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#
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SPHINXOPTS =
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SPHINXPROJ = pyFTS
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# Sphinx build info version 1
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# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done.
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config: 23a83af8fc84956f406e435cfed523f9
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config: e7ed10e5c6fce8ae09ccdd825dd277b3
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tags: 645f666f9bcd5a90fca523b33c5a78b7
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<title>Overview: module code — pyFTS 1.2.3 documentation</title>
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<div class="documentwrapper">
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<div class="bodywrapper">
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<div class="body" role="main">
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<h1>All modules for which code is available</h1>
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<ul><li><a href="pyFTS/benchmarks/Measures.html">pyFTS.benchmarks.Measures</a></li>
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<li><a href="pyFTS/benchmarks/ResidualAnalysis.html">pyFTS.benchmarks.ResidualAnalysis</a></li>
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||||
<li><a href="pyFTS/benchmarks/Util.html">pyFTS.benchmarks.Util</a></li>
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||||
<li><a href="pyFTS/benchmarks/arima.html">pyFTS.benchmarks.arima</a></li>
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||||
<li><a href="pyFTS/benchmarks/benchmarks.html">pyFTS.benchmarks.benchmarks</a></li>
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||||
<li><a href="pyFTS/benchmarks/knn.html">pyFTS.benchmarks.knn</a></li>
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||||
<li><a href="pyFTS/benchmarks/naive.html">pyFTS.benchmarks.naive</a></li>
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||||
<li><a href="pyFTS/benchmarks/parallel_benchmarks.html">pyFTS.benchmarks.parallel_benchmarks</a></li>
|
||||
<li><a href="pyFTS/benchmarks/quantreg.html">pyFTS.benchmarks.quantreg</a></li>
|
||||
<li><a href="pyFTS/common/Composite.html">pyFTS.common.Composite</a></li>
|
||||
<li><a href="pyFTS/common/FLR.html">pyFTS.common.FLR</a></li>
|
||||
<li><a href="pyFTS/common/FuzzySet.html">pyFTS.common.FuzzySet</a></li>
|
||||
<li><a href="pyFTS/common/Membership.html">pyFTS.common.Membership</a></li>
|
||||
<li><a href="pyFTS/common/SortedCollection.html">pyFTS.common.SortedCollection</a></li>
|
||||
<li><a href="pyFTS/common/Transformations.html">pyFTS.common.Transformations</a></li>
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||||
<li><a href="pyFTS/common/Util.html">pyFTS.common.Util</a></li>
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||||
<li><a href="pyFTS/common/flrg.html">pyFTS.common.flrg</a></li>
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||||
<li><a href="pyFTS/common/fts.html">pyFTS.common.fts</a></li>
|
||||
<li><a href="pyFTS/common/tree.html">pyFTS.common.tree</a></li>
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||||
<li><a href="pyFTS/data/AirPassengers.html">pyFTS.data.AirPassengers</a></li>
|
||||
<li><a href="pyFTS/data/Enrollments.html">pyFTS.data.Enrollments</a></li>
|
||||
<li><a href="pyFTS/data/INMET.html">pyFTS.data.INMET</a></li>
|
||||
<li><a href="pyFTS/data/NASDAQ.html">pyFTS.data.NASDAQ</a></li>
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||||
<li><a href="pyFTS/data/SONDA.html">pyFTS.data.SONDA</a></li>
|
||||
<li><a href="pyFTS/data/SP500.html">pyFTS.data.SP500</a></li>
|
||||
<li><a href="pyFTS/data/TAIEX.html">pyFTS.data.TAIEX</a></li>
|
||||
<li><a href="pyFTS/data/artificial.html">pyFTS.data.artificial</a></li>
|
||||
<li><a href="pyFTS/data/common.html">pyFTS.data.common</a></li>
|
||||
<li><a href="pyFTS/data/henon.html">pyFTS.data.henon</a></li>
|
||||
<li><a href="pyFTS/data/logistic_map.html">pyFTS.data.logistic_map</a></li>
|
||||
<li><a href="pyFTS/data/lorentz.html">pyFTS.data.lorentz</a></li>
|
||||
<li><a href="pyFTS/data/mackey_glass.html">pyFTS.data.mackey_glass</a></li>
|
||||
<li><a href="pyFTS/data/rossler.html">pyFTS.data.rossler</a></li>
|
||||
<li><a href="pyFTS/data/sunspots.html">pyFTS.data.sunspots</a></li>
|
||||
<li><a href="pyFTS/models/chen.html">pyFTS.models.chen</a></li>
|
||||
<li><a href="pyFTS/models/cheng.html">pyFTS.models.cheng</a></li>
|
||||
<li><a href="pyFTS/models/ensemble/ensemble.html">pyFTS.models.ensemble.ensemble</a></li>
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||||
<li><a href="pyFTS/models/ensemble/multiseasonal.html">pyFTS.models.ensemble.multiseasonal</a></li>
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||||
<li><a href="pyFTS/models/hofts.html">pyFTS.models.hofts</a></li>
|
||||
<li><a href="pyFTS/models/hwang.html">pyFTS.models.hwang</a></li>
|
||||
<li><a href="pyFTS/models/ifts.html">pyFTS.models.ifts</a></li>
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||||
<li><a href="pyFTS/models/ismailefendi.html">pyFTS.models.ismailefendi</a></li>
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||||
<li><a href="pyFTS/models/multivariate/FLR.html">pyFTS.models.multivariate.FLR</a></li>
|
||||
<li><a href="pyFTS/models/multivariate/common.html">pyFTS.models.multivariate.common</a></li>
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||||
<li><a href="pyFTS/models/multivariate/flrg.html">pyFTS.models.multivariate.flrg</a></li>
|
||||
<li><a href="pyFTS/models/multivariate/mvfts.html">pyFTS.models.multivariate.mvfts</a></li>
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||||
<li><a href="pyFTS/models/multivariate/variable.html">pyFTS.models.multivariate.variable</a></li>
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||||
<li><a href="pyFTS/models/nonstationary/common.html">pyFTS.models.nonstationary.common</a></li>
|
||||
<li><a href="pyFTS/models/nonstationary/cvfts.html">pyFTS.models.nonstationary.cvfts</a></li>
|
||||
<li><a href="pyFTS/models/nonstationary/flrg.html">pyFTS.models.nonstationary.flrg</a></li>
|
||||
<li><a href="pyFTS/models/nonstationary/honsfts.html">pyFTS.models.nonstationary.honsfts</a></li>
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||||
<li><a href="pyFTS/models/nonstationary/nsfts.html">pyFTS.models.nonstationary.nsfts</a></li>
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||||
<li><a href="pyFTS/models/nonstationary/partitioners.html">pyFTS.models.nonstationary.partitioners</a></li>
|
||||
<li><a href="pyFTS/models/nonstationary/perturbation.html">pyFTS.models.nonstationary.perturbation</a></li>
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||||
<li><a href="pyFTS/models/nonstationary/util.html">pyFTS.models.nonstationary.util</a></li>
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||||
<li><a href="pyFTS/models/pwfts.html">pyFTS.models.pwfts</a></li>
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||||
<li><a href="pyFTS/models/sadaei.html">pyFTS.models.sadaei</a></li>
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||||
<li><a href="pyFTS/models/seasonal/SeasonalIndexer.html">pyFTS.models.seasonal.SeasonalIndexer</a></li>
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||||
<li><a href="pyFTS/models/seasonal/cmsfts.html">pyFTS.models.seasonal.cmsfts</a></li>
|
||||
<li><a href="pyFTS/models/seasonal/common.html">pyFTS.models.seasonal.common</a></li>
|
||||
<li><a href="pyFTS/models/seasonal/msfts.html">pyFTS.models.seasonal.msfts</a></li>
|
||||
<li><a href="pyFTS/models/seasonal/partitioner.html">pyFTS.models.seasonal.partitioner</a></li>
|
||||
<li><a href="pyFTS/models/seasonal/sfts.html">pyFTS.models.seasonal.sfts</a></li>
|
||||
<li><a href="pyFTS/models/song.html">pyFTS.models.song</a></li>
|
||||
<li><a href="pyFTS/models/yu.html">pyFTS.models.yu</a></li>
|
||||
<li><a href="pyFTS/partitioners/CMeans.html">pyFTS.partitioners.CMeans</a></li>
|
||||
<li><a href="pyFTS/partitioners/Entropy.html">pyFTS.partitioners.Entropy</a></li>
|
||||
<li><a href="pyFTS/partitioners/FCM.html">pyFTS.partitioners.FCM</a></li>
|
||||
<li><a href="pyFTS/partitioners/Grid.html">pyFTS.partitioners.Grid</a></li>
|
||||
<li><a href="pyFTS/partitioners/Huarng.html">pyFTS.partitioners.Huarng</a></li>
|
||||
<li><a href="pyFTS/partitioners/Util.html">pyFTS.partitioners.Util</a></li>
|
||||
<li><a href="pyFTS/partitioners/parallel_util.html">pyFTS.partitioners.parallel_util</a></li>
|
||||
<li><a href="pyFTS/partitioners/partitioner.html">pyFTS.partitioners.partitioner</a></li>
|
||||
<li><a href="pyFTS/probabilistic/ProbabilityDistribution.html">pyFTS.probabilistic.ProbabilityDistribution</a></li>
|
||||
<li><a href="pyFTS/probabilistic/kde.html">pyFTS.probabilistic.kde</a></li>
|
||||
</ul>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
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<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
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<div class="sphinxsidebarwrapper"><div class="relations">
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<h3>Related Topics</h3>
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<ul>
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<li><a href="../index.html">Documentation overview</a><ul>
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</ul></li>
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</ul>
|
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</div>
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<div id="searchbox" style="display: none" role="search">
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<h3>Quick search</h3>
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<script type="text/javascript">$('#searchbox').show(0);</script>
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<div class="clearer"></div>
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<div class="footer">
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©2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
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Powered by <a href="http://sphinx-doc.org/">Sphinx 1.7.2</a>
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<title>pyFTS.benchmarks.Measures — pyFTS 1.2.3 documentation</title>
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<h1>Source code for pyFTS.benchmarks.Measures</h1><div class="highlight"><pre>
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<span></span><span class="c1"># -*- coding: utf8 -*-</span>
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<span class="sd">"""</span>
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<span class="sd">pyFTS module for common benchmark metrics</span>
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<span class="sd">"""</span>
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<span class="kn">import</span> <span class="nn">time</span>
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<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
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<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
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<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span><span class="n">SortedCollection</span>
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<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">ProbabilityDistribution</span>
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<div class="viewcode-block" id="acf"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.acf">[docs]</a><span class="k">def</span> <span class="nf">acf</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span>
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<span class="sd">"""</span>
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<span class="sd"> Autocorrelation function estimative</span>
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<span class="sd"> :param data: </span>
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<span class="sd"> :param k: </span>
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<span class="sd"> :return: </span>
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<span class="sd"> """</span>
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<span class="n">mu</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
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<span class="n">sigma</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">var</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
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<span class="n">n</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
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<span class="n">s</span> <span class="o">=</span> <span class="mi">0</span>
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<span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="n">n</span><span class="o">-</span><span class="n">k</span><span class="p">):</span>
|
||||
<span class="n">s</span> <span class="o">+=</span> <span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">]</span><span class="o">-</span><span class="n">mu</span><span class="p">)</span> <span class="o">*</span> <span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="o">+</span><span class="n">k</span><span class="p">]</span> <span class="o">-</span> <span class="n">mu</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="mi">1</span><span class="o">/</span><span class="p">((</span><span class="n">n</span><span class="o">-</span><span class="n">k</span><span class="p">)</span><span class="o">*</span><span class="n">sigma</span><span class="p">)</span><span class="o">*</span><span class="n">s</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="rmse"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.rmse">[docs]</a><span class="k">def</span> <span class="nf">rmse</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Root Mean Squared Error</span>
|
||||
|
||||
<span class="sd"> :param targets: </span>
|
||||
<span class="sd"> :param forecasts: </span>
|
||||
<span class="sd"> :return: </span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="n">targets</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">targets</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">forecasts</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">nanmean</span><span class="p">((</span><span class="n">targets</span> <span class="o">-</span> <span class="n">forecasts</span><span class="p">)</span> <span class="o">**</span> <span class="mi">2</span><span class="p">))</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="rmse_interval"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.rmse_interval">[docs]</a><span class="k">def</span> <span class="nf">rmse_interval</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Root Mean Squared Error</span>
|
||||
|
||||
<span class="sd"> :param targets: </span>
|
||||
<span class="sd"> :param forecasts: </span>
|
||||
<span class="sd"> :return: </span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">fmean</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">i</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">forecasts</span><span class="p">]</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">nanmean</span><span class="p">((</span><span class="n">fmean</span> <span class="o">-</span> <span class="n">targets</span><span class="p">)</span> <span class="o">**</span> <span class="mi">2</span><span class="p">))</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="mape"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.mape">[docs]</a><span class="k">def</span> <span class="nf">mape</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Mean Average Percentual Error</span>
|
||||
|
||||
<span class="sd"> :param targets: </span>
|
||||
<span class="sd"> :param forecasts: </span>
|
||||
<span class="sd"> :return: </span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="n">targets</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">targets</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">forecasts</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">((</span><span class="n">targets</span> <span class="o">-</span> <span class="n">forecasts</span><span class="p">)</span> <span class="o">/</span> <span class="n">targets</span><span class="p">))</span> <span class="o">*</span> <span class="mi">100</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="smape"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.smape">[docs]</a><span class="k">def</span> <span class="nf">smape</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="mi">2</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Symmetric Mean Average Percentual Error</span>
|
||||
|
||||
<span class="sd"> :param targets: </span>
|
||||
<span class="sd"> :param forecasts: </span>
|
||||
<span class="sd"> :param type: </span>
|
||||
<span class="sd"> :return: </span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="n">targets</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">targets</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">forecasts</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="nb">type</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">forecasts</span> <span class="o">-</span> <span class="n">targets</span><span class="p">)</span> <span class="o">/</span> <span class="p">((</span><span class="n">forecasts</span> <span class="o">+</span> <span class="n">targets</span><span class="p">)</span><span class="o">/</span><span class="mi">2</span><span class="p">))</span>
|
||||
<span class="k">elif</span> <span class="nb">type</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">forecasts</span> <span class="o">-</span> <span class="n">targets</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="nb">abs</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)</span> <span class="o">+</span> <span class="nb">abs</span><span class="p">(</span><span class="n">targets</span><span class="p">))</span> <span class="p">)</span><span class="o">*</span><span class="mi">100</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="nb">sum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">forecasts</span> <span class="o">-</span> <span class="n">targets</span><span class="p">))</span> <span class="o">/</span> <span class="nb">sum</span><span class="p">(</span><span class="n">forecasts</span> <span class="o">+</span> <span class="n">targets</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="mape_interval"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.mape_interval">[docs]</a><span class="k">def</span> <span class="nf">mape_interval</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">):</span>
|
||||
<span class="n">fmean</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">i</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">forecasts</span><span class="p">]</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="nb">abs</span><span class="p">(</span><span class="n">fmean</span> <span class="o">-</span> <span class="n">targets</span><span class="p">)</span> <span class="o">/</span> <span class="n">fmean</span><span class="p">)</span> <span class="o">*</span> <span class="mi">100</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="UStatistic"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.UStatistic">[docs]</a><span class="k">def</span> <span class="nf">UStatistic</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Theil's U Statistic</span>
|
||||
|
||||
<span class="sd"> :param targets: </span>
|
||||
<span class="sd"> :param forecasts: </span>
|
||||
<span class="sd"> :return: </span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">targets</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="n">targets</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">targets</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">forecasts</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)</span>
|
||||
|
||||
<span class="n">naive</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">y</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="n">l</span><span class="o">-</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="n">y</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">forecasts</span><span class="p">[</span><span class="n">k</span> <span class="p">]</span> <span class="o">-</span> <span class="n">targets</span><span class="p">[</span><span class="n">k</span><span class="p">])</span> <span class="o">**</span> <span class="mi">2</span><span class="p">)</span>
|
||||
<span class="n">naive</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">targets</span><span class="p">[</span><span class="n">k</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">targets</span><span class="p">[</span><span class="n">k</span><span class="p">])</span> <span class="o">**</span> <span class="mi">2</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="nb">sum</span><span class="p">(</span><span class="n">y</span><span class="p">)</span> <span class="o">/</span> <span class="nb">sum</span><span class="p">(</span><span class="n">naive</span><span class="p">))</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="TheilsInequality"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.TheilsInequality">[docs]</a><span class="k">def</span> <span class="nf">TheilsInequality</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Theil’s Inequality Coefficient</span>
|
||||
|
||||
<span class="sd"> :param targets: </span>
|
||||
<span class="sd"> :param forecasts: </span>
|
||||
<span class="sd"> :return: </span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">res</span> <span class="o">=</span> <span class="n">targets</span> <span class="o">-</span> <span class="n">forecasts</span>
|
||||
<span class="n">t</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">res</span><span class="p">)</span>
|
||||
<span class="n">us</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="nb">sum</span><span class="p">([</span><span class="n">u</span><span class="o">**</span><span class="mi">2</span> <span class="k">for</span> <span class="n">u</span> <span class="ow">in</span> <span class="n">res</span><span class="p">]))</span>
|
||||
<span class="n">ys</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="nb">sum</span><span class="p">([</span><span class="n">y</span><span class="o">**</span><span class="mi">2</span> <span class="k">for</span> <span class="n">y</span> <span class="ow">in</span> <span class="n">targets</span><span class="p">]))</span>
|
||||
<span class="n">fs</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="nb">sum</span><span class="p">([</span><span class="n">f</span><span class="o">**</span><span class="mi">2</span> <span class="k">for</span> <span class="n">f</span> <span class="ow">in</span> <span class="n">forecasts</span><span class="p">]))</span>
|
||||
<span class="k">return</span> <span class="n">us</span> <span class="o">/</span> <span class="p">(</span><span class="n">ys</span> <span class="o">+</span> <span class="n">fs</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="BoxPierceStatistic"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.BoxPierceStatistic">[docs]</a><span class="k">def</span> <span class="nf">BoxPierceStatistic</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">h</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Q Statistic for Box-Pierce test</span>
|
||||
|
||||
<span class="sd"> :param data: </span>
|
||||
<span class="sd"> :param h: </span>
|
||||
<span class="sd"> :return: </span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">n</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">s</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="n">h</span><span class="o">+</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="n">r</span> <span class="o">=</span> <span class="n">acf</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
|
||||
<span class="n">s</span> <span class="o">+=</span> <span class="n">r</span><span class="o">**</span><span class="mi">2</span>
|
||||
<span class="k">return</span> <span class="n">n</span><span class="o">*</span><span class="n">s</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="BoxLjungStatistic"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.BoxLjungStatistic">[docs]</a><span class="k">def</span> <span class="nf">BoxLjungStatistic</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">h</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Q Statistic for Ljung–Box test</span>
|
||||
|
||||
<span class="sd"> :param data: </span>
|
||||
<span class="sd"> :param h: </span>
|
||||
<span class="sd"> :return: </span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">n</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">s</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="n">h</span><span class="o">+</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="n">r</span> <span class="o">=</span> <span class="n">acf</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
|
||||
<span class="n">s</span> <span class="o">+=</span> <span class="n">r</span><span class="o">**</span><span class="mi">2</span> <span class="o">/</span> <span class="p">(</span><span class="n">n</span> <span class="o">-</span><span class="n">k</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">n</span><span class="o">*</span><span class="p">(</span><span class="n">n</span><span class="o">-</span><span class="mi">2</span><span class="p">)</span><span class="o">*</span><span class="n">s</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="sharpness"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.sharpness">[docs]</a><span class="k">def</span> <span class="nf">sharpness</span><span class="p">(</span><span class="n">forecasts</span><span class="p">):</span>
|
||||
<span class="sd">"""Sharpness - Mean size of the intervals"""</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[</span><span class="n">i</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">i</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">forecasts</span><span class="p">]</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="resolution"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.resolution">[docs]</a><span class="k">def</span> <span class="nf">resolution</span><span class="p">(</span><span class="n">forecasts</span><span class="p">):</span>
|
||||
<span class="sd">"""Resolution - Standard deviation of the intervals"""</span>
|
||||
<span class="n">shp</span> <span class="o">=</span> <span class="n">sharpness</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[</span><span class="nb">abs</span><span class="p">((</span><span class="n">i</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">i</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="o">-</span> <span class="n">shp</span><span class="p">)</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">forecasts</span><span class="p">]</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="coverage"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.coverage">[docs]</a><span class="k">def</span> <span class="nf">coverage</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">):</span>
|
||||
<span class="sd">"""Percent of target values that fall inside forecasted interval"""</span>
|
||||
<span class="n">preds</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)):</span>
|
||||
<span class="k">if</span> <span class="n">targets</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">>=</span> <span class="n">forecasts</span><span class="p">[</span><span class="n">i</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="ow">and</span> <span class="n">targets</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o"><=</span> <span class="n">forecasts</span><span class="p">[</span><span class="n">i</span><span class="p">][</span><span class="mi">1</span><span class="p">]:</span>
|
||||
<span class="n">preds</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">preds</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">preds</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="pinball"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.pinball">[docs]</a><span class="k">def</span> <span class="nf">pinball</span><span class="p">(</span><span class="n">tau</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">forecast</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Pinball loss function. Measure the distance of forecast to the tau-quantile of the target</span>
|
||||
|
||||
<span class="sd"> :param tau: quantile value in the range (0,1)</span>
|
||||
<span class="sd"> :param target: </span>
|
||||
<span class="sd"> :param forecast: </span>
|
||||
<span class="sd"> :return: float, distance of forecast to the tau-quantile of the target</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">if</span> <span class="n">target</span> <span class="o">>=</span> <span class="n">forecast</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="p">(</span><span class="n">target</span> <span class="o">-</span> <span class="n">forecast</span><span class="p">)</span> <span class="o">*</span> <span class="n">tau</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="p">(</span><span class="n">forecast</span> <span class="o">-</span> <span class="n">target</span><span class="p">)</span> <span class="o">*</span> <span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">tau</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="pinball_mean"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.pinball_mean">[docs]</a><span class="k">def</span> <span class="nf">pinball_mean</span><span class="p">(</span><span class="n">tau</span><span class="p">,</span> <span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Mean pinball loss value of the forecast for a given tau-quantile of the targets</span>
|
||||
|
||||
<span class="sd"> :param tau: quantile value in the range (0,1)</span>
|
||||
<span class="sd"> :param targets: list of target values</span>
|
||||
<span class="sd"> :param forecasts: list of prediction intervals</span>
|
||||
<span class="sd"> :return: float, the pinball loss mean for tau quantile</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">if</span> <span class="n">tau</span> <span class="o"><=</span> <span class="mf">0.5</span><span class="p">:</span>
|
||||
<span class="n">preds</span> <span class="o">=</span> <span class="p">[</span><span class="n">pinball</span><span class="p">(</span><span class="n">tau</span><span class="p">,</span> <span class="n">targets</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">forecasts</span><span class="p">[</span><span class="n">i</span><span class="p">][</span><span class="mi">0</span><span class="p">])</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">forecasts</span><span class="p">))]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">preds</span> <span class="o">=</span> <span class="p">[</span><span class="n">pinball</span><span class="p">(</span><span class="n">tau</span><span class="p">,</span> <span class="n">targets</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">forecasts</span><span class="p">[</span><span class="n">i</span><span class="p">][</span><span class="mi">1</span><span class="p">])</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">forecasts</span><span class="p">))]</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmean</span><span class="p">(</span><span class="n">preds</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="winkler_score"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.winkler_score">[docs]</a><span class="k">def</span> <span class="nf">winkler_score</span><span class="p">(</span><span class="n">tau</span><span class="p">,</span> <span class="n">target</span><span class="p">,</span> <span class="n">forecast</span><span class="p">):</span>
|
||||
<span class="sd">'''R. L. Winkler, A Decision-Theoretic Approach to Interval Estimation, J. Am. Stat. Assoc. 67 (337) (1972) 187–191. doi:10.2307/2284720. '''</span>
|
||||
<span class="n">delta</span> <span class="o">=</span> <span class="n">forecast</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">forecast</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="n">forecast</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o"><</span> <span class="n">target</span> <span class="ow">and</span> <span class="n">target</span> <span class="o"><</span> <span class="n">forecast</span><span class="p">[</span><span class="mi">1</span><span class="p">]:</span>
|
||||
<span class="k">return</span> <span class="n">delta</span>
|
||||
<span class="k">elif</span> <span class="n">forecast</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">></span> <span class="n">target</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">delta</span> <span class="o">+</span> <span class="mi">2</span><span class="o">*</span><span class="p">(</span><span class="n">forecast</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">-</span> <span class="n">target</span><span class="p">)</span><span class="o">/</span><span class="n">tau</span>
|
||||
<span class="k">elif</span> <span class="n">forecast</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o"><</span> <span class="n">target</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">delta</span> <span class="o">+</span> <span class="mi">2</span><span class="o">*</span><span class="p">(</span><span class="n">target</span> <span class="o">-</span> <span class="n">forecast</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span><span class="o">/</span><span class="n">tau</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="winkler_mean"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.winkler_mean">[docs]</a><span class="k">def</span> <span class="nf">winkler_mean</span><span class="p">(</span><span class="n">tau</span><span class="p">,</span> <span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Mean Winkler score value of the forecast for a given tau-quantile of the targets</span>
|
||||
|
||||
<span class="sd"> :param tau: quantile value in the range (0,1)</span>
|
||||
<span class="sd"> :param targets: list of target values</span>
|
||||
<span class="sd"> :param forecasts: list of prediction intervals</span>
|
||||
