans.c_means" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
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<dl class="py function">
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<dt id="pyFTS.partitioners.CMeans.distance">
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<code class="sig-prename descclassname">pyFTS.partitioners.CMeans.</code><code class="sig-name descname">distance</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em>, <em class="sig-param"><span class="n">y</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/CMeans.html#distance"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.CMeans.distance" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
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</div>
<div class="section" id="module-pyFTS.partitioners.Entropy">
<span id="pyfts-partitioners-entropy-module"></span><h2>pyFTS.partitioners.Entropy module<a class="headerlink" href="#module-pyFTS.partitioners.Entropy" title="Permalink to this headline"></a></h2>
<p>C. H. Cheng, R. J. Chang, and C. A. Yeh, “Entropy-based and trapezoidal fuzzification-based fuzzy time series approach for forecasting IT project cost,”
Technol. Forecast. Social Change, vol. 73, no. 5, pp. 524542, Jun. 2006.</p>
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<dl class="py class">
<dt id="pyFTS.partitioners.Entropy.EntropyPartitioner">
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<em class="property">class </em><code class="sig-prename descclassname">pyFTS.partitioners.Entropy.</code><code class="sig-name descname">EntropyPartitioner</code><span class="sig-paren">(</span><em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Entropy.html#EntropyPartitioner"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Entropy.EntropyPartitioner" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="#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>Huarng Entropy Partitioner</p>
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<dl class="py method">
<dt id="pyFTS.partitioners.Entropy.EntropyPartitioner.build">
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<code class="sig-name descname">build</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Entropy.html#EntropyPartitioner.build"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Entropy.EntropyPartitioner.build" title="Permalink to this definition"></a></dt>
<dd><p>Perform the partitioning of the Universe of Discourse</p>
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<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>
</dd></dl>
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<dl class="py function">
<dt id="pyFTS.partitioners.Entropy.PMF">
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<code class="sig-prename descclassname">pyFTS.partitioners.Entropy.</code><code class="sig-name descname">PMF</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="n">threshold</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Entropy.html#PMF"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Entropy.PMF" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
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<dl class="py function">
<dt id="pyFTS.partitioners.Entropy.bestSplit">
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<code class="sig-prename descclassname">pyFTS.partitioners.Entropy.</code><code class="sig-name descname">bestSplit</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="n">npart</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Entropy.html#bestSplit"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Entropy.bestSplit" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
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<dl class="py function">
<dt id="pyFTS.partitioners.Entropy.entropy">
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<code class="sig-prename descclassname">pyFTS.partitioners.Entropy.</code><code class="sig-name descname">entropy</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="n">threshold</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Entropy.html#entropy"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Entropy.entropy" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
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<dl class="py function">
<dt id="pyFTS.partitioners.Entropy.informationGain">
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<code class="sig-prename descclassname">pyFTS.partitioners.Entropy.</code><code class="sig-name descname">informationGain</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="n">thres1</span></em>, <em class="sig-param"><span class="n">thres2</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Entropy.html#informationGain"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Entropy.informationGain" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
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<dl class="py function">
<dt id="pyFTS.partitioners.Entropy.splitAbove">
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<code class="sig-prename descclassname">pyFTS.partitioners.Entropy.</code><code class="sig-name descname">splitAbove</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="n">threshold</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Entropy.html#splitAbove"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Entropy.splitAbove" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
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<dl class="py function">
<dt id="pyFTS.partitioners.Entropy.splitBelow">
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<code class="sig-prename descclassname">pyFTS.partitioners.Entropy.</code><code class="sig-name descname">splitBelow</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="n">threshold</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Entropy.html#splitBelow"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Entropy.splitBelow" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</div>
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<div class="section" id="module-pyFTS.partitioners.FCM">
<span id="pyfts-partitioners-fcm-module"></span><h2>pyFTS.partitioners.FCM module<a class="headerlink" href="#module-pyFTS.partitioners.FCM" title="Permalink to this headline"></a></h2>
<p>S. T. Li, Y. C. Cheng, and S. Y. Lin, “A FCM-based deterministic forecasting model for fuzzy time series,”
