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Time Series sample classification infrastructure; WMVFTS is the first method with a functional implementation
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Time Series sample classification infrastructure; WMVFTS is the first method with a functional implementation
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<section id="pyfts-models-multivariate-package">
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<h1>pyFTS.models.multivariate package<a class="headerlink" href="#pyfts-models-multivariate-package" title="Permalink to this headline"></a></h1>
Time Series sample classification infrastructure; WMVFTS is the first method with a functional implementation
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<section id="module-pyFTS.models.multivariate">
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<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>
Time Series sample classification infrastructure; WMVFTS is the first method with a functional implementation
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</section>
<section id="submodules">
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<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline"></a></h2>
Time Series sample classification infrastructure; WMVFTS is the first method with a functional implementation
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</section>
<section id="module-pyFTS.models.multivariate.FLR">
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<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>
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<dl class="py class">
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<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>
Time Series sample classification infrastructure; WMVFTS is the first method with a functional implementation
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<dd><p>Bases: <a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.11)"><code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></a></p>
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<p>Multivariate Fuzzy Logical Relationship</p>
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<dl class="py method">
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<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>
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<dd></dd></dl>
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<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>
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<dd></dd></dl>
</dd></dl>
Time Series sample classification infrastructure; WMVFTS is the first method with a functional implementation
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</section>
<section id="module-pyFTS.models.multivariate.common">
Sphinx documentation for ReadTheDocs site
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<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>
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<dl class="py class">
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<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>
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<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>
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<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>
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<dd><p>Appends a new fuzzy set from a new variable</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>variable</strong> – an multivariate.variable instance</p></li>
<li><p><strong>set</strong> – an common.FuzzySet instance</p></li>
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</ul>
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</dd>
</dl>
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</dd></dl>
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<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>
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<dd><p>Calculate the membership value of a given input</p>
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<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 method">
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<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>
Single partitioner; documentation update
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<dd></dd></dl>
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</dd></dl>
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<dl class="py function">
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<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>
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<dd></dd></dl>
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<dl class="py function">
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<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>
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<dd></dd></dl>
Time Series sample classification infrastructure; WMVFTS is the first method with a functional implementation
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</section>
<section id="pyfts-models-multivariate-variable-module">
<h2>pyFTS.models.multivariate.variable module<a class="headerlink" href="#pyfts-models-multivariate-variable-module" title="Permalink to this headline"></a></h2>
</section>
<section id="module-pyFTS.models.multivariate.flrg">
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<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>
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<dl class="py class">
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<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>
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<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>
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<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>
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<dd></dd></dl>
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<dl class="py method">
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<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>
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<dd><p>Returns the lower bound value for the RHS fuzzy sets</p>
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<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">
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<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>
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<dd><p>Returns the membership value of the FLRG for the input data</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 data</p></li>
<li><p><strong>sets</strong> – fuzzy sets</p></li>
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</ul>
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</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>the membership value</p>
</dd>
</dl>
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</dd></dl>
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<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>
Updating documentiation
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<dd><p>Returns the upper bound value for the RHS fuzzy sets</p>
Documentation update
2020-08-19 00:06:41 +04:00
<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">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<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>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<dd></dd></dl>
</dd></dl>
Time Series sample classification infrastructure; WMVFTS is the first method with a functional implementation
2023-05-25 02:46:07 +04:00
</section>
<section id="module-pyFTS.models.multivariate.partitioner">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<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>
Documentation update
2020-08-19 00:06:41 +04:00
<dl class="py class">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<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>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
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<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>
Documentation update
2020-08-19 00:06:41 +04:00
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<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>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<dd></dd></dl>
Documentation update
2020-08-19 00:06:41 +04:00