<span class="sd"> :return: float, the Winkler score mean for tau quantile</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">preds</span> <span class="o">=</span> <span class="p">[</span><span class="n">winkler_score</span><span class="p">(</span><span class="n">tau</span><span class="p">,</span> <span class="n">targets</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">forecasts</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">forecasts</span><span class="p">))]</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmean</span><span class="p">(</span><span class="n">preds</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="brier_score"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.brier_score">[docs]</a><span class="k">def</span> <span class="nf">brier_score</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">densities</span><span class="p">):</span>
|
||||
<span class="sd">'''Brier (1950). "Verification of Forecasts Expressed in Terms of Probability". Monthly Weather Review. 78: 1–3. '''</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">d</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">densities</span><span class="p">):</span>
|
||||
<span class="k">try</span><span class="p">:</span>
|
||||
<span class="n">v</span> <span class="o">=</span> <span class="n">d</span><span class="o">.</span><span class="n">bin_index</span><span class="o">.</span><span class="n">find_ge</span><span class="p">(</span><span class="n">targets</span><span class="p">[</span><span class="n">ct</span><span class="p">])</span>
|
||||
|
||||
<span class="n">score</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">([</span><span class="n">d</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">**</span> <span class="mi">2</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">d</span><span class="o">.</span><span class="n">bins</span> <span class="k">if</span> <span class="n">k</span> <span class="o">!=</span> <span class="n">v</span><span class="p">])</span>
|
||||
<span class="n">score</span> <span class="o">+=</span> <span class="p">(</span><span class="n">d</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">v</span><span class="p">]</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="o">**</span> <span class="mi">2</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">score</span><span class="p">)</span>
|
||||
<span class="k">except</span> <span class="ne">ValueError</span> <span class="k">as</span> <span class="n">ex</span><span class="p">:</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">sum</span><span class="p">([</span><span class="n">d</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">**</span> <span class="mi">2</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">d</span><span class="o">.</span><span class="n">bins</span><span class="p">]))</span>
|
||||
<span class="k">return</span> <span class="nb">sum</span><span class="p">(</span><span class="n">ret</span><span class="p">)</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="pmf_to_cdf"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.pmf_to_cdf">[docs]</a><span class="k">def</span> <span class="nf">pmf_to_cdf</span><span class="p">(</span><span class="n">density</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">row</span> <span class="ow">in</span> <span class="n">density</span><span class="o">.</span><span class="n">index</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">prev</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">col</span> <span class="ow">in</span> <span class="n">density</span><span class="o">.</span><span class="n">columns</span><span class="p">:</span>
|
||||
<span class="n">prev</span> <span class="o">+=</span> <span class="n">density</span><span class="p">[</span><span class="n">col</span><span class="p">][</span><span class="n">row</span><span class="p">]</span> <span class="k">if</span> <span class="ow">not</span> <span class="n">np</span><span class="o">.</span><span class="n">isnan</span><span class="p">(</span><span class="n">density</span><span class="p">[</span><span class="n">col</span><span class="p">][</span><span class="n">row</span><span class="p">])</span> <span class="k">else</span> <span class="mi">0</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span> <span class="n">prev</span> <span class="p">)</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">ret</span><span class="p">,</span> <span class="n">columns</span><span class="o">=</span><span class="n">density</span><span class="o">.</span><span class="n">columns</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">df</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="heavyside"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.heavyside">[docs]</a><span class="k">def</span> <span class="nf">heavyside</span><span class="p">(</span><span class="nb">bin</span><span class="p">,</span> <span class="n">target</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="mi">1</span> <span class="k">if</span> <span class="nb">bin</span> <span class="o">>=</span> <span class="n">target</span> <span class="k">else</span> <span class="mi">0</span></div>
|
||||
|
||||
<div class="viewcode-block" id="heavyside_cdf"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.heavyside_cdf">[docs]</a><span class="k">def</span> <span class="nf">heavyside_cdf</span><span class="p">(</span><span class="n">bins</span><span class="p">,</span> <span class="n">targets</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">targets</span><span class="p">:</span>
|
||||
<span class="n">result</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span> <span class="k">if</span> <span class="n">b</span> <span class="o">>=</span> <span class="n">t</span> <span class="k">else</span> <span class="mi">0</span> <span class="k">for</span> <span class="n">b</span> <span class="ow">in</span> <span class="n">bins</span><span class="p">]</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">result</span><span class="p">)</span>
|
||||
<span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">ret</span><span class="p">,</span> <span class="n">columns</span><span class="o">=</span><span class="n">bins</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">df</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="crps"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.crps">[docs]</a><span class="k">def</span> <span class="nf">crps</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">densities</span><span class="p">):</span>
|
||||
<span class="sd">'''</span>
|
||||
<span class="sd"> Continuous Ranked Probability Score</span>
|
||||
|
||||
<span class="sd"> :param targets: a list with the target values</span>
|
||||
<span class="sd"> :param densities: a list with pyFTS.probabil objectsistic.ProbabilityDistribution</span>
|
||||
<span class="sd"> :return: float</span>
|
||||
<span class="sd"> '''</span>
|
||||
<span class="n">_crps</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="mf">0.0</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">densities</span><span class="p">,</span> <span class="n">ProbabilityDistribution</span><span class="o">.</span><span class="n">ProbabilityDistribution</span><span class="p">):</span>
|
||||
<span class="n">densities</span> <span class="o">=</span> <span class="p">[</span><span class="n">densities</span><span class="p">]</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">densities</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">bins</span><span class="p">)</span>
|
||||
<span class="n">n</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">densities</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">df</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">densities</span><span class="p">):</span>
|
||||
<span class="n">_crps</span> <span class="o">+=</span> <span class="nb">sum</span><span class="p">([(</span><span class="n">df</span><span class="o">.</span><span class="n">cummulative</span><span class="p">(</span><span class="nb">bin</span><span class="p">)</span> <span class="o">-</span> <span class="p">(</span><span class="mi">1</span> <span class="k">if</span> <span class="nb">bin</span> <span class="o">>=</span> <span class="n">targets</span><span class="p">[</span><span class="n">ct</span><span class="p">]</span> <span class="k">else</span> <span class="mi">0</span><span class="p">))</span> <span class="o">**</span> <span class="mi">2</span> <span class="k">for</span> <span class="nb">bin</span> <span class="ow">in</span> <span class="n">df</span><span class="o">.</span><span class="n">bins</span><span class="p">])</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">_crps</span> <span class="o">/</span> <span class="nb">float</span><span class="p">(</span><span class="n">l</span> <span class="o">*</span> <span class="n">n</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_point_statistics"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.get_point_statistics">[docs]</a><span class="k">def</span> <span class="nf">get_point_statistics</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">model</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">'''</span>
|
||||
<span class="sd"> Condensate all measures for point forecasters</span>
|
||||
|
||||
<span class="sd"> :param data: test data</span>
|
||||
<span class="sd"> :param model: FTS model with point forecasting capability</span>
|
||||
<span class="sd"> :param kwargs:</span>
|
||||
<span class="sd"> :return: a list with the RMSE, SMAPE and U Statistic</span>
|
||||
<span class="sd"> '''</span>
|
||||
|
||||
<span class="n">steps_ahead</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'steps_ahead'</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>
|
||||
<span class="n">kwargs</span><span class="p">[</span><span class="s1">'type'</span><span class="p">]</span> <span class="o">=</span> <span class="s1">'point'</span>
|
||||
|
||||
<span class="n">indexer</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'indexer'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">indexer</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_data</span><span class="p">(</span><span class="n">data</span><span class="p">))</span>
|
||||
<span class="k">elif</span> <span class="n">model</span><span class="o">.</span><span class="n">is_multivariate</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">):</span>
|
||||
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"Multivariate data must be a Pandas DataFrame!"</span><span class="p">)</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">data</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="nb">list</span><span class="p">()</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">steps_ahead</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">model</span><span class="o">.</span><span class="n">is_multivariate</span> <span class="ow">and</span> <span class="n">model</span><span class="o">.</span><span class="n">has_seasonality</span><span class="p">:</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_data</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="n">model</span><span class="o">.</span><span class="n">is_multivariate</span><span class="p">:</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">ndata</span><span class="p">[</span><span class="n">model</span><span class="o">.</span><span class="n">target_variable</span><span class="o">.</span><span class="n">data_label</span><span class="p">]</span><span class="o">.</span><span class="n">values</span>
|
||||
|
||||
<span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">forecasts</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)):</span>
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="p">[</span><span class="n">forecasts</span><span class="p">]</span>
|
||||
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">forecasts</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">rmse</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">model</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">mape</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">model</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">UStatistic</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">model</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">steps_ahead_sampler</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'steps_ahead_sampler'</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
|
||||
<span class="n">nforecasts</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span><span class="o">-</span><span class="n">steps_ahead</span><span class="p">,</span><span class="n">steps_ahead_sampler</span><span class="p">):</span>
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">ndata</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="n">nforecasts</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
|
||||
|
||||
<span class="n">start</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">+</span> <span class="n">steps_ahead</span> <span class="o">-</span><span class="mi">1</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">rmse</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">start</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">:</span><span class="n">steps_ahead_sampler</span><span class="p">],</span> <span class="n">nforecasts</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">mape</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">start</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">:</span><span class="n">steps_ahead_sampler</span><span class="p">],</span> <span class="n">nforecasts</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">UStatistic</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">start</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">:</span><span class="n">steps_ahead_sampler</span><span class="p">],</span> <span class="n">nforecasts</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_interval_statistics"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.get_interval_statistics">[docs]</a><span class="k">def</span> <span class="nf">get_interval_statistics</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">model</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">'''</span>
|
||||
<span class="sd"> Condensate all measures for point interval forecasters</span>
|
||||
|
||||
<span class="sd"> :param data: test data</span>
|
||||
<span class="sd"> :param model: FTS model with interval forecasting capability</span>
|
||||
<span class="sd"> :param kwargs:</span>
|
||||
<span class="sd"> :return: a list with the sharpness, resolution, coverage, .05 pinball mean,</span>
|
||||
<span class="sd"> .25 pinball mean, .75 pinball mean and .95 pinball mean.</span>
|
||||
<span class="sd"> '''</span>
|
||||
|
||||
<span class="n">steps_ahead</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'steps_ahead'</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
|
||||
<span class="n">kwargs</span><span class="p">[</span><span class="s1">'type'</span><span class="p">]</span> <span class="o">=</span> <span class="s1">'interval'</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="nb">list</span><span class="p">()</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">steps_ahead</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">sharpness</span><span class="p">(</span><span class="n">forecasts</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">resolution</span><span class="p">(</span><span class="n">forecasts</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">coverage</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">pinball_mean</span><span class="p">(</span><span class="mf">0.05</span><span class="p">,</span> <span class="n">data</span><span class="p">[</span><span class="n">model</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">pinball_mean</span><span class="p">(</span><span class="mf">0.25</span><span class="p">,</span> <span class="n">data</span><span class="p">[</span><span class="n">model</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">pinball_mean</span><span class="p">(</span><span class="mf">0.75</span><span class="p">,</span> <span class="n">data</span><span class="p">[</span><span class="n">model</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">pinball_mean</span><span class="p">(</span><span class="mf">0.95</span><span class="p">,</span> <span class="n">data</span><span class="p">[</span><span class="n">model</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">winkler_mean</span><span class="p">(</span><span class="mf">0.05</span><span class="p">,</span> <span class="n">data</span><span class="p">[</span><span class="n">model</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">winkler_mean</span><span class="p">(</span><span class="mf">0.25</span><span class="p">,</span> <span class="n">data</span><span class="p">[</span><span class="n">model</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span> <span class="o">-</span> <span class="n">steps_ahead</span><span class="p">):</span>
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="n">forecasts</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
|
||||
|
||||
<span class="n">start</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">+</span> <span class="n">steps_ahead</span> <span class="o">-</span><span class="mi">1</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">sharpness</span><span class="p">(</span><span class="n">forecasts</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">resolution</span><span class="p">(</span><span class="n">forecasts</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">coverage</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">model</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">pinball_mean</span><span class="p">(</span><span class="mf">0.05</span><span class="p">,</span> <span class="n">data</span><span class="p">[</span><span class="n">start</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">pinball_mean</span><span class="p">(</span><span class="mf">0.25</span><span class="p">,</span> <span class="n">data</span><span class="p">[</span><span class="n">start</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">pinball_mean</span><span class="p">(</span><span class="mf">0.75</span><span class="p">,</span> <span class="n">data</span><span class="p">[</span><span class="n">start</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">pinball_mean</span><span class="p">(</span><span class="mf">0.95</span><span class="p">,</span> <span class="n">data</span><span class="p">[</span><span class="n">start</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">winkler_mean</span><span class="p">(</span><span class="mf">0.05</span><span class="p">,</span> <span class="n">data</span><span class="p">[</span><span class="n">start</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">winkler_mean</span><span class="p">(</span><span class="mf">0.25</span><span class="p">,</span> <span class="n">data</span><span class="p">[</span><span class="n">start</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_distribution_statistics"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.get_distribution_statistics">[docs]</a><span class="k">def</span> <span class="nf">get_distribution_statistics</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">model</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">'''</span>
|
||||
<span class="sd"> Get CRPS statistic and time for a forecasting model</span>
|
||||
|
||||
<span class="sd"> :param data: test data</span>
|
||||
<span class="sd"> :param model: FTS model with probabilistic forecasting capability</span>
|
||||
<span class="sd"> :param kwargs:</span>
|
||||
<span class="sd"> :return: a list with the CRPS and execution time</span>
|
||||
<span class="sd"> '''</span>
|
||||
<span class="n">steps_ahead</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'steps_ahead'</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
|
||||
<span class="n">kwargs</span><span class="p">[</span><span class="s1">'type'</span><span class="p">]</span> <span class="o">=</span> <span class="s1">'distribution'</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="nb">list</span><span class="p">()</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">steps_ahead</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">_s1</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="n">_e1</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">crps</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">model</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]),</span> <span class="mi">3</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">_e1</span> <span class="o">-</span> <span class="n">_s1</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">brier_score</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">model</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">]),</span> <span class="mi">3</span><span class="p">))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">skip</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'steps_ahead_sampler'</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">_s1</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span> <span class="o">-</span> <span class="n">steps_ahead</span><span class="p">,</span> <span class="n">skip</span><span class="p">):</span>
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="n">model</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="n">forecasts</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="n">_e1</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
|
||||
<span class="n">start</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">+</span> <span class="n">steps_ahead</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">crps</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">start</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">:</span><span class="n">skip</span><span class="p">],</span> <span class="n">forecasts</span><span class="p">),</span> <span class="mi">3</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">_e1</span> <span class="o">-</span> <span class="n">_s1</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">brier_score</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">start</span><span class="p">:</span><span class="o">-</span><span class="mi">1</span><span class="p">:</span><span class="n">skip</span><span class="p">],</span> <span class="n">forecasts</span><span class="p">),</span> <span class="mi">3</span><span class="p">))</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
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|
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232
docs/_build/html/_modules/pyFTS/benchmarks/ResidualAnalysis.html
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232
docs/_build/html/_modules/pyFTS/benchmarks/ResidualAnalysis.html
vendored
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<h1>Source code for pyFTS.benchmarks.ResidualAnalysis</h1><div class="highlight"><pre>
|
||||
<span></span><span class="ch">#!/usr/bin/python</span>
|
||||
<span class="c1"># -*- coding: utf8 -*-</span>
|
||||
|
||||
<span class="sd">"""Residual Analysis methods"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
<span class="kn">import</span> <span class="nn">matplotlib</span> <span class="k">as</span> <span class="nn">plt</span>
|
||||
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Transformations</span><span class="p">,</span><span class="n">Util</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span>
|
||||
<span class="kn">from</span> <span class="nn">scipy</span> <span class="k">import</span> <span class="n">stats</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="residuals"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.ResidualAnalysis.residuals">[docs]</a><span class="k">def</span> <span class="nf">residuals</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="sd">"""First order residuals"""</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">targets</span><span class="p">[</span><span class="n">order</span><span class="p">:])</span> <span class="o">-</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">forecasts</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="chi_squared"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.ResidualAnalysis.chi_squared">[docs]</a><span class="k">def</span> <span class="nf">chi_squared</span><span class="p">(</span><span class="n">q</span><span class="p">,</span> <span class="n">h</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Chi-Squared value</span>
|
||||
|
||||
<span class="sd"> :param q: </span>
|
||||
<span class="sd"> :param h: </span>
|
||||
<span class="sd"> :return: </span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">p</span> <span class="o">=</span> <span class="n">stats</span><span class="o">.</span><span class="n">chi2</span><span class="o">.</span><span class="n">sf</span><span class="p">(</span><span class="n">q</span><span class="p">,</span> <span class="n">h</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">p</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="compare_residuals"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.ResidualAnalysis.compare_residuals">[docs]</a><span class="k">def</span> <span class="nf">compare_residuals</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">models</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Compare residual's statistics of several models</span>
|
||||
|
||||
<span class="sd"> :param data: test data</span>
|
||||
<span class="sd"> :param models: </span>
|
||||
<span class="sd"> :return: a Pandas dataframe with the Box-Ljung statistic for each model</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="kn">from</span> <span class="nn">statsmodels.stats.diagnostic</span> <span class="k">import</span> <span class="n">acorr_ljungbox</span>
|
||||
<span class="n">rows</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">columns</span> <span class="o">=</span> <span class="p">[</span><span class="s2">"Model"</span><span class="p">,</span><span class="s2">"Order"</span><span class="p">,</span><span class="s2">"AVG"</span><span class="p">,</span><span class="s2">"STD"</span><span class="p">,</span><span class="s2">"Box-Ljung"</span><span class="p">,</span><span class="s2">"p-value"</span><span class="p">]</span>
|
||||
<span class="k">for</span> <span class="n">mfts</span> <span class="ow">in</span> <span class="n">models</span><span class="p">:</span>
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="n">mfts</span><span class="o">.</span><span class="n">forecast</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">res</span> <span class="o">=</span> <span class="n">residuals</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">,</span> <span class="n">mfts</span><span class="o">.</span><span class="n">order</span><span class="p">)</span>
|
||||
<span class="n">mu</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">res</span><span class="p">)</span>
|
||||
<span class="n">sig</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">res</span><span class="p">)</span>
|
||||
<span class="n">row</span> <span class="o">=</span> <span class="p">[</span><span class="n">mfts</span><span class="o">.</span><span class="n">shortname</span><span class="p">,</span> <span class="n">mfts</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">mu</span><span class="p">,</span> <span class="n">sig</span><span class="p">]</span>
|
||||
<span class="n">stat</span><span class="p">,</span> <span class="n">pval</span> <span class="o">=</span> <span class="n">acorr_ljungbox</span><span class="p">(</span><span class="n">res</span><span class="p">)</span>
|
||||
<span class="n">row</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="n">stat</span><span class="p">,</span> <span class="n">pval</span><span class="p">])</span>
|
||||
<span class="n">rows</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">row</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">rows</span><span class="p">,</span> <span class="n">columns</span><span class="o">=</span><span class="n">columns</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="plotResiduals"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.ResidualAnalysis.plotResiduals">[docs]</a><span class="k">def</span> <span class="nf">plotResiduals</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">models</span><span class="p">,</span> <span class="n">tam</span><span class="o">=</span><span class="p">[</span><span class="mi">8</span><span class="p">,</span> <span class="mi">8</span><span class="p">],</span> <span class="n">save</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">file</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Plot residuals and statistics</span>
|
||||
|
||||
<span class="sd"> :param targets: </span>
|
||||
<span class="sd"> :param models: </span>
|
||||
<span class="sd"> :param tam: </span>
|
||||
<span class="sd"> :param save: </span>
|
||||
<span class="sd"> :param file: </span>
|
||||
<span class="sd"> :return: </span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">fig</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">nrows</span><span class="o">=</span><span class="nb">len</span><span class="p">(</span><span class="n">models</span><span class="p">),</span> <span class="n">ncols</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="n">tam</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">c</span><span class="p">,</span> <span class="n">mfts</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">models</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">models</span><span class="p">)</span> <span class="o">></span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">ax</span> <span class="o">=</span> <span class="n">axes</span><span class="p">[</span><span class="n">c</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ax</span> <span class="o">=</span> <span class="n">axes</span>
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="n">mfts</span><span class="o">.</span><span class="n">forecast</span><span class="p">(</span><span class="n">targets</span><span class="p">)</span>
|
||||
<span class="n">res</span> <span class="o">=</span> <span class="n">residuals</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span><span class="n">forecasts</span><span class="p">,</span><span class="n">mfts</span><span class="o">.</span><span class="n">order</span><span class="p">)</span>
|
||||
<span class="n">mu</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">res</span><span class="p">)</span>
|
||||
<span class="n">sig</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">res</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"Residuals Mean="</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">mu</span><span class="p">)</span> <span class="o">+</span> <span class="s2">" STD = "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">sig</span><span class="p">))</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">'E'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">'T'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">res</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"Residuals Autocorrelation"</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">'ACS'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">'Lag'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">acorr</span><span class="p">(</span><span class="n">res</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"Residuals Histogram"</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">'Freq'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">'Bins'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">res</span><span class="p">)</span>
|
||||
|
||||
<span class="n">c</span> <span class="o">+=</span> <span class="mi">1</span>
|
||||
|
||||
<span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
|
||||
|
||||
<span class="n">Util</span><span class="o">.</span><span class="n">show_and_save_image</span><span class="p">(</span><span class="n">fig</span><span class="p">,</span> <span class="n">file</span><span class="p">,</span> <span class="n">save</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="plot_residuals"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.ResidualAnalysis.plot_residuals">[docs]</a><span class="k">def</span> <span class="nf">plot_residuals</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">models</span><span class="p">,</span> <span class="n">tam</span><span class="o">=</span><span class="p">[</span><span class="mi">8</span><span class="p">,</span> <span class="mi">8</span><span class="p">],</span> <span class="n">save</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">file</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="n">fig</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">nrows</span><span class="o">=</span><span class="nb">len</span><span class="p">(</span><span class="n">models</span><span class="p">),</span> <span class="n">ncols</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="n">tam</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">c</span><span class="p">,</span> <span class="n">mfts</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">models</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">models</span><span class="p">)</span> <span class="o">></span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">ax</span> <span class="o">=</span> <span class="n">axes</span><span class="p">[</span><span class="n">c</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ax</span> <span class="o">=</span> <span class="n">axes</span>
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="n">mfts</span><span class="o">.</span><span class="n">forecast</span><span class="p">(</span><span class="n">targets</span><span class="p">)</span>
|
||||
<span class="n">res</span> <span class="o">=</span> <span class="n">residuals</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">,</span> <span class="n">mfts</span><span class="o">.</span><span class="n">order</span><span class="p">)</span>
|
||||
<span class="n">mu</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">res</span><span class="p">)</span>
|
||||