Comput. Math. Appl., vol. 56, no. 12, pp. 30523063, Dec. 2008. DOI: 10.1016/j.camwa.2008.07.033.</p>
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<dl class="py class">
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<dt id="pyFTS.partitioners.FCM.FCMPartitioner">
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<em class="property">class </em><code class="sig-prename descclassname">pyFTS.partitioners.FCM.</code><code class="sig-name descname">FCMPartitioner</code><span class="sig-paren">(</span><em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/FCM.html#FCMPartitioner"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.FCM.FCMPartitioner" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="#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>
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<dl class="py method">
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<dt id="pyFTS.partitioners.FCM.FCMPartitioner.build">
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<code class="sig-name descname">build</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/FCM.html#FCMPartitioner.build"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.FCM.FCMPartitioner.build" title="Permalink to this definition"></a></dt>
<dd><p>Perform the partitioning of the Universe of Discourse</p>
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<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>
</dd></dl>
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<dl class="py function">
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<dt id="pyFTS.partitioners.FCM.fuzzy_cmeans">
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<code class="sig-prename descclassname">pyFTS.partitioners.FCM.</code><code class="sig-name descname">fuzzy_cmeans</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">k</span></em>, <em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="n">size</span></em>, <em class="sig-param"><span class="n">m</span></em>, <em class="sig-param"><span class="n">deltadist</span><span class="o">=</span><span class="default_value">0.001</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/FCM.html#fuzzy_cmeans"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.FCM.fuzzy_cmeans" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
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<dl class="py function">
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<dt id="pyFTS.partitioners.FCM.fuzzy_distance">
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<code class="sig-prename descclassname">pyFTS.partitioners.FCM.</code><code class="sig-name descname">fuzzy_distance</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">x</span></em>, <em class="sig-param"><span class="n">y</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/FCM.html#fuzzy_distance"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.FCM.fuzzy_distance" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
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<dl class="py function">
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<dt id="pyFTS.partitioners.FCM.membership">
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<code class="sig-prename descclassname">pyFTS.partitioners.FCM.</code><code class="sig-name descname">membership</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">val</span></em>, <em class="sig-param"><span class="n">vals</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/FCM.html#membership"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.FCM.membership" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</div>
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<div class="section" id="module-pyFTS.partitioners.Grid">
<span id="pyfts-partitioners-grid-module"></span><h2>pyFTS.partitioners.Grid module<a class="headerlink" href="#module-pyFTS.partitioners.Grid" title="Permalink to this headline"></a></h2>
<p>Even Length Grid Partitioner</p>
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<dl class="py class">
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<dt id="pyFTS.partitioners.Grid.GridPartitioner">
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<em class="property">class </em><code class="sig-prename descclassname">pyFTS.partitioners.Grid.</code><code class="sig-name descname">GridPartitioner</code><span class="sig-paren">(</span><em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Grid.html#GridPartitioner"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Grid.GridPartitioner" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="#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>
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<p>Even Length Grid Partitioner</p>
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<dl class="py method">
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<dt id="pyFTS.partitioners.Grid.GridPartitioner.build">
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<code class="sig-name descname">build</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Grid.html#GridPartitioner.build"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Grid.GridPartitioner.build" title="Permalink to this definition"></a></dt>
<dd><p>Perform the partitioning of the Universe of Discourse</p>
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<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>
</dd></dl>
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<dl class="py class">
<dt id="pyFTS.partitioners.Grid.PreFixedGridPartitioner">
<em class="property">class </em><code class="sig-prename descclassname">pyFTS.partitioners.Grid.</code><code class="sig-name descname">PreFixedGridPartitioner</code><span class="sig-paren">(</span><em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Grid.html#PreFixedGridPartitioner"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Grid.PreFixedGridPartitioner" title="Permalink to this definition"></a></dt>
<dd><p>Bases: <a class="reference internal" href="#pyFTS.partitioners.Grid.GridPartitioner" title="pyFTS.partitioners.Grid.GridPartitioner"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.partitioners.Grid.GridPartitioner</span></code></a></p>
<p>Prefixed UoD with Even Length Grid Partitioner</p>
</dd></dl>
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</div>
<div class="section" id="module-pyFTS.partitioners.Huarng">