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<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>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<dd><p>Perform the partitioning of the Universe of Discourse</p>
Documentation update
2020-08-19 00:06:41 +04:00
<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">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<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>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<dd></dd></dl>
Documentation update
2020-08-19 00:06:41 +04:00
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<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>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<dd></dd></dl>
Documentation update
2020-08-19 00:06:41 +04:00
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<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>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<dd></dd></dl>
Documentation update
2020-08-19 00:06:41 +04:00
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<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>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<dd><p>Fuzzyfy the input data according to this partitioner fuzzy sets.</p>
Documentation update
2020-08-19 00:06:41 +04:00
<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>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
</ul>
Documentation update
2020-08-19 00:06:41 +04:00
</dd>
</dl>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<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>
Documentation update
2020-08-19 00:06:41 +04:00
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<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>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
<dd></dd></dl>
Documentation update
2020-08-19 00:06:41 +04:00
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<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>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<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>
Documentation update
2020-08-19 00:06:41 +04:00
<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>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
</ul>
Documentation update
2020-08-19 00:06:41 +04:00
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><p>a list with the nearest fuzzy sets</p>
</dd>
</dl>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
</dd></dl>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
</dd></dl>
Time Series sample classification infrastructure; WMVFTS is the first method with a functional implementation
2023-05-25 02:46:07 +04:00
</section>
<section id="module-pyFTS.models.multivariate.grid">
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<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>
Documentation update
2020-08-19 00:06:41 +04:00
<dl class="py class">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<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>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<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>
Documentation update
2019-04-22 17:01:58 +04:00
<p>A cartesian product of all fuzzy sets of all variables</p>
Documentation update
2020-08-19 00:06:41 +04:00
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<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>
Documentation update
2019-04-22 17:01:58 +04:00
<dd><p>Perform the partitioning of the Universe of Discourse</p>
Documentation update
2020-08-19 00:06:41 +04:00
<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">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<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>
Documentation update
2019-06-21 18:34:49 +04:00
<dd></dd></dl>
Documentation update
2019-04-22 17:01:58 +04:00
</dd></dl>
Documentation update
2020-08-19 00:06:41 +04:00
<dl class="py class">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<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>
New benchmarks.Tests module; Improvements on forecast_ahead_* function; Documentation update
2019-06-06 18:04:20 +04:00
<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>
Documentation update
2019-04-22 17:01:58 +04:00
<p>Create combinations of fuzzy sets of the variables on demand, incrementally increasing the
multivariate fuzzy set base.</p>
Documentation update
2020-08-19 00:06:41 +04:00
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<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>
Documentation update
2019-04-22 17:01:58 +04:00
<dd><p>Fuzzyfy the input data according to this partitioner fuzzy sets.</p>
Documentation update
2020-08-19 00:06:41 +04:00
<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>
Documentation update
2019-04-22 17:01:58 +04:00
</ul>
Documentation update
2020-08-19 00:06:41 +04:00
</dd>
</dl>
Documentation update
2019-04-22 17:01:58 +04:00
<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>
Documentation update
2020-08-19 00:06:41 +04:00
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<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>
Documentation update
2019-04-22 17:01:58 +04:00
<dd></dd></dl>
Documentation update
2020-08-19 00:06:41 +04:00
<dl class="py method">
Fixing documentation and type hints
2022-04-10 21:32:24 +04:00
<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>
Documentation update
2019-04-22 17:01:58 +04:00
<dd></dd></dl>
</dd></dl>
Time Series sample classification infrastructure; WMVFTS is the first method with a functional implementation
2023-05-25 02:46:07 +04:00
</section>
<section id="pyfts-models-multivariate-mvfts-module">
<h2>pyFTS.models.multivariate.mvfts module<a class="headerlink" href="#pyfts-models-multivariate-mvfts-module" title="Permalink to this headline"></a></h2>
</section>
<section id="pyfts-models-multivariate-wmvfts-module">
<h2>pyFTS.models.multivariate.wmvfts module<a class="headerlink" href="#pyfts-models-multivariate-wmvfts-module" title="Permalink to this headline"></a></h2>
</section>
<section id="pyfts-models-multivariate-cmvfts-module">
<h2>pyFTS.models.multivariate.cmvfts module<a class="headerlink" href="#pyfts-models-multivariate-cmvfts-module" title="Permalink to this headline"></a></h2>
</section>
<section id="pyfts-models-multivariate-granular-module">
<h2>pyFTS.models.multivariate.granular module<a class="headerlink" href="#pyfts-models-multivariate-granular-module" title="Permalink to this headline"></a></h2>
</section>
</section>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
Documentation update
2020-08-19 00:06:41 +04:00
<div class="clearer"></div>
Sphinx documentation for ReadTheDocs site
2018-08-30 09:05:29 +04:00
</div>
</div>
</div>
Documentation update
2020-08-19 00:06:41 +04:00
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
<div class="sphinxsidebarwrapper">
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Time Series sample classification infrastructure; WMVFTS is the first method with a functional implementation
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<h3><a href="index.html">Table of Contents</a></h3>
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<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>
Time Series sample classification infrastructure; WMVFTS is the first method with a functional implementation
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<li><a class="reference internal" href="#pyfts-models-multivariate-variable-module">pyFTS.models.multivariate.variable module</a></li>
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<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>
Time Series sample classification infrastructure; WMVFTS is the first method with a functional implementation
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<li><a class="reference internal" href="#pyfts-models-multivariate-mvfts-module">pyFTS.models.multivariate.mvfts module</a></li>
<li><a class="reference internal" href="#pyfts-models-multivariate-wmvfts-module">pyFTS.models.multivariate.wmvfts module</a></li>
<li><a class="reference internal" href="#pyfts-models-multivariate-cmvfts-module">pyFTS.models.multivariate.cmvfts module</a></li>
<li><a class="reference internal" href="#pyfts-models-multivariate-granular-module">pyFTS.models.multivariate.granular module</a></li>
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Time Series sample classification infrastructure; WMVFTS is the first method with a functional implementation
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Time Series sample classification infrastructure; WMVFTS is the first method with a functional implementation
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