<span class="n">sig</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">res</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">c</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span> <span class="n">ax</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"Residuals"</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="s1">'large'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="n">mfts</span><span class="o">.</span><span class="n">shortname</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="s1">'large'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">' '</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">res</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">c</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span> <span class="n">ax</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"Residuals Autocorrelation"</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="s1">'large'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">'ACS'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">'Lag'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">acorr</span><span class="p">(</span><span class="n">res</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">c</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span> <span class="n">ax</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"Residuals Histogram"</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="s1">'large'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">'Freq'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">'Bins'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">res</span><span class="p">)</span>
|
||||
|
||||
<span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
|
||||
|
||||
<span class="n">Util</span><span class="o">.</span><span class="n">show_and_save_image</span><span class="p">(</span><span class="n">fig</span><span class="p">,</span> <span class="n">file</span><span class="p">,</span> <span class="n">save</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="single_plot_residuals"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.ResidualAnalysis.single_plot_residuals">[docs]</a><span class="k">def</span> <span class="nf">single_plot_residuals</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="n">tam</span><span class="o">=</span><span class="p">[</span><span class="mi">8</span><span class="p">,</span> <span class="mi">8</span><span class="p">],</span> <span class="n">save</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">file</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="n">fig</span><span class="p">,</span> <span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">nrows</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">ncols</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="n">tam</span><span class="p">)</span>
|
||||
|
||||
<span class="n">res</span> <span class="o">=</span> <span class="n">residuals</span><span class="p">(</span><span class="n">targets</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">,</span> <span class="n">order</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"Residuals"</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="s1">'large'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s2">"Model"</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="s1">'large'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">' '</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">res</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"Residuals Autocorrelation"</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="s1">'large'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">'ACS'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">'Lag'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">acorr</span><span class="p">(</span><span class="n">res</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"Residuals Histogram"</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="s1">'large'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">'Freq'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">'Bins'</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span><span class="o">.</span><span class="n">hist</span><span class="p">(</span><span class="n">res</span><span class="p">)</span>
|
||||
|
||||
<span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
|
||||
|
||||
<span class="n">Util</span><span class="o">.</span><span class="n">show_and_save_image</span><span class="p">(</span><span class="n">fig</span><span class="p">,</span> <span class="n">file</span><span class="p">,</span> <span class="n">save</span><span class="p">)</span></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
||||
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|
||||
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<h3>Quick search</h3>
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1286
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1286
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<h1>Source code for pyFTS.benchmarks.arima</h1><div class="highlight"><pre>
|
||||
<span></span><span class="ch">#!/usr/bin/python</span>
|
||||
<span class="c1"># -*- coding: utf8 -*-</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
<span class="kn">from</span> <span class="nn">statsmodels.tsa.arima_model</span> <span class="k">import</span> <span class="n">ARIMA</span> <span class="k">as</span> <span class="n">stats_arima</span>
|
||||
<span class="kn">import</span> <span class="nn">scipy.stats</span> <span class="k">as</span> <span class="nn">st</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">SortedCollection</span><span class="p">,</span> <span class="n">fts</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">ProbabilityDistribution</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ARIMA"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.arima.ARIMA">[docs]</a><span class="k">class</span> <span class="nc">ARIMA</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Façade for statsmodels.tsa.arima_model</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">ARIMA</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"ARIMA"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">"Auto Regressive Integrated Moving Average"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_point_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_interval_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_probability_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">model_fit</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">trained_data</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">p</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">d</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">q</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">benchmark_only</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_order</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">alpha</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"alpha"</span><span class="p">,</span> <span class="mf">0.05</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"order"</span><span class="p">,</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">))</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_decompose_order</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">)</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">_decompose_order</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">order</span><span class="p">,</span> <span class="p">(</span><span class="nb">tuple</span><span class="p">,</span> <span class="nb">set</span><span class="p">,</span> <span class="nb">list</span><span class="p">)):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">p</span> <span class="o">=</span> <span class="n">order</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">d</span> <span class="o">=</span> <span class="n">order</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">q</span> <span class="o">=</span> <span class="n">order</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">p</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">q</span> <span class="o">+</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">q</span> <span class="o">-</span> <span class="mi">1</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">q</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="mi">0</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">d</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">transformations</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">"ARIMA("</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">p</span><span class="p">)</span> <span class="o">+</span> <span class="s2">","</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">d</span><span class="p">)</span> <span class="o">+</span> <span class="s2">","</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">q</span><span class="p">)</span> <span class="o">+</span> <span class="s2">") - "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">alpha</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="ARIMA.train"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.arima.ARIMA.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="s1">'order'</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
|
||||
<span class="n">order</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'order'</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_decompose_order</span><span class="p">(</span><span class="n">order</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">data</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_data</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="k">try</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="o">=</span> <span class="n">stats_arima</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">p</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">d</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">q</span><span class="p">))</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">model_fit</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">disp</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
|
||||
<span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">ex</span><span class="p">:</span>
|
||||
<span class="nb">print</span><span class="p">(</span><span class="n">ex</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">model_fit</span> <span class="o">=</span> <span class="kc">None</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ARIMA.ar"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.arima.ARIMA.ar">[docs]</a> <span class="k">def</span> <span class="nf">ar</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">data</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model_fit</span><span class="o">.</span><span class="n">arparams</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ARIMA.ma"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.arima.ARIMA.ma">[docs]</a> <span class="k">def</span> <span class="nf">ma</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">data</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model_fit</span><span class="o">.</span><span class="n">maparams</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ARIMA.forecast"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.arima.ARIMA.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_fit</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
|
||||
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">ar</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">ar</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">p</span><span class="p">:</span> <span class="n">k</span><span class="p">])</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">p</span><span class="p">,</span> <span class="n">l</span><span class="o">+</span><span class="mi">1</span><span class="p">)])</span> <span class="c1">#+1 to forecast one step ahead given all available lags</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">q</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">residuals</span> <span class="o">=</span> <span class="n">ndata</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">p</span><span class="o">-</span><span class="mi">1</span><span class="p">:]</span> <span class="o">-</span> <span class="n">ar</span>
|
||||
|
||||
<span class="n">ma</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">ma</span><span class="p">(</span><span class="n">residuals</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">q</span><span class="p">:</span> <span class="n">k</span><span class="p">])</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">q</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">residuals</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)])</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="n">ar</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">q</span> <span class="o">-</span> <span class="mi">1</span><span class="p">:]</span> <span class="o">+</span> <span class="n">ma</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="n">ret</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">q</span><span class="p">:]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="n">ar</span>
|
||||
|
||||
<span class="c1">#ret = self.apply_inverse_transformations(ret, params=[data[self.order - 1:]]) nforecasts = np.array(forecasts)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ARIMA.forecast_interval"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.arima.ARIMA.forecast_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_fit</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
|
||||
|
||||
<span class="n">sigma</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model_fit</span><span class="o">.</span><span class="n">sigma2</span><span class="p">)</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">l</span><span class="o">+</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="p">[</span><span class="n">data</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">k</span><span class="p">)]</span>
|
||||
|
||||
<span class="n">mean</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">mean</span><span class="p">,(</span><span class="nb">list</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)):</span>
|
||||
<span class="n">mean</span> <span class="o">=</span> <span class="n">mean</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mean</span> <span class="o">+</span> <span class="n">st</span><span class="o">.</span><span class="n">norm</span><span class="o">.</span><span class="n">ppf</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">alpha</span><span class="p">)</span> <span class="o">*</span> <span class="n">sigma</span><span class="p">)</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mean</span> <span class="o">+</span> <span class="n">st</span><span class="o">.</span><span class="n">norm</span><span class="o">.</span><span class="n">ppf</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">alpha</span><span class="p">)</span> <span class="o">*</span> <span class="n">sigma</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ARIMA.forecast_ahead_interval"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.arima.ARIMA.forecast_ahead_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">model_fit</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
|
||||
|
||||
<span class="n">smoothing</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"smoothing"</span><span class="p">,</span><span class="mf">0.5</span><span class="p">)</span>
|
||||
|
||||
<span class="n">sigma</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model_fit</span><span class="o">.</span><span class="n">sigma2</span><span class="p">)</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">nmeans</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast_ahead</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">steps</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">hsigma</span> <span class="o">=</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="n">k</span><span class="o">*</span><span class="n">smoothing</span><span class="p">)</span><span class="o">*</span><span class="n">sigma</span>
|
||||
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">nmeans</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">+</span> <span class="n">st</span><span class="o">.</span><span class="n">norm</span><span class="o">.</span><span class="n">ppf</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">alpha</span><span class="p">)</span> <span class="o">*</span> <span class="n">hsigma</span><span class="p">)</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">nmeans</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">+</span> <span class="n">st</span><span class="o">.</span><span class="n">norm</span><span class="o">.</span><span class="n">ppf</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">alpha</span><span class="p">)</span> <span class="o">*</span> <span class="n">hsigma</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ARIMA.forecast_distribution"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.arima.ARIMA.forecast_distribution">[docs]</a> <span class="k">def</span> <span class="nf">forecast_distribution</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">sigma</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model_fit</span><span class="o">.</span><span class="n">sigma2</span><span class="p">)</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">l</span> <span class="o">+</span> <span class="mi">1</span><span class="p">):</span>
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="p">[</span><span class="n">data</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">k</span><span class="p">)]</span>
|
||||
|
||||
<span class="n">mean</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">mean</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)):</span>
|
||||
<span class="n">mean</span> <span class="o">=</span> <span class="n">mean</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
|
||||
<span class="n">dist</span> <span class="o">=</span> <span class="n">ProbabilityDistribution</span><span class="o">.</span><span class="n">ProbabilityDistribution</span><span class="p">(</span><span class="nb">type</span><span class="o">=</span><span class="s2">"histogram"</span><span class="p">,</span> <span class="n">uod</span><span class="o">=</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">original_min</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_max</span><span class="p">])</span>
|
||||
<span class="n">intervals</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">alpha</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mf">0.05</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.05</span><span class="p">):</span>
|
||||
|
||||
<span class="n">qt1</span> <span class="o">=</span> <span class="n">mean</span> <span class="o">+</span> <span class="n">st</span><span class="o">.</span><span class="n">norm</span><span class="o">.</span><span class="n">ppf</span><span class="p">(</span><span class="n">alpha</span><span class="p">)</span> <span class="o">*</span> <span class="n">sigma</span>
|
||||
<span class="n">qt2</span> <span class="o">=</span> <span class="n">mean</span> <span class="o">+</span> <span class="n">st</span><span class="o">.</span><span class="n">norm</span><span class="o">.</span><span class="n">ppf</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">alpha</span><span class="p">)</span> <span class="o">*</span> <span class="n">sigma</span>
|
||||
|
||||
<span class="n">intervals</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="n">qt1</span><span class="p">,</span> <span class="n">qt2</span><span class="p">])</span>
|
||||
|
||||
<span class="n">dist</span><span class="o">.</span><span class="n">append_interval</span><span class="p">(</span><span class="n">intervals</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">dist</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ARIMA.forecast_ahead_distribution"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.arima.ARIMA.forecast_ahead_distribution">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead_distribution</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">smoothing</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"smoothing"</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">)</span>
|
||||
|
||||
<span class="n">sigma</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model_fit</span><span class="o">.</span><span class="n">sigma2</span><span class="p">)</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">nmeans</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast_ahead</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">steps</span><span class="p">):</span>
|
||||
<span class="n">dist</span> <span class="o">=</span> <span class="n">ProbabilityDistribution</span><span class="o">.</span><span class="n">ProbabilityDistribution</span><span class="p">(</span><span class="nb">type</span><span class="o">=</span><span class="s2">"histogram"</span><span class="p">,</span>
|
||||
<span class="n">uod</span><span class="o">=</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">original_min</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_max</span><span class="p">])</span>
|
||||
<span class="n">intervals</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">alpha</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mf">0.05</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.05</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">hsigma</span> <span class="o">=</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="n">k</span> <span class="o">*</span> <span class="n">smoothing</span><span class="p">)</span> <span class="o">*</span> <span class="n">sigma</span>
|
||||
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">nmeans</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">+</span> <span class="n">st</span><span class="o">.</span><span class="n">norm</span><span class="o">.</span><span class="n">ppf</span><span class="p">(</span><span class="n">alpha</span><span class="p">)</span> <span class="o">*</span> <span class="n">hsigma</span><span class="p">)</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">nmeans</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">+</span> <span class="n">st</span><span class="o">.</span><span class="n">norm</span><span class="o">.</span><span class="n">ppf</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">alpha</span><span class="p">)</span> <span class="o">*</span> <span class="n">hsigma</span><span class="p">)</span>
|
||||
|
||||
<span class="n">intervals</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
|
||||
<span class="n">dist</span><span class="o">.</span><span class="n">append_interval</span><span class="p">(</span><span class="n">intervals</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">dist</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div></div>
|
||||
</pre></div>
|
||||
|
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|
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|
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1234
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<h1>Source code for pyFTS.benchmarks.knn</h1><div class="highlight"><pre>
|
||||
<span></span><span class="ch">#!/usr/bin/python</span>
|
||||
<span class="c1"># -*- coding: utf8 -*-</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">statsmodels.tsa.tsatools</span> <span class="k">import</span> <span class="n">lagmat</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">fts</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">ProbabilityDistribution</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="KNearestNeighbors"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.knn.KNearestNeighbors">[docs]</a><span class="k">class</span> <span class="nc">KNearestNeighbors</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> K-Nearest Neighbors</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">KNearestNeighbors</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"kNN"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">"kNN"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">"K-Nearest Neighbors"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_point_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_interval_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_probability_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">benchmark_only</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_order</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">alpha</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"alpha"</span><span class="p">,</span> <span class="mf">0.05</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">lag</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">k</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"k"</span><span class="p">,</span> <span class="mi">30</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">uod</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
|
||||
<div class="viewcode-block" id="KNearestNeighbors.train"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.knn.KNearestNeighbors.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">data</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">data</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="KNearestNeighbors.knn"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.knn.KNearestNeighbors.knn">[docs]</a> <span class="k">def</span> <span class="nf">knn</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sample</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">dist</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">apply_along_axis</span><span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="p">(</span><span class="n">x</span> <span class="o">-</span> <span class="n">sample</span><span class="p">)</span> <span class="o">**</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">ix</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">argsort</span><span class="p">(</span><span class="n">dist</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">dist</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">)):</span>
|
||||
<span class="n">dist</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">sum</span><span class="p">([</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="n">kk</span><span class="p">]</span> <span class="o">-</span> <span class="n">sample</span><span class="p">[</span><span class="n">kk</span><span class="p">])</span><span class="o">**</span><span class="mi">2</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">)]))</span>
|
||||
<span class="n">ix</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">argsort</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">dist</span><span class="p">))</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">+</span> <span class="mi">1</span>
|
||||
|
||||
<span class="n">ix2</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">clip</span><span class="p">(</span><span class="n">ix</span><span class="p">[:</span><span class="bp">self</span><span class="o">.</span><span class="n">k</span><span class="p">],</span> <span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">)</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">[</span><span class="n">ix2</span><span class="p">]</span></div>
|
||||
|
||||
<div class="viewcode-block" id="KNearestNeighbors.forecast_distribution"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.knn.KNearestNeighbors.forecast_distribution">[docs]</a> <span class="k">def</span> <span class="nf">forecast_distribution</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">smooth</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"smooth"</span><span class="p">,</span> <span class="s2">"KDE"</span><span class="p">)</span>
|
||||
<span class="n">alpha</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"alpha"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="n">uod</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_UoD</span><span class="p">()</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)):</span>
|
||||
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span><span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="p">:</span> <span class="n">k</span><span class="p">]</span>
|
||||
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">knn</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
|
||||
<span class="n">dist</span> <span class="o">=</span> <span class="n">ProbabilityDistribution</span><span class="o">.</span><span class="n">ProbabilityDistribution</span><span class="p">(</span><span class="n">smooth</span><span class="p">,</span> <span class="n">uod</span><span class="o">=</span><span class="n">uod</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">forecasts</span><span class="p">,</span>
|
||||
<span class="n">name</span><span class="o">=</span><span class="s2">""</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">dist</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div></div>
|
||||
|
||||
|
||||
</pre></div>
|
||||
|
||||
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|
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|
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|
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|
||||
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|
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|
||||
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|
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|
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|
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|
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96
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<h1>Source code for pyFTS.benchmarks.naive</h1><div class="highlight"><pre>
|
||||
<span></span><span class="ch">#!/usr/bin/python</span>
|
||||
<span class="c1"># -*- coding: utf8 -*-</span>
|
||||
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">fts</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="Naive"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.naive.Naive">[docs]</a><span class="k">class</span> <span class="nc">Naive</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
|
||||
<span class="sd">"""Naïve Forecasting method"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">Naive</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">"Naive"</span><span class="p">,</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Naïve Model"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">"Naïve Model"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">benchmark_only</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
|
||||
<div class="viewcode-block" id="Naive.forecast"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.naive.Naive.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">data</span></div></div>
|
||||
|
||||
</pre></div>
|
||||
|
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|
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|
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|
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<li><a href="../../index.html">Module code</a><ul>
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476
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vendored
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476
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vendored
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<h1>Source code for pyFTS.benchmarks.parallel_benchmarks</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">joblib Parallelized Benchmarks to FTS methods</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">datetime</span>
|
||||
<span class="kn">import</span> <span class="nn">multiprocessing</span>
|
||||
<span class="kn">import</span> <span class="nn">time</span>
|
||||
<span class="kn">from</span> <span class="nn">copy</span> <span class="k">import</span> <span class="n">deepcopy</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">joblib</span> <span class="k">import</span> <span class="n">Parallel</span><span class="p">,</span> <span class="n">delayed</span>
|
||||
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">benchmarks</span><span class="p">,</span> <span class="n">Util</span> <span class="k">as</span> <span class="n">bUtil</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Util</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="run_point"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.parallel_benchmarks.run_point">[docs]</a><span class="k">def</span> <span class="nf">run_point</span><span class="p">(</span><span class="n">mfts</span><span class="p">,</span> <span class="n">partitioner</span><span class="p">,</span> <span class="n">train_data</span><span class="p">,</span> <span class="n">test_data</span><span class="p">,</span> <span class="n">transformation</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">indexer</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Point forecast benchmark function to be executed on threads</span>
|
||||
<span class="sd"> :param mfts: FTS model</span>
|
||||
<span class="sd"> :param partitioner: Universe of Discourse partitioner</span>
|
||||
<span class="sd"> :param train_data: data used to train the model</span>
|
||||
<span class="sd"> :param test_data: ata used to test the model</span>
|
||||
<span class="sd"> :param window_key: id of the sliding window</span>
|
||||
<span class="sd"> :param transformation: data transformation</span>
|
||||
<span class="sd"> :param indexer: seasonal indexer</span>
|
||||
<span class="sd"> :return: a dictionary with the benchmark results </span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">pttr</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="vm">__module__</span><span class="p">)</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">'.'</span><span class="p">)[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
|
||||
<span class="n">_key</span> <span class="o">=</span> <span class="n">mfts</span><span class="o">.</span><span class="n">shortname</span> <span class="o">+</span> <span class="s2">" n = "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">mfts</span><span class="o">.</span><span class="n">order</span><span class="p">)</span> <span class="o">+</span> <span class="s2">" "</span> <span class="o">+</span> <span class="n">pttr</span> <span class="o">+</span> <span class="s2">" q = "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="n">partitions</span><span class="p">)</span>
|
||||
<span class="n">mfts</span><span class="o">.</span><span class="n">partitioner</span> <span class="o">=</span> <span class="n">partitioner</span>
|
||||
<span class="k">if</span> <span class="n">transformation</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">mfts</span><span class="o">.</span><span class="n">append_transformation</span><span class="p">(</span><span class="n">transformation</span><span class="p">)</span>