<span id="pyfts-partitioners-huarng-module"></span><h2>pyFTS.partitioners.Huarng module<a class="headerlink" href="#module-pyFTS.partitioners.Huarng" title="Permalink to this headline"></a></h2>
<p>K. H. Huarng, “Effective lengths of intervals to improve forecasting in fuzzy time series,”
Fuzzy Sets Syst., vol. 123, no. 3, pp. 387394, Nov. 2001.</p>
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<dl class="py class">
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<dt id="pyFTS.partitioners.Huarng.HuarngPartitioner">
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<em class="property">class </em><code class="sig-prename descclassname">pyFTS.partitioners.Huarng.</code><code class="sig-name descname">HuarngPartitioner</code><span class="sig-paren">(</span><em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Huarng.html#HuarngPartitioner"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Huarng.HuarngPartitioner" title="Permalink to this definition"></a></dt>
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<dd><p>Bases: <a class="reference internal" href="#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>Huarng Empirical Partitioner</p>
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<dl class="py method">
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<dt id="pyFTS.partitioners.Huarng.HuarngPartitioner.build">
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<code class="sig-name descname">build</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Huarng.html#HuarngPartitioner.build"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Huarng.HuarngPartitioner.build" title="Permalink to this definition"></a></dt>
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<dd><p>Perform the partitioning of the Universe of Discourse</p>
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<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>
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</dd></dl>
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</dd></dl>
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</div>
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<div class="section" id="module-pyFTS.partitioners.Singleton">
<span id="pyfts-partitioners-singleton-module"></span><h2>pyFTS.partitioners.Singleton module<a class="headerlink" href="#module-pyFTS.partitioners.Singleton" title="Permalink to this headline"></a></h2>
<p>Even Length Grid Partitioner</p>
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<dl class="py class">
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<dt id="pyFTS.partitioners.Singleton.SingletonPartitioner">
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<em class="property">class </em><code class="sig-prename descclassname">pyFTS.partitioners.Singleton.</code><code class="sig-name descname">SingletonPartitioner</code><span class="sig-paren">(</span><em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Singleton.html#SingletonPartitioner"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Singleton.SingletonPartitioner" title="Permalink to this definition"></a></dt>
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<dd><p>Bases: <a class="reference internal" href="#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>Singleton Partitioner</p>
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<dl class="py method">
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<dt id="pyFTS.partitioners.Singleton.SingletonPartitioner.build">
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<code class="sig-name descname">build</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Singleton.html#SingletonPartitioner.build"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Singleton.SingletonPartitioner.build" title="Permalink to this definition"></a></dt>
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<dd><p>Perform the partitioning of the Universe of Discourse</p>
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<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>
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</dd></dl>
</dd></dl>
</div>
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<div class="section" id="module-pyFTS.partitioners.Simple">
<span id="pyfts-partitioners-simple-module"></span><h2>pyFTS.partitioners.Simple module<a class="headerlink" href="#module-pyFTS.partitioners.Simple" title="Permalink to this headline"></a></h2>
<p>Simple Partitioner for manually informed fuzzy sets</p>
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<dl class="py class">
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<dt id="pyFTS.partitioners.Simple.SimplePartitioner">
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<em class="property">class </em><code class="sig-prename descclassname">pyFTS.partitioners.Simple.</code><code class="sig-name descname">SimplePartitioner</code><span class="sig-paren">(</span><em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Simple.html#SimplePartitioner"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Simple.SimplePartitioner" title="Permalink to this definition"></a></dt>
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<dd><p>Bases: <a class="reference internal" href="#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>Simple Partitioner for manually informed fuzzy sets</p>
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<dl class="py method">
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<dt id="pyFTS.partitioners.Simple.SimplePartitioner.append">
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<code class="sig-name descname">append</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">name</span></em>, <em class="sig-param"><span class="n">mf</span></em>, <em class="sig-param"><span class="n">parameters</span></em>, <em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Simple.html#SimplePartitioner.append"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Simple.SimplePartitioner.append" title="Permalink to this definition"></a></dt>
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<dd><p>Append a new partition (fuzzy set) to the partitioner</p>
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<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><ul class="simple">
<li><p><strong>name</strong> Fuzzy set name</p></li>
<li><p><strong>mf</strong> One of the pyFTS.common.Membership functions</p></li>