|
||||
|
||||
<span class="k">try</span><span class="p">:</span>
|
||||
<span class="n">_start</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
<span class="n">mfts</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="n">train_data</span><span class="p">,</span> <span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="n">mfts</span><span class="o">.</span><span class="n">order</span><span class="p">)</span>
|
||||
<span class="n">_end</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
<span class="n">times</span> <span class="o">=</span> <span class="n">_end</span> <span class="o">-</span> <span class="n">_start</span>
|
||||
|
||||
<span class="n">_start</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
<span class="n">_rmse</span><span class="p">,</span> <span class="n">_smape</span><span class="p">,</span> <span class="n">_u</span> <span class="o">=</span> <span class="n">benchmarks</span><span class="o">.</span><span class="n">get_point_statistics</span><span class="p">(</span><span class="n">test_data</span><span class="p">,</span> <span class="n">mfts</span><span class="p">,</span> <span class="n">indexer</span><span class="p">)</span>
|
||||
<span class="n">_end</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
<span class="n">times</span> <span class="o">+=</span> <span class="n">_end</span> <span class="o">-</span> <span class="n">_start</span>
|
||||
<span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
|
||||
<span class="nb">print</span><span class="p">(</span><span class="n">e</span><span class="p">)</span>
|
||||
<span class="n">_rmse</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
|
||||
<span class="n">_smape</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
|
||||
<span class="n">_u</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
|
||||
<span class="n">times</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'key'</span><span class="p">:</span> <span class="n">_key</span><span class="p">,</span> <span class="s1">'obj'</span><span class="p">:</span> <span class="n">mfts</span><span class="p">,</span> <span class="s1">'rmse'</span><span class="p">:</span> <span class="n">_rmse</span><span class="p">,</span> <span class="s1">'smape'</span><span class="p">:</span> <span class="n">_smape</span><span class="p">,</span> <span class="s1">'u'</span><span class="p">:</span> <span class="n">_u</span><span class="p">,</span> <span class="s1">'time'</span><span class="p">:</span> <span class="n">times</span><span class="p">}</span>
|
||||
|
||||
<span class="nb">print</span><span class="p">(</span><span class="n">ret</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="point_sliding_window"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.parallel_benchmarks.point_sliding_window">[docs]</a><span class="k">def</span> <span class="nf">point_sliding_window</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">windowsize</span><span class="p">,</span> <span class="n">train</span><span class="o">=</span><span class="mf">0.8</span><span class="p">,</span> <span class="n">models</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">partitioners</span><span class="o">=</span><span class="p">[</span><span class="n">Grid</span><span class="o">.</span><span class="n">GridPartitioner</span><span class="p">],</span>
|
||||
<span class="n">partitions</span><span class="o">=</span><span class="p">[</span><span class="mi">10</span><span class="p">],</span> <span class="n">max_order</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">transformation</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">indexer</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dump</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
|
||||
<span class="n">save</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">file</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">sintetic</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Parallel sliding window benchmarks for FTS point forecasters</span>
|
||||
<span class="sd"> :param data: </span>
|
||||
<span class="sd"> :param windowsize: size of sliding window</span>
|
||||
<span class="sd"> :param train: percentual of sliding window data used to train the models</span>
|
||||
<span class="sd"> :param models: FTS point forecasters</span>
|
||||
<span class="sd"> :param partitioners: Universe of Discourse partitioner</span>
|
||||
<span class="sd"> :param partitions: the max number of partitions on the Universe of Discourse </span>
|
||||
<span class="sd"> :param max_order: the max order of the models (for high order models)</span>
|
||||
<span class="sd"> :param transformation: data transformation</span>
|
||||
<span class="sd"> :param indexer: seasonal indexer</span>
|
||||
<span class="sd"> :param dump: </span>
|
||||
<span class="sd"> :param save: save results</span>
|
||||
<span class="sd"> :param file: file path to save the results</span>
|
||||
<span class="sd"> :param sintetic: if true only the average and standard deviation of the results</span>
|
||||
<span class="sd"> :return: DataFrame with the results</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">_process_start</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
|
||||
<span class="nb">print</span><span class="p">(</span><span class="s2">"Process Start: {0: %H:%M:%S}"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">()))</span>
|
||||
|
||||
<span class="n">num_cores</span> <span class="o">=</span> <span class="n">multiprocessing</span><span class="o">.</span><span class="n">cpu_count</span><span class="p">()</span>
|
||||
|
||||
<span class="n">pool</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">objs</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="n">rmse</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="n">smape</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="n">u</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="n">times</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">model</span> <span class="ow">in</span> <span class="n">benchmarks</span><span class="o">.</span><span class="n">get_point_methods</span><span class="p">():</span>
|
||||
<span class="n">mfts</span> <span class="o">=</span> <span class="n">model</span><span class="p">(</span><span class="s2">""</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">mfts</span><span class="o">.</span><span class="n">is_high_order</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">order</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">max_order</span> <span class="o">+</span> <span class="mi">1</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">order</span> <span class="o">>=</span> <span class="n">mfts</span><span class="o">.</span><span class="n">min_order</span><span class="p">:</span>
|
||||
<span class="n">mfts</span> <span class="o">=</span> <span class="n">model</span><span class="p">(</span><span class="s2">""</span><span class="p">)</span>
|
||||
<span class="n">mfts</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="n">order</span>
|
||||
<span class="n">pool</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mfts</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">pool</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mfts</span><span class="p">)</span>
|
||||
|
||||
<span class="n">experiments</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">train</span><span class="p">,</span> <span class="n">test</span> <span class="ow">in</span> <span class="n">Util</span><span class="o">.</span><span class="n">sliding_window</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">windowsize</span><span class="p">,</span> <span class="n">train</span><span class="p">):</span>
|
||||
<span class="n">experiments</span> <span class="o">+=</span> <span class="mi">1</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">dump</span><span class="p">:</span> <span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">Window: </span><span class="si">{0}</span><span class="se">\n</span><span class="s1">'</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">ct</span><span class="p">))</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">partition</span> <span class="ow">in</span> <span class="n">partitions</span><span class="p">:</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">partitioner</span> <span class="ow">in</span> <span class="n">partitioners</span><span class="p">:</span>
|
||||
|
||||
<span class="n">data_train_fs</span> <span class="o">=</span> <span class="n">partitioner</span><span class="p">(</span><span class="n">train</span><span class="p">,</span> <span class="n">partition</span><span class="p">,</span> <span class="n">transformation</span><span class="o">=</span><span class="n">transformation</span><span class="p">)</span>
|
||||
|
||||
<span class="n">results</span> <span class="o">=</span> <span class="n">Parallel</span><span class="p">(</span><span class="n">n_jobs</span><span class="o">=</span><span class="n">num_cores</span><span class="p">)(</span>
|
||||
<span class="n">delayed</span><span class="p">(</span><span class="n">run_point</span><span class="p">)(</span><span class="n">deepcopy</span><span class="p">(</span><span class="n">m</span><span class="p">),</span> <span class="n">deepcopy</span><span class="p">(</span><span class="n">data_train_fs</span><span class="p">),</span> <span class="n">deepcopy</span><span class="p">(</span><span class="n">train</span><span class="p">),</span> <span class="n">deepcopy</span><span class="p">(</span><span class="n">test</span><span class="p">),</span>
|
||||
<span class="n">transformation</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">m</span> <span class="ow">in</span> <span class="n">pool</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">tmp</span> <span class="ow">in</span> <span class="n">results</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">objs</span><span class="p">:</span>
|
||||
<span class="n">objs</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span> <span class="o">=</span> <span class="n">tmp</span><span class="p">[</span><span class="s1">'obj'</span><span class="p">]</span>
|
||||
<span class="n">rmse</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">smape</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">u</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">times</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">rmse</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'rmse'</span><span class="p">])</span>
|
||||
<span class="n">smape</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'smape'</span><span class="p">])</span>
|
||||
<span class="n">u</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'u'</span><span class="p">])</span>
|
||||
<span class="n">times</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'time'</span><span class="p">])</span>
|
||||
|
||||
<span class="n">_process_end</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
|
||||
<span class="nb">print</span><span class="p">(</span><span class="s2">"Process End: {0: %H:%M:%S}"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">()))</span>
|
||||
|
||||
<span class="nb">print</span><span class="p">(</span><span class="s2">"Process Duration: </span><span class="si">{0}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">_process_end</span> <span class="o">-</span> <span class="n">_process_start</span><span class="p">))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">Util</span><span class="o">.</span><span class="n">save_dataframe_point</span><span class="p">(</span><span class="n">experiments</span><span class="p">,</span> <span class="n">file</span><span class="p">,</span> <span class="n">objs</span><span class="p">,</span> <span class="n">rmse</span><span class="p">,</span> <span class="n">save</span><span class="p">,</span> <span class="n">sintetic</span><span class="p">,</span> <span class="n">smape</span><span class="p">,</span> <span class="n">times</span><span class="p">,</span> <span class="n">u</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="run_interval"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.parallel_benchmarks.run_interval">[docs]</a><span class="k">def</span> <span class="nf">run_interval</span><span class="p">(</span><span class="n">mfts</span><span class="p">,</span> <span class="n">partitioner</span><span class="p">,</span> <span class="n">train_data</span><span class="p">,</span> <span class="n">test_data</span><span class="p">,</span> <span class="n">transformation</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">indexer</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Interval forecast benchmark function to be executed on threads</span>
|
||||
<span class="sd"> :param mfts: FTS model</span>
|
||||
<span class="sd"> :param partitioner: Universe of Discourse partitioner</span>
|
||||
<span class="sd"> :param train_data: data used to train the model</span>
|
||||
<span class="sd"> :param test_data: ata used to test the model</span>
|
||||
<span class="sd"> :param window_key: id of the sliding window</span>
|
||||
<span class="sd"> :param transformation: data transformation</span>
|
||||
<span class="sd"> :param indexer: seasonal indexer</span>
|
||||
<span class="sd"> :return: a dictionary with the benchmark results </span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">pttr</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="vm">__module__</span><span class="p">)</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">'.'</span><span class="p">)[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
|
||||
<span class="n">_key</span> <span class="o">=</span> <span class="n">mfts</span><span class="o">.</span><span class="n">shortname</span> <span class="o">+</span> <span class="s2">" n = "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">mfts</span><span class="o">.</span><span class="n">order</span><span class="p">)</span> <span class="o">+</span> <span class="s2">" "</span> <span class="o">+</span> <span class="n">pttr</span> <span class="o">+</span> <span class="s2">" q = "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="n">partitions</span><span class="p">)</span>
|
||||
<span class="n">mfts</span><span class="o">.</span><span class="n">partitioner</span> <span class="o">=</span> <span class="n">partitioner</span>
|
||||
<span class="k">if</span> <span class="n">transformation</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">mfts</span><span class="o">.</span><span class="n">append_transformation</span><span class="p">(</span><span class="n">transformation</span><span class="p">)</span>
|
||||
|
||||
<span class="k">try</span><span class="p">:</span>
|
||||
<span class="n">_start</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
<span class="n">mfts</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="n">train_data</span><span class="p">,</span> <span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="n">mfts</span><span class="o">.</span><span class="n">order</span><span class="p">)</span>
|
||||
<span class="n">_end</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
<span class="n">times</span> <span class="o">=</span> <span class="n">_end</span> <span class="o">-</span> <span class="n">_start</span>
|
||||
|
||||
<span class="n">_start</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
<span class="n">_sharp</span><span class="p">,</span> <span class="n">_res</span><span class="p">,</span> <span class="n">_cov</span> <span class="o">=</span> <span class="n">benchmarks</span><span class="o">.</span><span class="n">get_interval_statistics</span><span class="p">(</span><span class="n">test_data</span><span class="p">,</span> <span class="n">mfts</span><span class="p">)</span>
|
||||
<span class="n">_end</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
<span class="n">times</span> <span class="o">+=</span> <span class="n">_end</span> <span class="o">-</span> <span class="n">_start</span>
|
||||
<span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
|
||||
<span class="nb">print</span><span class="p">(</span><span class="n">e</span><span class="p">)</span>
|
||||
<span class="n">_sharp</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
|
||||
<span class="n">_res</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
|
||||
<span class="n">_cov</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
|
||||
<span class="n">times</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'key'</span><span class="p">:</span> <span class="n">_key</span><span class="p">,</span> <span class="s1">'obj'</span><span class="p">:</span> <span class="n">mfts</span><span class="p">,</span> <span class="s1">'sharpness'</span><span class="p">:</span> <span class="n">_sharp</span><span class="p">,</span> <span class="s1">'resolution'</span><span class="p">:</span> <span class="n">_res</span><span class="p">,</span> <span class="s1">'coverage'</span><span class="p">:</span> <span class="n">_cov</span><span class="p">,</span> <span class="s1">'time'</span><span class="p">:</span> <span class="n">times</span><span class="p">}</span>
|
||||
|
||||
<span class="nb">print</span><span class="p">(</span><span class="n">ret</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="interval_sliding_window"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.parallel_benchmarks.interval_sliding_window">[docs]</a><span class="k">def</span> <span class="nf">interval_sliding_window</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">windowsize</span><span class="p">,</span> <span class="n">train</span><span class="o">=</span><span class="mf">0.8</span><span class="p">,</span> <span class="n">models</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">partitioners</span><span class="o">=</span><span class="p">[</span><span class="n">Grid</span><span class="o">.</span><span class="n">GridPartitioner</span><span class="p">],</span>
|
||||
<span class="n">partitions</span><span class="o">=</span><span class="p">[</span><span class="mi">10</span><span class="p">],</span> <span class="n">max_order</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">transformation</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">indexer</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dump</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
|
||||
<span class="n">save</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">file</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">sintetic</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Parallel sliding window benchmarks for FTS point_to_interval forecasters</span>
|
||||
<span class="sd"> :param data: </span>
|
||||
<span class="sd"> :param windowsize: size of sliding window</span>
|
||||
<span class="sd"> :param train: percentual of sliding window data used to train the models</span>
|
||||
<span class="sd"> :param models: FTS point forecasters</span>
|
||||
<span class="sd"> :param partitioners: Universe of Discourse partitioner</span>
|
||||
<span class="sd"> :param partitions: the max number of partitions on the Universe of Discourse </span>
|
||||
<span class="sd"> :param max_order: the max order of the models (for high order models)</span>
|
||||
<span class="sd"> :param transformation: data transformation</span>
|
||||
<span class="sd"> :param indexer: seasonal indexer</span>
|
||||
<span class="sd"> :param dump: </span>
|
||||
<span class="sd"> :param save: save results</span>
|
||||
<span class="sd"> :param file: file path to save the results</span>
|
||||
<span class="sd"> :param sintetic: if true only the average and standard deviation of the results</span>
|
||||
<span class="sd"> :return: DataFrame with the results</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">_process_start</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
|
||||
<span class="nb">print</span><span class="p">(</span><span class="s2">"Process Start: {0: %H:%M:%S}"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">()))</span>
|
||||
|
||||
<span class="n">num_cores</span> <span class="o">=</span> <span class="n">multiprocessing</span><span class="o">.</span><span class="n">cpu_count</span><span class="p">()</span>
|
||||
|
||||
<span class="n">pool</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">objs</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="n">sharpness</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="n">resolution</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="n">coverage</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="n">times</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">model</span> <span class="ow">in</span> <span class="n">benchmarks</span><span class="o">.</span><span class="n">get_interval_methods</span><span class="p">():</span>
|
||||
<span class="n">mfts</span> <span class="o">=</span> <span class="n">model</span><span class="p">(</span><span class="s2">""</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">mfts</span><span class="o">.</span><span class="n">is_high_order</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">order</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">max_order</span> <span class="o">+</span> <span class="mi">1</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">order</span> <span class="o">>=</span> <span class="n">mfts</span><span class="o">.</span><span class="n">min_order</span><span class="p">:</span>
|
||||
<span class="n">mfts</span> <span class="o">=</span> <span class="n">model</span><span class="p">(</span><span class="s2">""</span><span class="p">)</span>
|
||||
<span class="n">mfts</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="n">order</span>
|
||||
<span class="n">pool</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mfts</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">pool</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mfts</span><span class="p">)</span>
|
||||
|
||||
<span class="n">experiments</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">train</span><span class="p">,</span> <span class="n">test</span> <span class="ow">in</span> <span class="n">Util</span><span class="o">.</span><span class="n">sliding_window</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">windowsize</span><span class="p">,</span> <span class="n">train</span><span class="p">):</span>
|
||||
<span class="n">experiments</span> <span class="o">+=</span> <span class="mi">1</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">dump</span><span class="p">:</span> <span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">Window: </span><span class="si">{0}</span><span class="se">\n</span><span class="s1">'</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">ct</span><span class="p">))</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">partition</span> <span class="ow">in</span> <span class="n">partitions</span><span class="p">:</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">partitioner</span> <span class="ow">in</span> <span class="n">partitioners</span><span class="p">:</span>
|
||||
|
||||
<span class="n">data_train_fs</span> <span class="o">=</span> <span class="n">partitioner</span><span class="p">(</span><span class="n">train</span><span class="p">,</span> <span class="n">partition</span><span class="p">,</span> <span class="n">transformation</span><span class="o">=</span><span class="n">transformation</span><span class="p">)</span>
|
||||
|
||||
<span class="n">results</span> <span class="o">=</span> <span class="n">Parallel</span><span class="p">(</span><span class="n">n_jobs</span><span class="o">=</span><span class="n">num_cores</span><span class="p">)(</span>
|
||||
<span class="n">delayed</span><span class="p">(</span><span class="n">run_interval</span><span class="p">)(</span><span class="n">deepcopy</span><span class="p">(</span><span class="n">m</span><span class="p">),</span> <span class="n">deepcopy</span><span class="p">(</span><span class="n">data_train_fs</span><span class="p">),</span> <span class="n">deepcopy</span><span class="p">(</span><span class="n">train</span><span class="p">),</span> <span class="n">deepcopy</span><span class="p">(</span><span class="n">test</span><span class="p">),</span>
|
||||
<span class="n">transformation</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">m</span> <span class="ow">in</span> <span class="n">pool</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">tmp</span> <span class="ow">in</span> <span class="n">results</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">objs</span><span class="p">:</span>
|
||||
<span class="n">objs</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span> <span class="o">=</span> <span class="n">tmp</span><span class="p">[</span><span class="s1">'obj'</span><span class="p">]</span>
|
||||
<span class="n">sharpness</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">resolution</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">coverage</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">times</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">sharpness</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'sharpness'</span><span class="p">])</span>
|
||||
<span class="n">resolution</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'resolution'</span><span class="p">])</span>
|
||||
<span class="n">coverage</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'coverage'</span><span class="p">])</span>
|
||||
<span class="n">times</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'time'</span><span class="p">])</span>
|
||||
|
||||
<span class="n">_process_end</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
|
||||
<span class="nb">print</span><span class="p">(</span><span class="s2">"Process End: {0: %H:%M:%S}"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">()))</span>
|
||||
|
||||
<span class="nb">print</span><span class="p">(</span><span class="s2">"Process Duration: </span><span class="si">{0}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">_process_end</span> <span class="o">-</span> <span class="n">_process_start</span><span class="p">))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">Util</span><span class="o">.</span><span class="n">save_dataframe_interval</span><span class="p">(</span><span class="n">coverage</span><span class="p">,</span> <span class="n">experiments</span><span class="p">,</span> <span class="n">file</span><span class="p">,</span> <span class="n">objs</span><span class="p">,</span> <span class="n">resolution</span><span class="p">,</span> <span class="n">save</span><span class="p">,</span> <span class="n">sharpness</span><span class="p">,</span> <span class="n">sintetic</span><span class="p">,</span> <span class="n">times</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="run_ahead"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.parallel_benchmarks.run_ahead">[docs]</a><span class="k">def</span> <span class="nf">run_ahead</span><span class="p">(</span><span class="n">mfts</span><span class="p">,</span> <span class="n">partitioner</span><span class="p">,</span> <span class="n">train_data</span><span class="p">,</span> <span class="n">test_data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="n">resolution</span><span class="p">,</span> <span class="n">transformation</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">indexer</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Probabilistic m-step ahead forecast benchmark function to be executed on threads</span>
|
||||
<span class="sd"> :param mfts: FTS model</span>
|
||||
<span class="sd"> :param partitioner: Universe of Discourse partitioner</span>
|
||||
<span class="sd"> :param train_data: data used to train the model</span>
|
||||
<span class="sd"> :param test_data: ata used to test the model </span>
|
||||
<span class="sd"> :param steps: </span>
|
||||
<span class="sd"> :param resolution: </span>
|
||||
<span class="sd"> :param transformation: data transformation</span>
|
||||
<span class="sd"> :param indexer: seasonal indexer</span>
|
||||
<span class="sd"> :return: a dictionary with the benchmark results </span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">pttr</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="vm">__module__</span><span class="p">)</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">'.'</span><span class="p">)[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
|
||||
<span class="n">_key</span> <span class="o">=</span> <span class="n">mfts</span><span class="o">.</span><span class="n">shortname</span> <span class="o">+</span> <span class="s2">" n = "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">mfts</span><span class="o">.</span><span class="n">order</span><span class="p">)</span> <span class="o">+</span> <span class="s2">" "</span> <span class="o">+</span> <span class="n">pttr</span> <span class="o">+</span> <span class="s2">" q = "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="n">partitions</span><span class="p">)</span>
|
||||
<span class="n">mfts</span><span class="o">.</span><span class="n">partitioner</span> <span class="o">=</span> <span class="n">partitioner</span>
|
||||
<span class="k">if</span> <span class="n">transformation</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">mfts</span><span class="o">.</span><span class="n">append_transformation</span><span class="p">(</span><span class="n">transformation</span><span class="p">)</span>
|
||||
|
||||
<span class="k">try</span><span class="p">:</span>
|
||||
<span class="n">_start</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
<span class="n">mfts</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="n">train_data</span><span class="p">,</span> <span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="n">mfts</span><span class="o">.</span><span class="n">order</span><span class="p">)</span>
|
||||
<span class="n">_end</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
<span class="n">times</span> <span class="o">=</span> <span class="n">_end</span> <span class="o">-</span> <span class="n">_start</span>
|
||||
|
||||
<span class="n">_crps1</span><span class="p">,</span> <span class="n">_crps2</span><span class="p">,</span> <span class="n">_t1</span><span class="p">,</span> <span class="n">_t2</span> <span class="o">=</span> <span class="n">benchmarks</span><span class="o">.</span><span class="n">get_distribution_statistics</span><span class="p">(</span><span class="n">test_data</span><span class="p">,</span> <span class="n">mfts</span><span class="p">,</span> <span class="n">steps</span><span class="o">=</span><span class="n">steps</span><span class="p">,</span>
|
||||
<span class="n">resolution</span><span class="o">=</span><span class="n">resolution</span><span class="p">)</span>
|
||||
<span class="n">_t1</span> <span class="o">+=</span> <span class="n">times</span>
|
||||
<span class="n">_t2</span> <span class="o">+=</span> <span class="n">times</span>
|
||||
<span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">e</span><span class="p">:</span>
|
||||
<span class="nb">print</span><span class="p">(</span><span class="n">e</span><span class="p">)</span>
|
||||
<span class="n">_crps1</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
|
||||
<span class="n">_crps2</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
|
||||
<span class="n">_t1</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
|
||||
<span class="n">_t2</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'key'</span><span class="p">:</span> <span class="n">_key</span><span class="p">,</span> <span class="s1">'obj'</span><span class="p">:</span> <span class="n">mfts</span><span class="p">,</span> <span class="s1">'CRPS_Interval'</span><span class="p">:</span> <span class="n">_crps1</span><span class="p">,</span> <span class="s1">'CRPS_Distribution'</span><span class="p">:</span> <span class="n">_crps2</span><span class="p">,</span> <span class="s1">'TIME_Interval'</span><span class="p">:</span> <span class="n">_t1</span><span class="p">,</span> <span class="s1">'TIME_Distribution'</span><span class="p">:</span> <span class="n">_t2</span><span class="p">}</span>
|
||||
|
||||
<span class="nb">print</span><span class="p">(</span><span class="n">ret</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ahead_sliding_window"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.parallel_benchmarks.ahead_sliding_window">[docs]</a><span class="k">def</span> <span class="nf">ahead_sliding_window</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">windowsize</span><span class="p">,</span> <span class="n">train</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span><span class="n">resolution</span><span class="p">,</span> <span class="n">models</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">partitioners</span><span class="o">=</span><span class="p">[</span><span class="n">Grid</span><span class="o">.</span><span class="n">GridPartitioner</span><span class="p">],</span>
|
||||
<span class="n">partitions</span><span class="o">=</span><span class="p">[</span><span class="mi">10</span><span class="p">],</span> <span class="n">max_order</span><span class="o">=</span><span class="mi">3</span><span class="p">,</span> <span class="n">transformation</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">indexer</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">dump</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span>
|
||||
<span class="n">save</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">file</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">sintetic</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Parallel sliding window benchmarks for FTS probabilistic forecasters</span>
|
||||
<span class="sd"> :param data: </span>
|
||||
<span class="sd"> :param windowsize: size of sliding window</span>
|
||||
<span class="sd"> :param train: percentual of sliding window data used to train the models</span>
|
||||
<span class="sd"> :param steps: </span>
|
||||
<span class="sd"> :param resolution: </span>
|
||||
<span class="sd"> :param models: FTS point forecasters</span>
|
||||
<span class="sd"> :param partitioners: Universe of Discourse partitioner</span>
|
||||
<span class="sd"> :param partitions: the max number of partitions on the Universe of Discourse </span>
|
||||
<span class="sd"> :param max_order: the max order of the models (for high order models)</span>
|
||||
<span class="sd"> :param transformation: data transformation</span>
|
||||
<span class="sd"> :param indexer: seasonal indexer</span>
|
||||
<span class="sd"> :param dump: </span>
|
||||
<span class="sd"> :param save: save results</span>
|
||||
<span class="sd"> :param file: file path to save the results</span>
|
||||
<span class="sd"> :param sintetic: if true only the average and standard deviation of the results</span>
|
||||
<span class="sd"> :return: DataFrame with the results </span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">_process_start</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
|
||||
<span class="nb">print</span><span class="p">(</span><span class="s2">"Process Start: {0: %H:%M:%S}"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">()))</span>
|
||||
|
||||
<span class="n">num_cores</span> <span class="o">=</span> <span class="n">multiprocessing</span><span class="o">.</span><span class="n">cpu_count</span><span class="p">()</span>
|
||||
|
||||
<span class="n">pool</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">objs</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="n">crps_interval</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="n">crps_distr</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="n">times1</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="n">times2</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">model</span> <span class="ow">in</span> <span class="n">benchmarks</span><span class="o">.</span><span class="n">get_interval_methods</span><span class="p">():</span>
|
||||
<span class="n">mfts</span> <span class="o">=</span> <span class="n">model</span><span class="p">(</span><span class="s2">""</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">mfts</span><span class="o">.</span><span class="n">is_high_order</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">order</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">max_order</span> <span class="o">+</span> <span class="mi">1</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">order</span> <span class="o">>=</span> <span class="n">mfts</span><span class="o">.</span><span class="n">min_order</span><span class="p">:</span>
|
||||
<span class="n">mfts</span> <span class="o">=</span> <span class="n">model</span><span class="p">(</span><span class="s2">""</span><span class="p">)</span>
|
||||
<span class="n">mfts</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="n">order</span>
|
||||
<span class="n">pool</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mfts</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">pool</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mfts</span><span class="p">)</span>
|
||||
|
||||
<span class="n">experiments</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">train</span><span class="p">,</span> <span class="n">test</span> <span class="ow">in</span> <span class="n">Util</span><span class="o">.</span><span class="n">sliding_window</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">windowsize</span><span class="p">,</span> <span class="n">train</span><span class="p">):</span>
|
||||
<span class="n">experiments</span> <span class="o">+=</span> <span class="mi">1</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">dump</span><span class="p">:</span> <span class="nb">print</span><span class="p">(</span><span class="s1">'</span><span class="se">\n</span><span class="s1">Window: </span><span class="si">{0}</span><span class="se">\n</span><span class="s1">'</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">ct</span><span class="p">))</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">partition</span> <span class="ow">in</span> <span class="n">partitions</span><span class="p">:</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">partitioner</span> <span class="ow">in</span> <span class="n">partitioners</span><span class="p">:</span>
|
||||
|
||||
<span class="n">data_train_fs</span> <span class="o">=</span> <span class="n">partitioner</span><span class="p">(</span><span class="n">train</span><span class="p">,</span> <span class="n">partition</span><span class="p">,</span> <span class="n">transformation</span><span class="o">=</span><span class="n">transformation</span><span class="p">)</span>
|
||||
|
||||
<span class="n">results</span> <span class="o">=</span> <span class="n">Parallel</span><span class="p">(</span><span class="n">n_jobs</span><span class="o">=</span><span class="n">num_cores</span><span class="p">)(</span>
|
||||
<span class="n">delayed</span><span class="p">(</span><span class="n">run_ahead</span><span class="p">)(</span><span class="n">deepcopy</span><span class="p">(</span><span class="n">m</span><span class="p">),</span> <span class="n">deepcopy</span><span class="p">(</span><span class="n">data_train_fs</span><span class="p">),</span> <span class="n">deepcopy</span><span class="p">(</span><span class="n">train</span><span class="p">),</span> <span class="n">deepcopy</span><span class="p">(</span><span class="n">test</span><span class="p">),</span>
|
||||
<span class="n">steps</span><span class="p">,</span> <span class="n">resolution</span><span class="p">,</span> <span class="n">transformation</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">m</span> <span class="ow">in</span> <span class="n">pool</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">tmp</span> <span class="ow">in</span> <span class="n">results</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">objs</span><span class="p">:</span>
|
||||
<span class="n">objs</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span> <span class="o">=</span> <span class="n">tmp</span><span class="p">[</span><span class="s1">'obj'</span><span class="p">]</span>
|
||||
<span class="n">crps_interval</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">crps_distr</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">times1</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">times2</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">crps_interval</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'CRPS_Interval'</span><span class="p">])</span>
|
||||
<span class="n">crps_distr</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'CRPS_Distribution'</span><span class="p">])</span>
|
||||
<span class="n">times1</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'TIME_Interval'</span><span class="p">])</span>
|
||||
<span class="n">times2</span><span class="p">[</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'key'</span><span class="p">]]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="s1">'TIME_Distribution'</span><span class="p">])</span>
|
||||
|
||||
<span class="n">_process_end</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
|
||||
|
||||
<span class="nb">print</span><span class="p">(</span><span class="s2">"Process End: {0: %H:%M:%S}"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">()))</span>
|
||||
|
||||
<span class="nb">print</span><span class="p">(</span><span class="s2">"Process Duration: </span><span class="si">{0}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">_process_end</span> <span class="o">-</span> <span class="n">_process_start</span><span class="p">))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">Util</span><span class="o">.</span><span class="n">save_dataframe_ahead</span><span class="p">(</span><span class="n">experiments</span><span class="p">,</span> <span class="n">file</span><span class="p">,</span> <span class="n">objs</span><span class="p">,</span> <span class="n">crps_interval</span><span class="p">,</span> <span class="n">crps_distr</span><span class="p">,</span> <span class="n">times1</span><span class="p">,</span> <span class="n">times2</span><span class="p">,</span> <span class="n">save</span><span class="p">,</span> <span class="n">sintetic</span><span class="p">)</span></div>
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
|
||||
<div class="sphinxsidebarwrapper"><div class="relations">
|
||||
<h3>Related Topics</h3>
|
||||
<ul>
|
||||
<li><a href="../../../index.html">Documentation overview</a><ul>
|
||||
<li><a href="../../index.html">Module code</a><ul>
|
||||
</ul></li>
|
||||
</ul></li>
|
||||
</ul>
|
||||
</div>
|
||||
<div id="searchbox" style="display: none" role="search">
|
||||
<h3>Quick search</h3>
|
||||
<div class="searchformwrapper">
|
||||
<form class="search" action="../../../search.html" method="get">
|
||||
<input type="text" name="q" />
|
||||
<input type="submit" value="Go" />
|
||||
<input type="hidden" name="check_keywords" value="yes" />
|
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<input type="hidden" name="area" value="default" />
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</form>
|
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</div>
|
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</div>
|
||||
<script type="text/javascript">$('#searchbox').show(0);</script>
|
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</div>
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</div>
|
||||
<div class="clearer"></div>
|
||||
</div>
|
||||
<div class="footer">
|
||||
©2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
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Powered by <a href="http://sphinx-doc.org/">Sphinx 1.7.2</a>
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& <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.10</a>
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</body>
|
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</html>
|
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231
docs/_build/html/_modules/pyFTS/benchmarks/quantreg.html
vendored
Normal file
231
docs/_build/html/_modules/pyFTS/benchmarks/quantreg.html
vendored
Normal file
@ -0,0 +1,231 @@
|
||||
|
||||
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
|
||||
"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
|
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|
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<html xmlns="http://www.w3.org/1999/xhtml">
|
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<head>
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<meta http-equiv="X-UA-Compatible" content="IE=Edge" />
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
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<title>pyFTS.benchmarks.quantreg — pyFTS 1.2.3 documentation</title>
|
||||
<link rel="stylesheet" href="../../../_static/alabaster.css" type="text/css" />
|
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<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
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<script type="text/javascript" src="../../../_static/documentation_options.js"></script>
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<script type="text/javascript" src="../../../_static/underscore.js"></script>
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<script type="text/javascript" src="../../../_static/doctools.js"></script>
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<script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script>
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<link rel="search" title="Search" href="../../../search.html" />
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<link rel="stylesheet" href="../../../_static/custom.css" type="text/css" />
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<meta name="viewport" content="width=device-width, initial-scale=0.9, maximum-scale=0.9" />
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</head><body>
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<div class="document">
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|
||||
<div class="bodywrapper">
|
||||
<div class="body" role="main">
|
||||
|
||||
<h1>Source code for pyFTS.benchmarks.quantreg</h1><div class="highlight"><pre>
|
||||
<span></span><span class="ch">#!/usr/bin/python</span>
|
||||
<span class="c1"># -*- coding: utf8 -*-</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
<span class="kn">from</span> <span class="nn">statsmodels.regression.quantile_regression</span> <span class="k">import</span> <span class="n">QuantReg</span>
|
||||
<span class="kn">from</span> <span class="nn">statsmodels.tsa.tsatools</span> <span class="k">import</span> <span class="n">lagmat</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">SortedCollection</span><span class="p">,</span> <span class="n">fts</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">ProbabilityDistribution</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="QuantileRegression"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.quantreg.QuantileRegression">[docs]</a><span class="k">class</span> <span class="nc">QuantileRegression</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
|
||||
<span class="sd">"""Façade for statsmodels.regression.quantile_regression"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">QuantileRegression</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"QR"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">"Quantile Regression"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_point_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_interval_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_probability_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">benchmark_only</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_order</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">alpha</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"alpha"</span><span class="p">,</span> <span class="mf">0.05</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">dist</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"dist"</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">upper_qt</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">mean_qt</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">lower_qt</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">dist_qt</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
|
||||
<div class="viewcode-block" id="QuantileRegression.train"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.quantreg.QuantileRegression.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">):</span>
|
||||
<span class="n">data</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_data</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="n">lagdata</span><span class="p">,</span> <span class="n">ndata</span> <span class="o">=</span> <span class="n">lagmat</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">maxlag</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">trim</span><span class="o">=</span><span class="s2">"both"</span><span class="p">,</span> <span class="n">original</span><span class="o">=</span><span class="s1">'sep'</span><span class="p">)</span>
|
||||
|
||||
<span class="n">mqt</span> <span class="o">=</span> <span class="n">QuantReg</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="n">lagdata</span><span class="p">)</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="mf">0.5</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">alpha</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">uqt</span> <span class="o">=</span> <span class="n">QuantReg</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="n">lagdata</span><span class="p">)</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">alpha</span><span class="p">)</span>
|
||||
<span class="n">lqt</span> <span class="o">=</span> <span class="n">QuantReg</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="n">lagdata</span><span class="p">)</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">alpha</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">mean_qt</span> <span class="o">=</span> <span class="p">[</span><span class="n">k</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">mqt</span><span class="o">.</span><span class="n">params</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">alpha</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">upper_qt</span> <span class="o">=</span> <span class="p">[</span><span class="n">k</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">uqt</span><span class="o">.</span><span class="n">params</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">lower_qt</span> <span class="o">=</span> <span class="p">[</span><span class="n">k</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">lqt</span><span class="o">.</span><span class="n">params</span><span class="p">]</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dist</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">dist_qt</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">alpha</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mf">0.05</span><span class="p">,</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">0.05</span><span class="p">):</span>
|
||||
<span class="n">lqt</span> <span class="o">=</span> <span class="n">QuantReg</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="n">lagdata</span><span class="p">)</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">alpha</span><span class="p">)</span>
|
||||
<span class="n">uqt</span> <span class="o">=</span> <span class="n">QuantReg</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="n">lagdata</span><span class="p">)</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">alpha</span><span class="p">)</span>
|
||||
<span class="n">lo_qt</span> <span class="o">=</span> <span class="p">[</span><span class="n">k</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">lqt</span><span class="o">.</span><span class="n">params</span><span class="p">]</span>
|
||||
<span class="n">up_qt</span> <span class="o">=</span> <span class="p">[</span><span class="n">k</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">uqt</span><span class="o">.</span><span class="n">params</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">dist_qt</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="n">lo_qt</span><span class="p">,</span> <span class="n">up_qt</span><span class="p">])</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">"QAR("</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">)</span> <span class="o">+</span> <span class="s2">") - "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">alpha</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="QuantileRegression.linearmodel"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.quantreg.QuantileRegression.linearmodel">[docs]</a> <span class="k">def</span> <span class="nf">linearmodel</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">data</span><span class="p">,</span><span class="n">params</span><span class="p">):</span>
|
||||
<span class="c1">#return params[0] + sum([ data[k] * params[k+1] for k in np.arange(0, self.order) ])</span>
|
||||
<span class="k">return</span> <span class="nb">sum</span><span class="p">([</span><span class="n">data</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">*</span> <span class="n">params</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">)])</span></div>
|
||||
|
||||
<div class="viewcode-block" id="QuantileRegression.point_to_interval"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.quantreg.QuantileRegression.point_to_interval">[docs]</a> <span class="k">def</span> <span class="nf">point_to_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">lo_params</span><span class="p">,</span> <span class="n">up_params</span><span class="p">):</span>
|
||||
<span class="n">lo</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">linearmodel</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">lo_params</span><span class="p">)</span>
|
||||
<span class="n">up</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">linearmodel</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">up_params</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="n">lo</span><span class="p">,</span> <span class="n">up</span><span class="p">]</span></div>
|
||||
|
||||
<div class="viewcode-block" id="QuantileRegression.interval_to_interval"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.quantreg.QuantileRegression.interval_to_interval">[docs]</a> <span class="k">def</span> <span class="nf">interval_to_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">lo_params</span><span class="p">,</span> <span class="n">up_params</span><span class="p">):</span>
|
||||
<span class="n">lo</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">linearmodel</span><span class="p">([</span><span class="n">k</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">data</span><span class="p">],</span> <span class="n">lo_params</span><span class="p">)</span>
|
||||
<span class="n">up</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">linearmodel</span><span class="p">([</span><span class="n">k</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">data</span><span class="p">],</span> <span class="n">up_params</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="n">lo</span><span class="p">,</span> <span class="n">up</span><span class="p">]</span></div>
|
||||
|
||||
<div class="viewcode-block" id="QuantileRegression.forecast"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.quantreg.QuantileRegression.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">l</span><span class="o">+</span><span class="mi">1</span><span class="p">):</span> <span class="c1">#+1 to forecast one step ahead given all available lags</span>
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">ndata</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="p">:</span> <span class="n">k</span><span class="p">]</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">linearmodel</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">mean_qt</span><span class="p">))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="QuantileRegression.forecast_interval"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.quantreg.QuantileRegression.forecast_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">ndata</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">point_to_interval</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">lower_qt</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">upper_qt</span><span class="p">))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="QuantileRegression.forecast_ahead_interval"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.quantreg.QuantileRegression.forecast_ahead_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">smoothing</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"smoothing"</span><span class="p">,</span> <span class="mf">0.9</span><span class="p">)</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">nmeans</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast_ahead</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">):</span>
|
||||
<span class="n">nmeans</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="n">k</span><span class="p">,</span><span class="n">ndata</span><span class="p">[</span><span class="o">-</span><span class="p">(</span><span class="n">k</span><span class="o">+</span><span class="mi">1</span><span class="p">)])</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">steps</span><span class="o">+</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">):</span>
|
||||
<span class="n">intl</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">point_to_interval</span><span class="p">(</span><span class="n">nmeans</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">:</span> <span class="n">k</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">lower_qt</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">upper_qt</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="n">intl</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">*</span><span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="n">k</span><span class="o">*</span><span class="n">smoothing</span><span class="p">),</span> <span class="n">intl</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">*</span><span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="n">k</span><span class="o">*</span><span class="n">smoothing</span><span class="p">)])</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span><span class="p">[</span><span class="o">-</span><span class="n">steps</span><span class="p">:]</span></div>
|
||||
|
||||
<div class="viewcode-block" id="QuantileRegression.forecast_distribution"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.quantreg.QuantileRegression.forecast_distribution">[docs]</a> <span class="k">def</span> <span class="nf">forecast_distribution</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">l</span> <span class="o">+</span> <span class="mi">1</span><span class="p">):</span>
|
||||
<span class="n">dist</span> <span class="o">=</span> <span class="n">ProbabilityDistribution</span><span class="o">.</span><span class="n">ProbabilityDistribution</span><span class="p">(</span><span class="nb">type</span><span class="o">=</span><span class="s2">"histogram"</span><span class="p">,</span>
|
||||
<span class="n">uod</span><span class="o">=</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">original_min</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_max</span><span class="p">])</span>
|
||||
<span class="n">intervals</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">qt</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">dist_qt</span><span class="p">:</span>
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">ndata</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
|
||||
<span class="n">intl</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">point_to_interval</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="n">qt</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">qt</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="n">intervals</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">intl</span><span class="p">)</span>
|
||||
|
||||
<span class="n">dist</span><span class="o">.</span><span class="n">append_interval</span><span class="p">(</span><span class="n">intervals</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">dist</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="QuantileRegression.forecast_ahead_distribution"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.quantreg.QuantileRegression.forecast_ahead_distribution">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead_distribution</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">steps</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">):</span>
|
||||
<span class="n">dist</span> <span class="o">=</span> <span class="n">ProbabilityDistribution</span><span class="o">.</span><span class="n">ProbabilityDistribution</span><span class="p">(</span><span class="nb">type</span><span class="o">=</span><span class="s2">"histogram"</span><span class="p">,</span>
|
||||
<span class="n">uod</span><span class="o">=</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">original_min</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_max</span><span class="p">])</span>
|
||||
<span class="n">intervals</span> <span class="o">=</span> <span class="p">[[</span><span class="n">k</span><span class="p">,</span> <span class="n">k</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">ndata</span><span class="p">[</span><span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">:]]</span>
|
||||
<span class="k">for</span> <span class="n">qt</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">dist_qt</span><span class="p">:</span>
|
||||
<span class="n">intl</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">interval_to_interval</span><span class="p">([</span><span class="n">intervals</span><span class="p">[</span><span class="n">x</span><span class="p">]</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">k</span><span class="p">)],</span> <span class="n">qt</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">qt</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="n">intervals</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">intl</span><span class="p">)</span>
|
||||
<span class="n">dist</span><span class="o">.</span><span class="n">append_interval</span><span class="p">(</span><span class="n">intervals</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">dist</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
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|
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137
docs/_build/html/_modules/pyFTS/common/Composite.html
vendored
Normal file
137
docs/_build/html/_modules/pyFTS/common/Composite.html
vendored
Normal file
@ -0,0 +1,137 @@
|
||||
|
||||
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
|
||||
"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
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||||
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|
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|
||||
<h1>Source code for pyFTS.common.Composite</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">Composite Fuzzy Sets</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="k">import</span> <span class="o">*</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">FuzzySet</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="FuzzySet"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Composite.FuzzySet">[docs]</a><span class="k">class</span> <span class="nc">FuzzySet</span><span class="p">(</span><span class="n">FuzzySet</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Composite Fuzzy Set</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">superset</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Create an empty composite fuzzy set</span>
|
||||
<span class="sd"> :param name: fuzzy set name</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">FuzzySet</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="s1">'composite'</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">superset</span> <span class="o">=</span> <span class="n">superset</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">superset</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">parameters</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="FuzzySet.membership"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Composite.FuzzySet.membership">[docs]</a> <span class="k">def</span> <span class="nf">membership</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Calculate the membership value of a given input</span>
|
||||
|
||||
<span class="sd"> :param x: input value</span>
|
||||
<span class="sd"> :return: membership value of x at this fuzzy set</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">superset</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="nb">max</span><span class="p">([</span><span class="n">s</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="nb">min</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">mf</span><span class="p">[</span><span class="n">ct</span><span class="p">](</span><span class="n">x</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">parameters</span><span class="p">[</span><span class="n">ct</span><span class="p">])</span> <span class="k">for</span> <span class="n">ct</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">mf</span><span class="p">))])</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FuzzySet.append"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Composite.FuzzySet.append">[docs]</a> <span class="k">def</span> <span class="nf">append</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">mf</span><span class="p">,</span> <span class="n">parameters</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Adds a new function to composition</span>
|
||||
|
||||
<span class="sd"> :param mf:</span>
|
||||
<span class="sd"> :param parameters:</span>
|
||||
<span class="sd"> :return:</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">mf</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mf</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">parameters</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">parameters</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FuzzySet.append_set"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Composite.FuzzySet.append_set">[docs]</a> <span class="k">def</span> <span class="nf">append_set</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="nb">set</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Adds a new function to composition</span>
|
||||
|
||||
<span class="sd"> :param mf:</span>
|
||||
<span class="sd"> :param parameters:</span>
|
||||
<span class="sd"> :return:</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">set</span><span class="p">)</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
|
||||
<div class="sphinxsidebarwrapper"><div class="relations">
|
||||
<h3>Related Topics</h3>
|
||||
<ul>
|
||||
<li><a href="../../../index.html">Documentation overview</a><ul>
|
||||
<li><a href="../../index.html">Module code</a><ul>
|
||||
</ul></li>
|
||||
</ul></li>
|
||||
</ul>
|
||||
</div>
|
||||
<div id="searchbox" style="display: none" role="search">
|
||||
<h3>Quick search</h3>
|
||||
<div class="searchformwrapper">
|
||||
<form class="search" action="../../../search.html" method="get">
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<input type="text" name="q" />
|
||||
<input type="submit" value="Go" />
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|
||||
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|
||||
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|
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|
||||
©2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
|
||||
|
||||
|
|
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Powered by <a href="http://sphinx-doc.org/">Sphinx 1.7.2</a>
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|
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|
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|
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|
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</body>
|
||||
</html>
|
||||
196
docs/_build/html/_modules/pyFTS/common/FLR.html
vendored
Normal file
196
docs/_build/html/_modules/pyFTS/common/FLR.html
vendored
Normal file
@ -0,0 +1,196 @@
|
||||
|
||||
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
|
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"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
|
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|
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<html xmlns="http://www.w3.org/1999/xhtml">
|
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<head>
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<meta http-equiv="X-UA-Compatible" content="IE=Edge" />