<li><p><strong>parameters</strong> A list with the parameters for the membership function</p></li>
<li><p><strong>kwargs</strong> Optional arguments for the fuzzy set</p></li>
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</ul>
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</dd>
</dl>
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</dd></dl>
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<dl class="py method">
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<dt id="pyFTS.partitioners.Simple.SimplePartitioner.append_complex">
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<code class="sig-name descname">append_complex</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">fs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Simple.html#SimplePartitioner.append_complex"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Simple.SimplePartitioner.append_complex" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
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</dd></dl>
</div>
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<div class="section" id="module-pyFTS.partitioners.SubClust">
<span id="pyfts-partitioners-subclust-module"></span><h2>pyFTS.partitioners.SubClust module<a class="headerlink" href="#module-pyFTS.partitioners.SubClust" title="Permalink to this headline"></a></h2>
<p>Chiu, Stephen L. “Fuzzy model identification based on cluster estimation.” Journal of Intelligent &amp; fuzzy systems 2.3 (1994): 267-278.</p>
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<dl class="py class">
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<dt id="pyFTS.partitioners.SubClust.SubClustPartitioner">
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<em class="property">class </em><code class="sig-prename descclassname">pyFTS.partitioners.SubClust.</code><code class="sig-name descname">SubClustPartitioner</code><span class="sig-paren">(</span><em class="sig-param"><span class="o">**</span><span class="n">kwargs</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/SubClust.html#SubClustPartitioner"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.SubClust.SubClustPartitioner" title="Permalink to this definition"></a></dt>
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<dd><p>Bases: <a class="reference internal" href="#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>Subtractive Clustering Partitioner</p>
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<dl class="py method">
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<dt id="pyFTS.partitioners.SubClust.SubClustPartitioner.build">
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<code class="sig-name descname">build</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/SubClust.html#SubClustPartitioner.build"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.SubClust.SubClustPartitioner.build" title="Permalink to this definition"></a></dt>
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<dd><p>Perform the partitioning of the Universe of Discourse</p>
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<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>
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</dd></dl>
</dd></dl>
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<dl class="py function">
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<dt id="pyFTS.partitioners.SubClust.imax">
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<code class="sig-prename descclassname">pyFTS.partitioners.SubClust.</code><code class="sig-name descname">imax</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">vec</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/SubClust.html#imax"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.SubClust.imax" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
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<dl class="py function">
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<dt id="pyFTS.partitioners.SubClust.subclust">
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<code class="sig-prename descclassname">pyFTS.partitioners.SubClust.</code><code class="sig-name descname">subclust</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="n">ra</span></em>, <em class="sig-param"><span class="n">rb</span></em>, <em class="sig-param"><span class="n">eps_sup</span></em>, <em class="sig-param"><span class="n">eps_inf</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/SubClust.html#subclust"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.SubClust.subclust" title="Permalink to this definition"></a></dt>
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<dd></dd></dl>
</div>
<div class="section" id="module-pyFTS.partitioners.Util">
<span id="pyfts-partitioners-util-module"></span><h2>pyFTS.partitioners.Util module<a class="headerlink" href="#module-pyFTS.partitioners.Util" title="Permalink to this headline"></a></h2>
<p>Facility methods for pyFTS partitioners module</p>
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<dl class="py function">
<dt id="pyFTS.partitioners.Util.explore_partitioners">
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<code class="sig-prename descclassname">pyFTS.partitioners.Util.</code><code class="sig-name descname">explore_partitioners</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="n">npart</span></em>, <em class="sig-param"><span class="n">methods</span><span class="o">=</span><span class="default_value">None</span></em>, <em class="sig-param"><span class="n">mf</span><span class="o">=</span><span class="default_value">None</span></em>, <em class="sig-param"><span class="n">transformation</span><span class="o">=</span><span class="default_value">None</span></em>, <em class="sig-param"><span class="n">size</span><span class="o">=</span><span class="default_value">[12, 10]</span></em>, <em class="sig-param"><span class="n">save</span><span class="o">=</span><span class="default_value">False</span></em>, <em class="sig-param"><span class="n">file</span><span class="o">=</span><span class="default_value">None</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Util.html#explore_partitioners"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Util.explore_partitioners" title="Permalink to this definition"></a></dt>
<dd><p>Create partitioners for the mf membership functions and npart partitions and show the partitioning images.
:data: Time series data
:npart: Maximum number of partitions of the universe of discourse
:methods: A list with the partitioning methods to be used
:mf: A list with the membership functions to be used
:transformation: a transformation to be used in partitioner
:size: list, the size of the output image [width, height]
:save: boolean, if the image will be saved on disk
:file: string, the file path to save the image
:return: the list of the built partitioners</p>
</dd></dl>
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<dl class="py function">
<dt id="pyFTS.partitioners.Util.plot_partitioners">
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<code class="sig-prename descclassname">pyFTS.partitioners.Util.</code><code class="sig-name descname">plot_partitioners</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="n">objs</span></em>, <em class="sig-param"><span class="n">tam</span><span class="o">=</span><span class="default_value">[12, 10]</span></em>, <em class="sig-param"><span class="n">save</span><span class="o">=</span><span class="default_value">False</span></em>, <em class="sig-param"><span class="n">file</span><span class="o">=</span><span class="default_value">None</span></em>, <em class="sig-param"><span class="n">axis</span><span class="o">=</span><span class="default_value">None</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Util.html#plot_partitioners"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Util.plot_partitioners" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
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<dl class="py function">
<dt id="pyFTS.partitioners.Util.plot_sets">
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<code class="sig-prename descclassname">pyFTS.partitioners.Util.</code><code class="sig-name descname">plot_sets</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="n">sets</span></em>, <em class="sig-param"><span class="n">titles</span></em>, <em class="sig-param"><span class="n">size</span><span class="o">=</span><span class="default_value">[12, 10]</span></em>, <em class="sig-param"><span class="n">save</span><span class="o">=</span><span class="default_value">False</span></em>, <em class="sig-param"><span class="n">file</span><span class="o">=</span><span class="default_value">None</span></em>, <em class="sig-param"><span class="n">axis</span><span class="o">=</span><span class="default_value">None</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Util.html#plot_sets"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Util.plot_sets" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</div>
<div class="section" id="module-pyFTS.partitioners.parallel_util">
<span id="pyfts-partitioners-parallel-util-module"></span><h2>pyFTS.partitioners.parallel_util module<a class="headerlink" href="#module-pyFTS.partitioners.parallel_util" title="Permalink to this headline"></a></h2>
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<dl class="py function">
<dt id="pyFTS.partitioners.parallel_util.explore_partitioners">
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<code class="sig-prename descclassname">pyFTS.partitioners.parallel_util.</code><code class="sig-name descname">explore_partitioners</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">data</span></em>, <em class="sig-param"><span class="n">npart</span></em>, <em class="sig-param"><span class="n">methods</span><span class="o">=</span><span class="default_value">None</span></em>, <em class="sig-param"><span class="n">mf</span><span class="o">=</span><span class="default_value">None</span></em>, <em class="sig-param"><span class="n">tam</span><span class="o">=</span><span class="default_value">[12, 10]</span></em>, <em class="sig-param"><span class="n">save</span><span class="o">=</span><span class="default_value">False</span></em>, <em class="sig-param"><span class="n">file</span><span class="o">=</span><span class="default_value">None</span></em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/parallel_util.html#explore_partitioners"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.parallel_util.explore_partitioners" title="Permalink to this definition"></a></dt>
<dd></dd></dl>
</div>
</div>
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<h3><a href="index.html">Table of Contents</a></h3>
<ul>
<li><a class="reference internal" href="#">pyFTS.partitioners package</a><ul>
<li><a class="reference internal" href="#module-pyFTS.partitioners">Module contents</a></li>
<li><a class="reference internal" href="#submodules">Submodules</a></li>
<li><a class="reference internal" href="#module-pyFTS.partitioners.partitioner">pyFTS.partitioners.partitioner module</a></li>
<li><a class="reference internal" href="#module-pyFTS.partitioners.CMeans">pyFTS.partitioners.CMeans module</a></li>
<li><a class="reference internal" href="#module-pyFTS.partitioners.Entropy">pyFTS.partitioners.Entropy module</a></li>
<li><a class="reference internal" href="#module-pyFTS.partitioners.FCM">pyFTS.partitioners.FCM module</a></li>
<li><a class="reference internal" href="#module-pyFTS.partitioners.Grid">pyFTS.partitioners.Grid module</a></li>
<li><a class="reference internal" href="#module-pyFTS.partitioners.Huarng">pyFTS.partitioners.Huarng module</a></li>
<li><a class="reference internal" href="#module-pyFTS.partitioners.Singleton">pyFTS.partitioners.Singleton module</a></li>
<li><a class="reference internal" href="#module-pyFTS.partitioners.Simple">pyFTS.partitioners.Simple module</a></li>
<li><a class="reference internal" href="#module-pyFTS.partitioners.SubClust">pyFTS.partitioners.SubClust module</a></li>
<li><a class="reference internal" href="#module-pyFTS.partitioners.Util">pyFTS.partitioners.Util module</a></li>
<li><a class="reference internal" href="#module-pyFTS.partitioners.parallel_util">pyFTS.partitioners.parallel_util module</a></li>
</ul>
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</ul>
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