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<title>pyFTS.common.FLR — pyFTS 1.2.3 documentation</title>
|
||||
<link rel="stylesheet" href="../../../_static/alabaster.css" type="text/css" />
|
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<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
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|
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|
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<script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script>
|
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|
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<link rel="search" title="Search" href="../../../search.html" />
|
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<meta name="viewport" content="width=device-width, initial-scale=0.9, maximum-scale=0.9" />
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|
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|
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<div class="document">
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||||
<div class="bodywrapper">
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|
||||
<h1>Source code for pyFTS.common.FLR</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">This module implements functions for Fuzzy Logical Relationship generation</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="FLR"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FLR.FLR">[docs]</a><span class="k">class</span> <span class="nc">FLR</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Fuzzy Logical Relationship</span>
|
||||
|
||||
<span class="sd"> Represents a temporal transition of the fuzzy set LHS on time t for the fuzzy set RHS on time t+1.</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="n">RHS</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Creates a Fuzzy Logical Relationship</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="n">LHS</span>
|
||||
<span class="sd">"""Left Hand Side fuzzy set"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="n">RHS</span>
|
||||
<span class="sd">"""Right Hand Side fuzzy set"""</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">+</span> <span class="s2">" -> "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="IndexedFLR"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FLR.IndexedFLR">[docs]</a><span class="k">class</span> <span class="nc">IndexedFLR</span><span class="p">(</span><span class="n">FLR</span><span class="p">):</span>
|
||||
<span class="sd">"""Season Indexed Fuzzy Logical Relationship"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">index</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="n">RHS</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Create a Season Indexed Fuzzy Logical Relationship</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">IndexedFLR</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">LHS</span><span class="p">,</span> <span class="n">RHS</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">index</span> <span class="o">=</span> <span class="n">index</span>
|
||||
<span class="sd">"""seasonal index"""</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">index</span><span class="p">)</span> <span class="o">+</span> <span class="s2">": "</span><span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">+</span> <span class="s2">" -> "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="generate_high_order_recurrent_flr"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FLR.generate_high_order_recurrent_flr">[docs]</a><span class="k">def</span> <span class="nf">generate_high_order_recurrent_flr</span><span class="p">(</span><span class="n">fuzzyData</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Create a ordered FLR set from a list of fuzzy sets with recurrence</span>
|
||||
|
||||
<span class="sd"> :param fuzzyData: ordered list of fuzzy sets</span>
|
||||
<span class="sd"> :return: ordered list of FLR</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">flrs</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="nb">len</span><span class="p">(</span><span class="n">fuzzyData</span><span class="p">)):</span>
|
||||
<span class="n">lhs</span> <span class="o">=</span> <span class="n">fuzzyData</span><span class="p">[</span><span class="n">i</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span>
|
||||
<span class="n">rhs</span> <span class="o">=</span> <span class="n">fuzzyData</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">lhs</span><span class="p">,</span> <span class="nb">list</span><span class="p">)</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">rhs</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">l</span> <span class="ow">in</span> <span class="n">lhs</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">r</span> <span class="ow">in</span> <span class="n">rhs</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">FLR</span><span class="p">(</span><span class="n">l</span><span class="p">,</span> <span class="n">r</span><span class="p">)</span>
|
||||
<span class="n">flrs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">FLR</span><span class="p">(</span><span class="n">lhs</span><span class="p">,</span><span class="n">rhs</span><span class="p">)</span>
|
||||
<span class="n">flrs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">flrs</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="generate_recurrent_flrs"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FLR.generate_recurrent_flrs">[docs]</a><span class="k">def</span> <span class="nf">generate_recurrent_flrs</span><span class="p">(</span><span class="n">fuzzyData</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Create a ordered FLR set from a list of fuzzy sets with recurrence</span>
|
||||
|
||||
<span class="sd"> :param fuzzyData: ordered list of fuzzy sets</span>
|
||||
<span class="sd"> :return: ordered list of FLR</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">flrs</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="nb">len</span><span class="p">(</span><span class="n">fuzzyData</span><span class="p">)):</span>
|
||||
<span class="n">lhs</span> <span class="o">=</span> <span class="p">[</span><span class="n">fuzzyData</span><span class="p">[</span><span class="n">i</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]]</span>
|
||||
<span class="n">rhs</span> <span class="o">=</span> <span class="p">[</span><span class="n">fuzzyData</span><span class="p">[</span><span class="n">i</span><span class="p">]]</span>
|
||||
<span class="k">for</span> <span class="n">l</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">lhs</span><span class="p">)</span><span class="o">.</span><span class="n">flatten</span><span class="p">():</span>
|
||||
<span class="k">for</span> <span class="n">r</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">rhs</span><span class="p">)</span><span class="o">.</span><span class="n">flatten</span><span class="p">():</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">FLR</span><span class="p">(</span><span class="n">l</span><span class="p">,</span> <span class="n">r</span><span class="p">)</span>
|
||||
<span class="n">flrs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">flrs</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="generate_non_recurrent_flrs"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FLR.generate_non_recurrent_flrs">[docs]</a><span class="k">def</span> <span class="nf">generate_non_recurrent_flrs</span><span class="p">(</span><span class="n">fuzzyData</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Create a ordered FLR set from a list of fuzzy sets without recurrence</span>
|
||||
|
||||
<span class="sd"> :param fuzzyData: ordered list of fuzzy sets</span>
|
||||
<span class="sd"> :return: ordered list of FLR</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">flrs</span> <span class="o">=</span> <span class="n">generate_recurrent_flrs</span><span class="p">(</span><span class="n">fuzzyData</span><span class="p">)</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="k">for</span> <span class="n">flr</span> <span class="ow">in</span> <span class="n">flrs</span><span class="p">:</span> <span class="n">tmp</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">flr</span><span class="p">)]</span> <span class="o">=</span> <span class="n">flr</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[</span><span class="n">value</span> <span class="k">for</span> <span class="n">key</span><span class="p">,</span> <span class="n">value</span> <span class="ow">in</span> <span class="n">tmp</span><span class="o">.</span><span class="n">items</span><span class="p">()]</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="generate_indexed_flrs"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FLR.generate_indexed_flrs">[docs]</a><span class="k">def</span> <span class="nf">generate_indexed_flrs</span><span class="p">(</span><span class="n">sets</span><span class="p">,</span> <span class="n">indexer</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">transformation</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">alpha_cut</span><span class="o">=</span><span class="mf">0.0</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Create a season-indexed ordered FLR set from a list of fuzzy sets with recurrence</span>
|
||||
|
||||
<span class="sd"> :param sets: fuzzy sets</span>
|
||||
<span class="sd"> :param indexer: seasonality indexer </span>
|
||||
<span class="sd"> :param data: original data</span>
|
||||
<span class="sd"> :return: ordered list of FLR </span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">flrs</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">index</span> <span class="o">=</span> <span class="n">indexer</span><span class="o">.</span><span class="n">get_season_of_data</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">indexer</span><span class="o">.</span><span class="n">get_data</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">transformation</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">transformation</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span><span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)):</span>
|
||||
<span class="n">lhs</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">fuzzyfy_series</span><span class="p">([</span><span class="n">ndata</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]],</span> <span class="n">sets</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s1">'fuzzy'</span><span class="p">,</span><span class="n">alpha_cut</span><span class="o">=</span><span class="n">alpha_cut</span><span class="p">)</span>
|
||||
<span class="n">rhs</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">fuzzyfy_series</span><span class="p">([</span><span class="n">ndata</span><span class="p">[</span><span class="n">k</span><span class="p">]],</span> <span class="n">sets</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s1">'fuzzy'</span><span class="p">,</span><span class="n">alpha_cut</span><span class="o">=</span><span class="n">alpha_cut</span><span class="p">)</span>
|
||||
<span class="n">season</span> <span class="o">=</span> <span class="n">index</span><span class="p">[</span><span class="n">k</span><span class="p">]</span>
|
||||
<span class="k">for</span> <span class="n">_l</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">lhs</span><span class="p">)</span><span class="o">.</span><span class="n">flatten</span><span class="p">():</span>
|
||||
<span class="k">for</span> <span class="n">_r</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">rhs</span><span class="p">)</span><span class="o">.</span><span class="n">flatten</span><span class="p">():</span>
|
||||
<span class="n">flr</span> <span class="o">=</span> <span class="n">IndexedFLR</span><span class="p">(</span><span class="n">season</span><span class="p">,</span><span class="n">_l</span><span class="p">,</span><span class="n">_r</span><span class="p">)</span>
|
||||
<span class="n">flrs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">flr</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">flrs</span></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
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|
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274
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<h1>Source code for pyFTS.common.FuzzySet</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="k">import</span> <span class="o">*</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Membership</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="FuzzySet"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.FuzzySet">[docs]</a><span class="k">class</span> <span class="nc">FuzzySet</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Fuzzy Set</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">mf</span><span class="p">,</span> <span class="n">parameters</span><span class="p">,</span> <span class="n">centroid</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Create a Fuzzy Set</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">name</span>
|
||||
<span class="sd">"""The fuzzy set name"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">=</span> <span class="n">mf</span>
|
||||
<span class="sd">"""The membership function"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">parameters</span> <span class="o">=</span> <span class="n">parameters</span>
|
||||
<span class="sd">"""The parameters of the membership function"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">centroid</span> <span class="o">=</span> <span class="n">centroid</span>
|
||||
<span class="sd">"""The fuzzy set center of mass (or midpoint)"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">alpha</span> <span class="o">=</span> <span class="n">alpha</span>
|
||||
<span class="sd">"""The alpha cut value"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'type'</span><span class="p">,</span> <span class="s1">'common'</span><span class="p">)</span>
|
||||
<span class="sd">"""The fuzzy set type (common, composite, nonstationary, etc)"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">variable</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'variable'</span><span class="p">,</span><span class="kc">None</span><span class="p">)</span>
|
||||
<span class="sd">"""In multivariate time series, indicate for which variable this fuzzy set belogs"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">Z</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="sd">"""Partition function in respect to the membership function"""</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">lower</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">parameters</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">upper</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">parameters</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">gaussmf</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">lower</span> <span class="o">=</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">-</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">*</span><span class="mi">3</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">upper</span> <span class="o">=</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">*</span><span class="mi">3</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">metadata</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<div class="viewcode-block" id="FuzzySet.membership"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.FuzzySet.membership">[docs]</a> <span class="k">def</span> <span class="nf">membership</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Calculate the membership value of a given input</span>
|
||||
|
||||
<span class="sd"> :param x: input value </span>
|
||||
<span class="sd"> :return: membership value of x at this fuzzy set</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">parameters</span><span class="p">)</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">alpha</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FuzzySet.partition_function"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.FuzzySet.partition_function">[docs]</a> <span class="k">def</span> <span class="nf">partition_function</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">uod</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">nbins</span><span class="o">=</span><span class="mi">100</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Calculate the partition function over the membership function.</span>
|
||||
|
||||
<span class="sd"> :param uod:</span>
|
||||
<span class="sd"> :param nbins:</span>
|
||||
<span class="sd"> :return:</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">Z</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">uod</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">Z</span> <span class="o">=</span> <span class="mf">0.0</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="n">uod</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">uod</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">nbins</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">Z</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">Z</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">+</span> <span class="s2">": "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">mf</span><span class="o">.</span><span class="vm">__name__</span><span class="p">)</span> <span class="o">+</span> <span class="s2">"("</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">parameters</span><span class="p">)</span> <span class="o">+</span> <span class="s2">")"</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="set_ordered"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.set_ordered">[docs]</a><span class="k">def</span> <span class="nf">set_ordered</span><span class="p">(</span><span class="n">fuzzySets</span><span class="p">):</span>
|
||||
<span class="sd">"""Order a fuzzy set list by their centroids"""</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">fuzzySets</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">tmp1</span> <span class="o">=</span> <span class="p">[</span><span class="n">fuzzySets</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">fuzzySets</span><span class="o">.</span><span class="n">keys</span><span class="p">()]</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="n">k</span><span class="o">.</span><span class="n">name</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">tmp1</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="o">.</span><span class="n">centroid</span><span class="p">)]</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="fuzzyfy_instance"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.fuzzyfy_instance">[docs]</a><span class="k">def</span> <span class="nf">fuzzyfy_instance</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="n">fuzzySets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Calculate the membership values for a data point given fuzzy sets</span>
|
||||
|
||||
<span class="sd"> :param inst: data point</span>
|
||||
<span class="sd"> :param fuzzySets: dict of fuzzy sets</span>
|
||||
<span class="sd"> :return: array of membership values</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">ordered_sets</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">ordered_sets</span> <span class="o">=</span> <span class="n">set_ordered</span><span class="p">(</span><span class="n">fuzzySets</span><span class="p">)</span>
|
||||
|
||||
<span class="n">mv</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">ordered_sets</span><span class="p">:</span>
|
||||
<span class="n">mv</span><span class="o">.</span><span class="n">append</span><span class="p">(</span> <span class="n">fuzzySets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">inst</span><span class="p">))</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">mv</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="fuzzyfy_instances"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.fuzzyfy_instances">[docs]</a><span class="k">def</span> <span class="nf">fuzzyfy_instances</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">fuzzySets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Calculate the membership values for a data point given fuzzy sets</span>
|
||||
|
||||
<span class="sd"> :param inst: data point</span>
|
||||
<span class="sd"> :param fuzzySets: dict of fuzzy sets</span>
|
||||
<span class="sd"> :return: array of membership values</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">if</span> <span class="n">ordered_sets</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">ordered_sets</span> <span class="o">=</span> <span class="n">set_ordered</span><span class="p">(</span><span class="n">fuzzySets</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">inst</span> <span class="ow">in</span> <span class="n">data</span><span class="p">:</span>
|
||||
<span class="n">mv</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">fuzzySets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">inst</span><span class="p">)</span> <span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">ordered_sets</span><span class="p">])</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mv</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_fuzzysets"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.get_fuzzysets">[docs]</a><span class="k">def</span> <span class="nf">get_fuzzysets</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="n">fuzzySets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">alpha_cut</span><span class="o">=</span><span class="mf">0.0</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Return the fuzzy sets which membership value for a inst is greater than the alpha_cut</span>
|
||||
|
||||
<span class="sd"> :param inst: data point</span>
|
||||
<span class="sd"> :param fuzzySets: dict of fuzzy sets</span>
|
||||
<span class="sd"> :param alpha_cut: Minimal membership to be considered on fuzzyfication process</span>
|
||||
<span class="sd"> :return: array of membership values</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">ordered_sets</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">ordered_sets</span> <span class="o">=</span> <span class="n">set_ordered</span><span class="p">(</span><span class="n">fuzzySets</span><span class="p">)</span>
|
||||
|
||||
<span class="n">fs</span> <span class="o">=</span> <span class="p">[</span><span class="n">key</span> <span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">ordered_sets</span> <span class="k">if</span> <span class="n">fuzzySets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">inst</span><span class="p">)</span> <span class="o">></span> <span class="n">alpha_cut</span><span class="p">]</span>
|
||||
<span class="k">return</span> <span class="n">fs</span></div>
|
||||
|
||||
<div class="viewcode-block" id="get_maximum_membership_fuzzyset"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.get_maximum_membership_fuzzyset">[docs]</a><span class="k">def</span> <span class="nf">get_maximum_membership_fuzzyset</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="n">fuzzySets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Fuzzify a data point, returning the fuzzy set with maximum membership value</span>
|
||||
|
||||
<span class="sd"> :param inst: data point</span>
|
||||
<span class="sd"> :param fuzzySets: dict of fuzzy sets</span>
|
||||
<span class="sd"> :return: fuzzy set with maximum membership</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">if</span> <span class="n">ordered_sets</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">ordered_sets</span> <span class="o">=</span> <span class="n">set_ordered</span><span class="p">(</span><span class="n">fuzzySets</span><span class="p">)</span>
|
||||
<span class="n">mv</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">fuzzySets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">inst</span><span class="p">)</span> <span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">ordered_sets</span><span class="p">])</span>
|
||||
<span class="n">key</span> <span class="o">=</span> <span class="n">ordered_sets</span><span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">mv</span> <span class="o">==</span> <span class="nb">max</span><span class="p">(</span><span class="n">mv</span><span class="p">))[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">]]</span>
|
||||
<span class="k">return</span> <span class="n">fuzzySets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_maximum_membership_fuzzyset_index"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.get_maximum_membership_fuzzyset_index">[docs]</a><span class="k">def</span> <span class="nf">get_maximum_membership_fuzzyset_index</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="n">fuzzySets</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Fuzzify a data point, returning the fuzzy set with maximum membership value</span>
|
||||
|
||||
<span class="sd"> :param inst: data point</span>
|
||||
<span class="sd"> :param fuzzySets: dict of fuzzy sets</span>
|
||||
<span class="sd"> :return: fuzzy set with maximum membership</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">mv</span> <span class="o">=</span> <span class="n">fuzzyfy_instance</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="n">fuzzySets</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">mv</span> <span class="o">==</span> <span class="nb">max</span><span class="p">(</span><span class="n">mv</span><span class="p">))[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">]</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="fuzzyfy_series_old"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.fuzzyfy_series_old">[docs]</a><span class="k">def</span> <span class="nf">fuzzyfy_series_old</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">fuzzySets</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s1">'maximum'</span><span class="p">):</span>
|
||||
<span class="n">fts</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">data</span><span class="p">:</span>
|
||||
<span class="n">fts</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">get_maximum_membership_fuzzyset</span><span class="p">(</span><span class="n">item</span><span class="p">,</span> <span class="n">fuzzySets</span><span class="p">)</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">fts</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="fuzzyfy_series"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.fuzzyfy_series">[docs]</a><span class="k">def</span> <span class="nf">fuzzyfy_series</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">fuzzySets</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s1">'maximum'</span><span class="p">,</span> <span class="n">alpha_cut</span><span class="o">=</span><span class="mf">0.0</span><span class="p">):</span>
|
||||
<span class="n">fts</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">ordered_sets</span> <span class="o">=</span> <span class="n">set_ordered</span><span class="p">(</span><span class="n">fuzzySets</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">t</span><span class="p">,</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">data</span><span class="p">):</span>
|
||||
<span class="n">mv</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">fuzzySets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">i</span><span class="p">)</span> <span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">ordered_sets</span><span class="p">])</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">mv</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">sets</span> <span class="o">=</span> <span class="n">check_bounds</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">fuzzySets</span><span class="o">.</span><span class="n">items</span><span class="p">(),</span> <span class="n">ordered_sets</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">method</span> <span class="o">==</span> <span class="s1">'fuzzy'</span><span class="p">:</span>
|
||||
<span class="n">ix</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">mv</span> <span class="o">></span> <span class="n">alpha_cut</span><span class="p">))</span>
|
||||
<span class="n">sets</span> <span class="o">=</span> <span class="p">[</span><span class="n">fuzzySets</span><span class="p">[</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">i</span><span class="p">]]</span><span class="o">.</span><span class="n">name</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">ix</span><span class="p">]</span>
|
||||
<span class="k">elif</span> <span class="n">method</span> <span class="o">==</span> <span class="s1">'maximum'</span><span class="p">:</span>
|
||||
<span class="n">mx</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">mv</span><span class="p">)</span>
|
||||
<span class="n">ix</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">mv</span> <span class="o">==</span> <span class="n">mx</span><span class="p">))</span>
|
||||
<span class="n">sets</span> <span class="o">=</span> <span class="n">fuzzySets</span><span class="p">[</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">ix</span><span class="p">[</span><span class="mi">0</span><span class="p">]]]</span><span class="o">.</span><span class="n">name</span>
|
||||
<span class="n">fts</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">sets</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">fts</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="grant_bounds"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.grant_bounds">[docs]</a><span class="k">def</span> <span class="nf">grant_bounds</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">sets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">data</span> <span class="o"><</span> <span class="n">sets</span><span class="p">[</span><span class="n">ordered_sets</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">.</span><span class="n">lower</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">sets</span><span class="p">[</span><span class="n">ordered_sets</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">.</span><span class="n">lower</span>
|
||||
<span class="k">elif</span> <span class="n">data</span> <span class="o">></span> <span class="n">sets</span><span class="p">[</span><span class="n">ordered_sets</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]]</span><span class="o">.</span><span class="n">upper</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">sets</span><span class="p">[</span><span class="n">ordered_sets</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]]</span><span class="o">.</span><span class="n">upper</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">data</span></div>
|
||||
|
||||
<div class="viewcode-block" id="check_bounds"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.check_bounds">[docs]</a><span class="k">def</span> <span class="nf">check_bounds</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">sets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">data</span> <span class="o"><</span> <span class="n">sets</span><span class="p">[</span><span class="n">ordered_sets</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">.</span><span class="n">lower</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">sets</span><span class="p">[</span><span class="n">ordered_sets</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span>
|
||||
<span class="k">elif</span> <span class="n">data</span> <span class="o">></span> <span class="n">sets</span><span class="p">[</span><span class="n">ordered_sets</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]]</span><span class="o">.</span><span class="n">upper</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">sets</span><span class="p">[</span><span class="n">ordered_sets</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]]</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="check_bounds_index"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.check_bounds_index">[docs]</a><span class="k">def</span> <span class="nf">check_bounds_index</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">sets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">data</span> <span class="o"><</span> <span class="n">sets</span><span class="p">[</span><span class="n">ordered_sets</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">.</span><span class="n">get_lower</span><span class="p">():</span>
|
||||
<span class="k">return</span> <span class="mi">0</span>
|
||||
<span class="k">elif</span> <span class="n">data</span> <span class="o">></span> <span class="n">sets</span><span class="p">[</span><span class="n">ordered_sets</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]]</span><span class="o">.</span><span class="n">get_upper</span><span class="p">():</span>
|
||||
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="n">sets</span><span class="p">)</span> <span class="o">-</span><span class="mi">1</span></div>
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
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|
||||
</div>
|
||||
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
|
||||
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|
||||
<h3>Related Topics</h3>
|
||||
<ul>
|
||||
<li><a href="../../../index.html">Documentation overview</a><ul>
|
||||
<li><a href="../../index.html">Module code</a><ul>
|
||||
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|
||||
</ul></li>
|
||||
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|
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|
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<div id="searchbox" style="display: none" role="search">
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<h3>Quick search</h3>
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<div class="searchformwrapper">
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<form class="search" action="../../../search.html" method="get">
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<input type="text" name="q" />
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<input type="submit" value="Go" />
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<input type="hidden" name="check_keywords" value="yes" />
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<div class="footer">
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©2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
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Powered by <a href="http://sphinx-doc.org/">Sphinx 1.7.2</a>
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157
docs/_build/html/_modules/pyFTS/common/Membership.html
vendored
Normal file
157
docs/_build/html/_modules/pyFTS/common/Membership.html
vendored
Normal file
@ -0,0 +1,157 @@
|
||||
|
||||
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
|
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"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
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<meta http-equiv="X-UA-Compatible" content="IE=Edge" />
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<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
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<title>pyFTS.common.Membership — pyFTS 1.2.3 documentation</title>
|
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<link rel="stylesheet" href="../../../_static/alabaster.css" type="text/css" />
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<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
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<div class="bodywrapper">
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<div class="body" role="main">
|
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|
||||
<h1>Source code for pyFTS.common.Membership</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">Membership functions for Fuzzy Sets</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">math</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="k">import</span> <span class="o">*</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="trimf"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Membership.trimf">[docs]</a><span class="k">def</span> <span class="nf">trimf</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">parameters</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Triangular fuzzy membership function</span>
|
||||
|
||||
<span class="sd"> :param x: data point</span>
|
||||
<span class="sd"> :param parameters: a list with 3 real values</span>
|
||||
<span class="sd"> :return: the membership value of x given the parameters</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">xx</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="mi">3</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">xx</span> <span class="o"><</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">0</span><span class="p">]:</span>
|
||||
<span class="k">return</span> <span class="mi">0</span>
|
||||
<span class="k">elif</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o"><=</span> <span class="n">xx</span> <span class="o"><</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">1</span><span class="p">]:</span>
|
||||
<span class="k">return</span> <span class="p">(</span><span class="n">x</span> <span class="o">-</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="o">/</span> <span class="p">(</span><span class="n">parameters</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
|
||||
<span class="k">elif</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o"><=</span> <span class="n">xx</span> <span class="o"><=</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">2</span><span class="p">]:</span>
|
||||
<span class="k">return</span> <span class="p">(</span><span class="n">parameters</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="o">-</span> <span class="n">xx</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="n">parameters</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="o">-</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="mi">0</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="trapmf"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Membership.trapmf">[docs]</a><span class="k">def</span> <span class="nf">trapmf</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">parameters</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Trapezoidal fuzzy membership function</span>
|
||||
|
||||
<span class="sd"> :param x: data point</span>
|
||||
<span class="sd"> :param parameters: a list with 4 real values</span>
|
||||
<span class="sd"> :return: the membership value of x given the parameters</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">if</span> <span class="n">x</span> <span class="o"><</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">0</span><span class="p">]:</span>
|
||||
<span class="k">return</span> <span class="mi">0</span>
|
||||
<span class="k">elif</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o"><=</span> <span class="n">x</span> <span class="o"><</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">1</span><span class="p">]:</span>
|
||||
<span class="k">return</span> <span class="p">(</span><span class="n">x</span> <span class="o">-</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="o">/</span> <span class="p">(</span><span class="n">parameters</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
|
||||
<span class="k">elif</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o"><=</span> <span class="n">x</span> <span class="o"><=</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">2</span><span class="p">]:</span>
|
||||
<span class="k">return</span> <span class="mi">1</span>
|
||||
<span class="k">elif</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="o"><=</span> <span class="n">x</span> <span class="o"><=</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">3</span><span class="p">]:</span>
|
||||
<span class="k">return</span> <span class="p">(</span><span class="n">parameters</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span> <span class="o">-</span> <span class="n">x</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="n">parameters</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span> <span class="o">-</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">2</span><span class="p">])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="mi">0</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="gaussmf"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Membership.gaussmf">[docs]</a><span class="k">def</span> <span class="nf">gaussmf</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">parameters</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Gaussian fuzzy membership function</span>
|
||||
|
||||
<span class="sd"> :param x: data point</span>
|
||||
<span class="sd"> :param parameters: a list with 2 real values (mean and variance)</span>
|
||||
<span class="sd"> :return: the membership value of x given the parameters</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="n">math</span><span class="o">.</span><span class="n">exp</span><span class="p">((</span><span class="o">-</span><span class="p">(</span><span class="n">x</span> <span class="o">-</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span><span class="o">**</span><span class="mi">2</span><span class="p">)</span><span class="o">/</span><span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span><span class="o">**</span><span class="mi">2</span><span class="p">))</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="bellmf"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Membership.bellmf">[docs]</a><span class="k">def</span> <span class="nf">bellmf</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">parameters</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Bell shaped membership function</span>
|
||||
|
||||
<span class="sd"> :param x:</span>
|
||||
<span class="sd"> :param parameters:</span>
|
||||
<span class="sd"> :return:</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="mi">1</span> <span class="o">/</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="nb">abs</span><span class="p">((</span><span class="n">x</span> <span class="o">-</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">2</span><span class="p">])</span> <span class="o">/</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="o">**</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">1</span><span class="p">]))</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="sigmf"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Membership.sigmf">[docs]</a><span class="k">def</span> <span class="nf">sigmf</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">parameters</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Sigmoid / Logistic membership function</span>
|
||||
|
||||
<span class="sd"> :param x:</span>
|
||||
<span class="sd"> :param parameters: an list with 2 real values (smoothness and midpoint)</span>
|
||||
<span class="sd"> :return:</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="mi">1</span> <span class="o">/</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="n">math</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="o">-</span><span class="n">parameters</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="n">x</span> <span class="o">-</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">1</span><span class="p">])))</span></div>
|
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<h1>Source code for pyFTS.common.SortedCollection</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">from</span> <span class="nn">bisect</span> <span class="k">import</span> <span class="n">bisect_left</span><span class="p">,</span> <span class="n">bisect_right</span>
|
||||
|
||||
<span class="c1">#</span>
|
||||
<span class="c1"># Original Source Code: https://code.activestate.com/recipes/577197-sortedcollection/</span>
|
||||
<span class="c1"># Author: RAYMOND HETTINGER</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="SortedCollection"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.SortedCollection.SortedCollection">[docs]</a><span class="k">class</span> <span class="nc">SortedCollection</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
|
||||
<span class="sd">'''Sequence sorted by a key function.</span>
|
||||
|
||||
<span class="sd"> SortedCollection() is much easier to work with than using bisect() directly.</span>
|
||||
<span class="sd"> It supports key functions like those use in sorted(), min(), and max().</span>
|
||||
<span class="sd"> The result of the key function call is saved so that keys can be searched</span>
|
||||
<span class="sd"> efficiently.</span>
|
||||
|
||||
<span class="sd"> Instead of returning an insertion-point which can be hard to interpret, the</span>
|
||||
<span class="sd"> five find-methods return a specific item in the sequence. They can scan for</span>
|
||||
<span class="sd"> exact matches, the last item less-than-or-equal to a key, or the first item</span>
|
||||
<span class="sd"> greater-than-or-equal to a key.</span>
|
||||
|
||||
<span class="sd"> Once found, an item's ordinal position can be located with the index() method.</span>
|
||||
<span class="sd"> New items can be added with the insert() and insert_right() methods.</span>
|
||||
<span class="sd"> Old items can be deleted with the remove() method.</span>
|
||||
|
||||
<span class="sd"> The usual sequence methods are provided to support indexing, slicing,</span>
|
||||
<span class="sd"> length lookup, clearing, copying, forward and reverse iteration, contains</span>
|
||||
<span class="sd"> checking, item counts, item removal, and a nice looking repr.</span>
|
||||
|
||||
<span class="sd"> Finding and indexing are O(log n) operations while iteration and insertion</span>
|
||||
<span class="sd"> are O(n). The initial sort is O(n log n).</span>
|
||||
|
||||
<span class="sd"> The key function is stored in the 'key' attibute for easy introspection or</span>
|
||||
<span class="sd"> so that you can assign a new key function (triggering an automatic re-sort).</span>
|
||||
|
||||
<span class="sd"> In short, the class was designed to handle all of the common use cases for</span>
|
||||
<span class="sd"> bisect but with a simpler API and support for key functions.</span>
|
||||
|
||||
<span class="sd"> >>> from pprint import pprint</span>
|
||||
<span class="sd"> >>> from operator import itemgetter</span>
|
||||
|
||||
<span class="sd"> >>> s = SortedCollection(key=itemgetter(2))</span>
|
||||
<span class="sd"> >>> for record in [</span>
|
||||
<span class="sd"> ... ('roger', 'young', 30),</span>
|
||||
<span class="sd"> ... ('angela', 'jones', 28),</span>
|
||||
<span class="sd"> ... ('bill', 'smith', 22),</span>
|
||||
<span class="sd"> ... ('david', 'thomas', 32)]:</span>
|
||||
<span class="sd"> ... s.insert(record)</span>
|
||||
|
||||
<span class="sd"> >>> pprint(list(s)) # show records sorted by age</span>
|
||||
<span class="sd"> [('bill', 'smith', 22),</span>
|
||||
<span class="sd"> ('angela', 'jones', 28),</span>
|
||||
<span class="sd"> ('roger', 'young', 30),</span>
|
||||
<span class="sd"> ('david', 'thomas', 32)]</span>
|
||||
|
||||
<span class="sd"> >>> s.find_le(29) # find oldest person aged 29 or younger</span>
|
||||
<span class="sd"> ('angela', 'jones', 28)</span>
|
||||
<span class="sd"> >>> s.find_lt(28) # find oldest person under 28</span>
|
||||
<span class="sd"> ('bill', 'smith', 22)</span>
|
||||
<span class="sd"> >>> s.find_gt(28) # find youngest person over 28</span>
|
||||
<span class="sd"> ('roger', 'young', 30)</span>
|
||||
|
||||
<span class="sd"> >>> r = s.find_ge(32) # find youngest person aged 32 or older</span>
|
||||
<span class="sd"> >>> s.index(r) # get the index of their record</span>
|
||||
<span class="sd"> 3</span>
|
||||
<span class="sd"> >>> s[3] # fetch the record at that index</span>
|
||||
<span class="sd"> ('david', 'thomas', 32)</span>
|
||||
|
||||
<span class="sd"> >>> s.key = itemgetter(0) # now sort by first name</span>
|
||||
<span class="sd"> >>> pprint(list(s))</span>
|
||||
<span class="sd"> [('angela', 'jones', 28),</span>
|
||||
<span class="sd"> ('bill', 'smith', 22),</span>
|
||||
<span class="sd"> ('david', 'thomas', 32),</span>
|
||||
<span class="sd"> ('roger', 'young', 30)]</span>
|
||||
|
||||
<span class="sd"> '''</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">iterable</span><span class="o">=</span><span class="p">(),</span> <span class="n">key</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_given_key</span> <span class="o">=</span> <span class="n">key</span>
|
||||
<span class="n">key</span> <span class="o">=</span> <span class="p">(</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">)</span> <span class="k">if</span> <span class="n">key</span> <span class="ow">is</span> <span class="kc">None</span> <span class="k">else</span> <span class="n">key</span>
|
||||
<span class="n">decorated</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">((</span><span class="n">key</span><span class="p">(</span><span class="n">item</span><span class="p">),</span> <span class="n">item</span><span class="p">)</span> <span class="k">for</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">iterable</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_keys</span> <span class="o">=</span> <span class="p">[</span><span class="n">k</span> <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">decorated</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_items</span> <span class="o">=</span> <span class="p">[</span><span class="n">item</span> <span class="k">for</span> <span class="n">k</span><span class="p">,</span> <span class="n">item</span> <span class="ow">in</span> <span class="n">decorated</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_key</span> <span class="o">=</span> <span class="n">key</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">_getkey</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_key</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">_setkey</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">key</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">key</span> <span class="ow">is</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">_key</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="n">key</span><span class="p">)</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">_delkey</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_setkey</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="n">key</span> <span class="o">=</span> <span class="nb">property</span><span class="p">(</span><span class="n">_getkey</span><span class="p">,</span> <span class="n">_setkey</span><span class="p">,</span> <span class="n">_delkey</span><span class="p">,</span> <span class="s1">'key function'</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="SortedCollection.clear"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.SortedCollection.SortedCollection.clear">[docs]</a> <span class="k">def</span> <span class="nf">clear</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="fm">__init__</span><span class="p">([],</span> <span class="bp">self</span><span class="o">.</span><span class="n">_key</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SortedCollection.copy"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.SortedCollection.SortedCollection.copy">[docs]</a> <span class="k">def</span> <span class="nf">copy</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_key</span><span class="p">)</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">)</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__getitem__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">i</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__iter__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">iter</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">)</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__reversed__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">reversed</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">)</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__repr__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="s1">'</span><span class="si">%s</span><span class="s1">(</span><span class="si">%r</span><span class="s1">, key=</span><span class="si">%s</span><span class="s1">)'</span> <span class="o">%</span> <span class="p">(</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span><span class="p">,</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">,</span>
|
||||
<span class="nb">getattr</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_given_key</span><span class="p">,</span> <span class="s1">'__name__'</span><span class="p">,</span> <span class="nb">repr</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_given_key</span><span class="p">))</span>
|
||||
<span class="p">)</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__reduce__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="p">,</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_given_key</span><span class="p">)</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__contains__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">item</span><span class="p">):</span>
|
||||
<span class="n">k</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_key</span><span class="p">(</span><span class="n">item</span><span class="p">)</span>
|
||||
<span class="n">i</span> <span class="o">=</span> <span class="n">bisect_left</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
|
||||
<span class="n">j</span> <span class="o">=</span> <span class="n">bisect_right</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">item</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">[</span><span class="n">i</span><span class="p">:</span><span class="n">j</span><span class="p">]</span>
|
||||
|
||||
<div class="viewcode-block" id="SortedCollection.index"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.SortedCollection.SortedCollection.index">[docs]</a> <span class="k">def</span> <span class="nf">index</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">item</span><span class="p">):</span>
|
||||
<span class="s1">'Find the position of an item. Raise ValueError if not found.'</span>
|
||||
<span class="n">k</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_key</span><span class="p">(</span><span class="n">item</span><span class="p">)</span>
|
||||
<span class="n">i</span> <span class="o">=</span> <span class="n">bisect_left</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
|
||||
<span class="n">j</span> <span class="o">=</span> <span class="n">bisect_right</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">[</span><span class="n">i</span><span class="p">:</span><span class="n">j</span><span class="p">]</span><span class="o">.</span><span class="n">index</span><span class="p">(</span><span class="n">item</span><span class="p">)</span> <span class="o">+</span> <span class="n">i</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SortedCollection.count"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.SortedCollection.SortedCollection.count">[docs]</a> <span class="k">def</span> <span class="nf">count</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">item</span><span class="p">):</span>
|
||||
<span class="s1">'Return number of occurrences of item'</span>
|
||||
<span class="n">k</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_key</span><span class="p">(</span><span class="n">item</span><span class="p">)</span>
|
||||
<span class="n">i</span> <span class="o">=</span> <span class="n">bisect_left</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
|
||||
<span class="n">j</span> <span class="o">=</span> <span class="n">bisect_right</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">[</span><span class="n">i</span><span class="p">:</span><span class="n">j</span><span class="p">]</span><span class="o">.</span><span class="n">count</span><span class="p">(</span><span class="n">item</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SortedCollection.insert"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.SortedCollection.SortedCollection.insert">[docs]</a> <span class="k">def</span> <span class="nf">insert</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">item</span><span class="p">):</span>
|
||||
<span class="s1">'Insert a new item. If equal keys are found, add to the left'</span>
|
||||
<span class="n">k</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_key</span><span class="p">(</span><span class="n">item</span><span class="p">)</span>
|
||||
<span class="n">i</span> <span class="o">=</span> <span class="n">bisect_left</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">item</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SortedCollection.insert_right"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.SortedCollection.SortedCollection.insert_right">[docs]</a> <span class="k">def</span> <span class="nf">insert_right</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">item</span><span class="p">):</span>
|
||||
<span class="s1">'Insert a new item. If equal keys are found, add to the right'</span>
|
||||
<span class="n">k</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_key</span><span class="p">(</span><span class="n">item</span><span class="p">)</span>
|
||||
<span class="n">i</span> <span class="o">=</span> <span class="n">bisect_right</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">item</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SortedCollection.remove"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.SortedCollection.SortedCollection.remove">[docs]</a> <span class="k">def</span> <span class="nf">remove</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">item</span><span class="p">):</span>
|
||||
<span class="s1">'Remove first occurence of item. Raise ValueError if not found'</span>
|
||||
<span class="n">i</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">index</span><span class="p">(</span><span class="n">item</span><span class="p">)</span>
|
||||
<span class="k">del</span> <span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
|
||||
<span class="k">del</span> <span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">[</span><span class="n">i</span><span class="p">]</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SortedCollection.find"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.SortedCollection.SortedCollection.find">[docs]</a> <span class="k">def</span> <span class="nf">find</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span>
|
||||
<span class="s1">'Return first item with a key == k. Raise ValueError if not found.'</span>
|
||||
<span class="n">i</span> <span class="o">=</span> <span class="n">bisect_left</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">i</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">==</span> <span class="n">k</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
|
||||
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s1">'No item found with key equal to: </span><span class="si">%r</span><span class="s1">'</span> <span class="o">%</span> <span class="p">(</span><span class="n">k</span><span class="p">,))</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SortedCollection.find_le"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.SortedCollection.SortedCollection.find_le">[docs]</a> <span class="k">def</span> <span class="nf">find_le</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span>
|
||||
<span class="s1">'Return last item with a key <= k. Raise ValueError if not found.'</span>
|
||||
<span class="n">i</span> <span class="o">=</span> <span class="n">bisect_right</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">i</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">[</span><span class="n">i</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
|
||||
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s1">'No item found with key at or below: </span><span class="si">%r</span><span class="s1">'</span> <span class="o">%</span> <span class="p">(</span><span class="n">k</span><span class="p">,))</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SortedCollection.find_lt"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.SortedCollection.SortedCollection.find_lt">[docs]</a> <span class="k">def</span> <span class="nf">find_lt</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span>
|
||||
<span class="s1">'Return last item with a key < k. Raise ValueError if not found.'</span>
|
||||
<span class="n">i</span> <span class="o">=</span> <span class="n">bisect_left</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">i</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">[</span><span class="n">i</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
|
||||
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s1">'No item found with key below: </span><span class="si">%r</span><span class="s1">'</span> <span class="o">%</span> <span class="p">(</span><span class="n">k</span><span class="p">,))</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SortedCollection.find_ge"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.SortedCollection.SortedCollection.find_ge">[docs]</a> <span class="k">def</span> <span class="nf">find_ge</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span>
|
||||
<span class="s1">'Return first item with a key >= equal to k. Raise ValueError if not found'</span>
|
||||
<span class="n">i</span> <span class="o">=</span> <span class="n">bisect_left</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">i</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
|
||||
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s1">'No item found with key at or above: </span><span class="si">%r</span><span class="s1">'</span> <span class="o">%</span> <span class="p">(</span><span class="n">k</span><span class="p">,))</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SortedCollection.find_gt"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.SortedCollection.SortedCollection.find_gt">[docs]</a> <span class="k">def</span> <span class="nf">find_gt</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span>
|
||||
<span class="s1">'Return first item with a key > k. Raise ValueError if not found'</span>
|
||||
<span class="n">i</span> <span class="o">=</span> <span class="n">bisect_right</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">i</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">[</span><span class="n">i</span><span class="p">]</span>
|
||||
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s1">'No item found with key above: </span><span class="si">%r</span><span class="s1">'</span> <span class="o">%</span> <span class="p">(</span><span class="n">k</span><span class="p">,))</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SortedCollection.between"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.SortedCollection.SortedCollection.between">[docs]</a> <span class="k">def</span> <span class="nf">between</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ge</span><span class="p">,</span> <span class="n">le</span><span class="p">):</span>
|
||||
<span class="n">g</span> <span class="o">=</span> <span class="n">bisect_left</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">ge</span><span class="p">)</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="n">bisect_right</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">le</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">g</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="ow">and</span> <span class="n">l</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">[</span><span class="n">g</span> <span class="p">:</span> <span class="n">l</span><span class="p">]</span>
|
||||
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s1">'No item found between keys : </span><span class="si">%r</span><span class="s1">,</span><span class="si">%r</span><span class="s1">'</span> <span class="o">%</span> <span class="p">(</span><span class="n">ge</span><span class="p">,</span><span class="n">le</span><span class="p">))</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SortedCollection.inside"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.SortedCollection.SortedCollection.inside">[docs]</a> <span class="k">def</span> <span class="nf">inside</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ge</span><span class="p">,</span> <span class="n">le</span><span class="p">):</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="n">bisect_right</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">le</span><span class="p">)</span>
|
||||
<span class="n">g</span> <span class="o">=</span> <span class="n">bisect_left</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">ge</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">g</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="ow">and</span> <span class="n">l</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="ow">and</span> <span class="n">g</span> <span class="o">!=</span> <span class="n">l</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">[</span><span class="n">g</span> <span class="p">:</span> <span class="n">l</span><span class="p">]</span>
|
||||
<span class="k">elif</span> <span class="n">g</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="ow">and</span> <span class="n">l</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="ow">and</span> <span class="n">g</span> <span class="o">==</span> <span class="n">l</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="p">[</span> <span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">[</span><span class="n">g</span><span class="p">]</span> <span class="p">]</span>
|
||||
<span class="k">elif</span> <span class="n">g</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">[</span><span class="n">g</span><span class="o">-</span><span class="mi">1</span><span class="p">:</span> <span class="n">l</span><span class="p">]</span>
|
||||
<span class="k">elif</span> <span class="n">l</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">[</span><span class="n">g</span><span class="p">:</span> <span class="n">l</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">[</span><span class="n">g</span> <span class="o">-</span> <span class="mi">1</span><span class="p">:</span> <span class="n">l</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span>
|
||||
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s1">'No item found inside keys: </span><span class="si">%r</span><span class="s1">,</span><span class="si">%r</span><span class="s1">'</span> <span class="o">%</span> <span class="p">(</span><span class="n">ge</span><span class="p">,</span><span class="n">le</span><span class="p">))</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SortedCollection.around"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.SortedCollection.SortedCollection.around">[docs]</a> <span class="k">def</span> <span class="nf">around</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span>
|
||||
<span class="n">g</span> <span class="o">=</span> <span class="n">bisect_right</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="n">bisect_left</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_keys</span><span class="p">,</span> <span class="n">k</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">g</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span> <span class="ow">and</span> <span class="n">l</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_items</span><span class="p">[</span><span class="n">g</span> <span class="p">:</span> <span class="n">l</span><span class="p">]</span>
|
||||
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s1">'No item found around key : </span><span class="si">%r</span><span class="s1">'</span> <span class="o">%</span> <span class="p">(</span><span class="n">k</span><span class="p">,))</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
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||||
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<h3>Related Topics</h3>
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313
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<h1>Source code for pyFTS.common.Transformations</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">Common data transformation used on pre and post processing of the FTS</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">math</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="k">import</span> <span class="o">*</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="Transformation"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Transformation">[docs]</a><span class="k">class</span> <span class="nc">Transformation</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Data transformation used on pre and post processing of the FTS</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_invertible</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">minimal_length</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
|
||||
<div class="viewcode-block" id="Transformation.apply"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Transformation.apply">[docs]</a> <span class="k">def</span> <span class="nf">apply</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">param</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Apply the transformation on input data</span>
|
||||
|
||||
<span class="sd"> :param data: input data</span>
|
||||
<span class="sd"> :param param:</span>
|
||||
<span class="sd"> :param kwargs:</span>
|
||||
<span class="sd"> :return: numpy array with transformed data</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">pass</span></div>
|
||||
|
||||
<div class="viewcode-block" id="Transformation.inverse"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Transformation.inverse">[docs]</a> <span class="k">def</span> <span class="nf">inverse</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">data</span><span class="p">,</span> <span class="n">param</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="sd"> :param data: transformed data</span>
|
||||
<span class="sd"> :param param:</span>
|
||||
<span class="sd"> :param kwargs:</span>
|
||||
<span class="sd"> :return: numpy array with inverse transformed data</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">pass</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span> <span class="o">+</span> <span class="s1">'('</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">parameters</span><span class="p">)</span> <span class="o">+</span> <span class="s1">')'</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="Differential"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Differential">[docs]</a><span class="k">class</span> <span class="nc">Differential</span><span class="p">(</span><span class="n">Transformation</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Differentiation data transform</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">lag</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">Differential</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">lag</span> <span class="o">=</span> <span class="n">lag</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">minimal_length</span> <span class="o">=</span> <span class="mi">2</span>
|
||||
|
||||
<span class="nd">@property</span>
|
||||
<span class="k">def</span> <span class="nf">parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">lag</span>
|
||||
|
||||
<div class="viewcode-block" id="Differential.apply"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Differential.apply">[docs]</a> <span class="k">def</span> <span class="nf">apply</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">param</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">param</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">lag</span> <span class="o">=</span> <span class="n">param</span>
|
||||
|
||||
<span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">generic</span><span class="p">)):</span>
|
||||
<span class="n">data</span> <span class="o">=</span> <span class="p">[</span><span class="n">data</span><span class="p">]</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">generic</span><span class="p">)):</span>
|
||||
<span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
|
||||
|
||||
<span class="n">n</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">diff</span> <span class="o">=</span> <span class="p">[</span><span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">-</span> <span class="n">data</span><span class="p">[</span><span class="n">t</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">lag</span><span class="p">]</span> <span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">lag</span><span class="p">,</span> <span class="n">n</span><span class="p">)]</span>
|
||||
<span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">lag</span><span class="p">):</span> <span class="n">diff</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">diff</span></div>
|
||||
|
||||
<div class="viewcode-block" id="Differential.inverse"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Differential.inverse">[docs]</a> <span class="k">def</span> <span class="nf">inverse</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">param</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="nb">type</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"type"</span><span class="p">,</span><span class="s2">"point"</span><span class="p">)</span>
|
||||
<span class="n">steps_ahead</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"steps_ahead"</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">generic</span><span class="p">)):</span>
|
||||
<span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
|
||||
|
||||
<span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="n">data</span> <span class="o">=</span> <span class="p">[</span><span class="n">data</span><span class="p">]</span>
|
||||
|
||||
<span class="n">n</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="c1"># print(n)</span>
|
||||
<span class="c1"># print(len(param))</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">steps_ahead</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="nb">type</span> <span class="o">==</span> <span class="s2">"point"</span><span class="p">:</span>
|
||||
<span class="n">inc</span> <span class="o">=</span> <span class="p">[</span><span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">+</span> <span class="n">param</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">n</span><span class="p">)]</span>
|
||||
<span class="k">elif</span> <span class="nb">type</span> <span class="o">==</span> <span class="s2">"interval"</span><span class="p">:</span>
|
||||
<span class="n">inc</span> <span class="o">=</span> <span class="p">[[</span><span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">param</span><span class="p">[</span><span class="n">t</span><span class="p">],</span> <span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">][</span><span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="n">param</span><span class="p">[</span><span class="n">t</span><span class="p">]]</span> <span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">n</span><span class="p">)]</span>
|
||||
<span class="k">elif</span> <span class="nb">type</span> <span class="o">==</span> <span class="s2">"distribution"</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">n</span><span class="p">):</span>
|
||||
<span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">]</span><span class="o">.</span><span class="n">differential_offset</span><span class="p">(</span><span class="n">param</span><span class="p">[</span><span class="n">t</span><span class="p">])</span>
|
||||
<span class="n">inc</span> <span class="o">=</span> <span class="n">data</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="nb">type</span> <span class="o">==</span> <span class="s2">"point"</span><span class="p">:</span>
|
||||
<span class="n">inc</span> <span class="o">=</span> <span class="p">[</span><span class="n">data</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span>
|
||||
<span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">steps_ahead</span><span class="p">):</span>
|
||||
<span class="n">inc</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">+</span> <span class="n">inc</span><span class="p">[</span><span class="n">t</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="k">elif</span> <span class="nb">type</span> <span class="o">==</span> <span class="s2">"interval"</span><span class="p">:</span>
|
||||
<span class="n">inc</span> <span class="o">=</span> <span class="p">[[</span><span class="n">data</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">data</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">]]]</span>
|
||||
<span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">steps_ahead</span><span class="p">):</span>
|
||||
<span class="n">inc</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmean</span><span class="p">(</span><span class="n">inc</span><span class="p">[</span><span class="n">t</span><span class="o">-</span><span class="mi">1</span><span class="p">]),</span> <span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">][</span><span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmean</span><span class="p">(</span><span class="n">inc</span><span class="p">[</span><span class="n">t</span><span class="o">-</span><span class="mi">1</span><span class="p">])])</span>
|
||||
<span class="k">elif</span> <span class="nb">type</span> <span class="o">==</span> <span class="s2">"distribution"</span><span class="p">:</span>
|
||||
<span class="n">data</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">differential_offset</span><span class="p">(</span><span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
|
||||
<span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">steps_ahead</span><span class="p">):</span>
|
||||
<span class="n">ex</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">expected_value</span><span class="p">()</span>
|
||||
<span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">]</span><span class="o">.</span><span class="n">differential_offset</span><span class="p">(</span><span class="n">ex</span><span class="p">)</span>
|
||||
<span class="n">inc</span> <span class="o">=</span> <span class="n">data</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">n</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">inc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">inc</span></div></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="Scale"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Scale">[docs]</a><span class="k">class</span> <span class="nc">Scale</span><span class="p">(</span><span class="n">Transformation</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Scale data inside a interval [min, max]</span>
|
||||
|
||||
<span class="sd"> </span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="nb">min</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="nb">max</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">Scale</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">data_max</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">data_min</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">transf_max</span> <span class="o">=</span> <span class="nb">max</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">transf_min</span> <span class="o">=</span> <span class="nb">min</span>
|
||||
|
||||
<span class="nd">@property</span>
|
||||
<span class="k">def</span> <span class="nf">parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">transf_max</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">transf_min</span><span class="p">]</span>
|
||||
|
||||
<div class="viewcode-block" id="Scale.apply"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Scale.apply">[docs]</a> <span class="k">def</span> <span class="nf">apply</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">param</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span><span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">data_max</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">data_max</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmax</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">data_min</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmin</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">data_range</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">data_max</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">data_min</span>
|
||||
<span class="n">transf_range</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">transf_max</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">transf_min</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[(</span><span class="n">k</span> <span class="o">+</span> <span class="p">(</span><span class="o">-</span><span class="mi">1</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">data_min</span><span class="p">))</span> <span class="o">/</span> <span class="n">data_range</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">data</span><span class="p">]</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="p">[</span> <span class="p">(</span><span class="n">k</span> <span class="o">*</span> <span class="n">transf_range</span><span class="p">)</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">transf_min</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">tmp</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">(</span><span class="n">data</span> <span class="o">+</span> <span class="p">(</span><span class="o">-</span><span class="mi">1</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">data_min</span><span class="p">))</span> <span class="o">/</span> <span class="n">data_range</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="p">(</span><span class="n">tmp</span> <span class="o">*</span> <span class="n">transf_range</span><span class="p">)</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">transf_min</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">tmp2</span></div>
|
||||
|
||||
<div class="viewcode-block" id="Scale.inverse"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Scale.inverse">[docs]</a> <span class="k">def</span> <span class="nf">inverse</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">param</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">data_range</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">data_max</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">data_min</span>
|
||||
<span class="n">transf_range</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">transf_max</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">transf_min</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="p">[(</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">transf_min</span><span class="p">)</span> <span class="o">/</span> <span class="n">transf_range</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">data</span><span class="p">]</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[(</span><span class="n">k</span> <span class="o">*</span> <span class="n">data_range</span><span class="p">)</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">data_min</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">tmp2</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="p">(</span><span class="n">data</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">transf_min</span><span class="p">)</span> <span class="o">/</span> <span class="n">transf_range</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">(</span><span class="n">tmp2</span> <span class="o">*</span> <span class="n">data_range</span><span class="p">)</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">data_min</span>
|
||||
<span class="k">return</span> <span class="n">tmp</span></div></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="AdaptiveExpectation"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.AdaptiveExpectation">[docs]</a><span class="k">class</span> <span class="nc">AdaptiveExpectation</span><span class="p">(</span><span class="n">Transformation</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Adaptive Expectation post processing</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">parameters</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">AdaptiveExpectation</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">parameters</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">h</span> <span class="o">=</span> <span class="n">parameters</span>
|
||||
|
||||
<span class="nd">@property</span>
|
||||
<span class="k">def</span> <span class="nf">parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">parameters</span>
|
||||
|
||||
<div class="viewcode-block" id="AdaptiveExpectation.apply"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.AdaptiveExpectation.apply">[docs]</a> <span class="k">def</span> <span class="nf">apply</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">param</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span><span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">data</span></div>
|
||||
|
||||
<div class="viewcode-block" id="AdaptiveExpectation.inverse"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.AdaptiveExpectation.inverse">[docs]</a> <span class="k">def</span> <span class="nf">inverse</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">param</span><span class="p">,</span><span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">n</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="n">inc</span> <span class="o">=</span> <span class="p">[</span><span class="n">param</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">h</span><span class="o">*</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">-</span> <span class="n">param</span><span class="p">[</span><span class="n">t</span><span class="p">])</span> <span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">n</span><span class="p">)]</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">n</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">inc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">inc</span></div></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="BoxCox"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.BoxCox">[docs]</a><span class="k">class</span> <span class="nc">BoxCox</span><span class="p">(</span><span class="n">Transformation</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Box-Cox power transformation</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">plambda</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">BoxCox</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">()</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">plambda</span> <span class="o">=</span> <span class="n">plambda</span>
|
||||
|
||||
<span class="nd">@property</span>
|
||||
<span class="k">def</span> <span class="nf">parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">plambda</span>
|
||||
|
||||
<div class="viewcode-block" id="BoxCox.apply"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.BoxCox.apply">[docs]</a> <span class="k">def</span> <span class="nf">apply</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">param</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">plambda</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">modified</span> <span class="o">=</span> <span class="p">[(</span><span class="n">dat</span> <span class="o">**</span> <span class="bp">self</span><span class="o">.</span><span class="n">plambda</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">plambda</span> <span class="k">for</span> <span class="n">dat</span> <span class="ow">in</span> <span class="n">data</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">modified</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">dat</span><span class="p">)</span> <span class="k">for</span> <span class="n">dat</span> <span class="ow">in</span> <span class="n">data</span><span class="p">]</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">modified</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="BoxCox.inverse"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.BoxCox.inverse">[docs]</a> <span class="k">def</span> <span class="nf">inverse</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">param</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">plambda</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">modified</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">dat</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">plambda</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span> <span class="p">)</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">plambda</span> <span class="k">for</span> <span class="n">dat</span> <span class="ow">in</span> <span class="n">data</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">modified</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="n">dat</span><span class="p">)</span> <span class="k">for</span> <span class="n">dat</span> <span class="ow">in</span> <span class="n">data</span><span class="p">]</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">modified</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="Z"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Z">[docs]</a><span class="k">def</span> <span class="nf">Z</span><span class="p">(</span><span class="n">original</span><span class="p">):</span>
|
||||
<span class="n">mu</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">original</span><span class="p">)</span>
|
||||
<span class="n">sigma</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">original</span><span class="p">)</span>
|
||||
<span class="n">z</span> <span class="o">=</span> <span class="p">[(</span><span class="n">k</span> <span class="o">-</span> <span class="n">mu</span><span class="p">)</span><span class="o">/</span><span class="n">sigma</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">original</span><span class="p">]</span>
|
||||
<span class="k">return</span> <span class="n">z</span></div>
|
||||
|
||||
|
||||
<span class="c1"># retrieved from Sadaei and Lee (2014) - Multilayer Stock ForecastingModel Using Fuzzy Time Series</span>
|
||||
<div class="viewcode-block" id="roi"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.roi">[docs]</a><span class="k">def</span> <span class="nf">roi</span><span class="p">(</span><span class="n">original</span><span class="p">):</span>
|
||||
<span class="n">n</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">original</span><span class="p">)</span>
|
||||
<span class="n">roi</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">n</span><span class="o">-</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="n">roi</span><span class="o">.</span><span class="n">append</span><span class="p">(</span> <span class="p">(</span><span class="n">original</span><span class="p">[</span><span class="n">t</span><span class="o">+</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">original</span><span class="p">[</span><span class="n">t</span><span class="p">])</span><span class="o">/</span><span class="n">original</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">roi</span></div>
|
||||
|
||||
<div class="viewcode-block" id="smoothing"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.smoothing">[docs]</a><span class="k">def</span> <span class="nf">smoothing</span><span class="p">(</span><span class="n">original</span><span class="p">,</span> <span class="n">lags</span><span class="p">):</span>
|
||||
<span class="k">pass</span></div>
|
||||
|
||||
<div class="viewcode-block" id="aggregate"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.aggregate">[docs]</a><span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="n">original</span><span class="p">,</span> <span class="n">operation</span><span class="p">):</span>
|
||||
<span class="k">pass</span></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
||||
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|
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<li><a href="../../../index.html">Documentation overview</a><ul>
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<h3>Quick search</h3>
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<form class="search" action="../../../search.html" method="get">
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<input type="submit" value="Go" />
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©2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
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Powered by <a href="http://sphinx-doc.org/">Sphinx 1.7.2</a>
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413
docs/_build/html/_modules/pyFTS/common/Util.html
vendored
Normal file
413
docs/_build/html/_modules/pyFTS/common/Util.html
vendored
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@ -0,0 +1,413 @@
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
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<h1>Source code for pyFTS.common.Util</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">Common facilities for pyFTS</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">time</span>
|
||||
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
|
||||
<span class="kn">import</span> <span class="nn">dill</span>
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="plot_rules"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.plot_rules">[docs]</a><span class="k">def</span> <span class="nf">plot_rules</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">[</span><span class="mi">5</span><span class="p">,</span> <span class="mi">5</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">rules_by_axis</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">columns</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">axis</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">rules_by_axis</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">rows</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="k">elif</span> <span class="n">axis</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">rules_by_axis</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">rows</span> <span class="o">=</span> <span class="p">(((</span><span class="nb">len</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span><span class="o">//</span><span class="n">rules_by_axis</span><span class="p">))</span> <span class="o">//</span> <span class="n">columns</span><span class="p">)</span><span class="o">+</span><span class="mi">1</span>
|
||||
|
||||
<span class="n">fig</span><span class="p">,</span> <span class="n">axis</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">nrows</span><span class="o">=</span><span class="n">rows</span><span class="p">,</span> <span class="n">ncols</span><span class="o">=</span><span class="n">columns</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="n">size</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">rules_by_axis</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">draw_sets_on_axis</span><span class="p">(</span><span class="n">axis</span><span class="p">,</span> <span class="n">model</span><span class="p">,</span> <span class="n">size</span><span class="p">)</span>
|
||||
|
||||
<span class="n">_lhs</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span> <span class="k">if</span> <span class="ow">not</span> <span class="n">model</span><span class="o">.</span><span class="n">is_high_order</span> <span class="k">else</span> <span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="o">.</span><span class="n">keys</span><span class="p">()</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">key</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">_lhs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">xticks</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">xtickslabels</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">rules_by_axis</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">ax</span> <span class="o">=</span> <span class="n">axis</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">colcount</span> <span class="o">=</span> <span class="p">(</span><span class="n">ct</span> <span class="o">//</span> <span class="n">rules_by_axis</span><span class="p">)</span> <span class="o">%</span> <span class="n">columns</span>
|
||||
<span class="n">rowcount</span> <span class="o">=</span> <span class="p">(</span><span class="n">ct</span> <span class="o">//</span> <span class="n">rules_by_axis</span><span class="p">)</span> <span class="o">//</span> <span class="n">columns</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">rows</span> <span class="o">></span> <span class="mi">1</span> <span class="ow">and</span> <span class="n">columns</span> <span class="o">></span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">ax</span> <span class="o">=</span> <span class="n">axis</span><span class="p">[</span><span class="n">rowcount</span><span class="p">,</span> <span class="n">colcount</span><span class="p">]</span>
|
||||
<span class="k">elif</span> <span class="n">columns</span> <span class="o">></span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">ax</span> <span class="o">=</span> <span class="n">axis</span><span class="p">[</span><span class="n">rowcount</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ax</span> <span class="o">=</span> <span class="n">axis</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">ct</span> <span class="o">%</span> <span class="n">rules_by_axis</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">draw_sets_on_axis</span><span class="p">(</span><span class="n">ax</span><span class="p">,</span> <span class="n">model</span><span class="p">,</span> <span class="n">size</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="ow">not</span> <span class="n">model</span><span class="o">.</span><span class="n">is_high_order</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">x</span> <span class="o">=</span> <span class="p">(</span><span class="n">ct</span> <span class="o">%</span> <span class="n">rules_by_axis</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span>
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">key</span><span class="p">]</span>
|
||||
<span class="n">y</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="n">x</span><span class="p">],[</span><span class="n">y</span><span class="p">],</span><span class="s1">'o'</span><span class="p">)</span>
|
||||
<span class="n">xticks</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
|
||||
<span class="n">xtickslabels</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">key</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">rhs</span> <span class="ow">in</span> <span class="n">flrg</span><span class="o">.</span><span class="n">RHS</span><span class="p">:</span>
|
||||
<span class="n">dest</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">rhs</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">arrow</span><span class="p">(</span><span class="n">x</span><span class="o">+.</span><span class="mi">1</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="mf">0.8</span><span class="p">,</span> <span class="n">dest</span> <span class="o">-</span> <span class="n">y</span><span class="p">,</span> <span class="c1">#length_includes_head=True,</span>
|
||||
<span class="n">head_width</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">head_length</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="s1">'full'</span><span class="p">,</span> <span class="n">overhang</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span>
|
||||
<span class="n">fc</span><span class="o">=</span><span class="s1">'k'</span><span class="p">,</span> <span class="n">ec</span><span class="o">=</span><span class="s1">'k'</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">key</span><span class="p">]</span>
|
||||
<span class="n">x</span> <span class="o">=</span> <span class="p">(</span><span class="n">ct</span><span class="o">%</span><span class="n">rules_by_axis</span><span class="p">)</span><span class="o">*</span><span class="n">model</span><span class="o">.</span><span class="n">order</span> <span class="o">+</span> <span class="mi">1</span>
|
||||
<span class="k">for</span> <span class="n">ct2</span><span class="p">,</span> <span class="n">lhs</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">):</span>
|
||||
<span class="n">y</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">lhs</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="n">x</span><span class="o">+</span><span class="n">ct2</span><span class="p">],</span> <span class="p">[</span><span class="n">y</span><span class="p">],</span> <span class="s1">'o'</span><span class="p">)</span>
|
||||
<span class="n">xticks</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">x</span><span class="o">+</span><span class="n">ct2</span><span class="p">)</span>
|
||||
<span class="n">xtickslabels</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">lhs</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">ct2</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">):</span>
|
||||
<span class="n">fs1</span> <span class="o">=</span> <span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="n">ct2</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
|
||||
<span class="n">fs2</span> <span class="o">=</span> <span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="n">ct2</span><span class="p">]</span>
|
||||
<span class="n">y</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">fs1</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span>
|
||||
<span class="n">dest</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">fs2</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="n">x</span><span class="o">+</span><span class="n">ct2</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span><span class="n">x</span><span class="o">+</span><span class="n">ct2</span><span class="p">],</span> <span class="p">[</span><span class="n">y</span><span class="p">,</span><span class="n">dest</span><span class="p">],</span><span class="s1">'-'</span><span class="p">)</span>
|
||||
|
||||
<span class="n">y</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]]</span><span class="o">.</span><span class="n">centroid</span>
|
||||
<span class="k">for</span> <span class="n">rhs</span> <span class="ow">in</span> <span class="n">flrg</span><span class="o">.</span><span class="n">RHS</span><span class="p">:</span>
|
||||
<span class="n">dest</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">rhs</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">arrow</span><span class="p">(</span><span class="n">x</span> <span class="o">+</span> <span class="n">model</span><span class="o">.</span><span class="n">order</span> <span class="o">-</span><span class="mi">1</span> <span class="o">+</span> <span class="o">.</span><span class="mi">1</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="mf">0.8</span><span class="p">,</span> <span class="n">dest</span> <span class="o">-</span> <span class="n">y</span><span class="p">,</span> <span class="c1"># length_includes_head=True,</span>
|
||||
<span class="n">head_width</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">head_length</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">shape</span><span class="o">=</span><span class="s1">'full'</span><span class="p">,</span> <span class="n">overhang</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span>
|
||||
<span class="n">fc</span><span class="o">=</span><span class="s1">'k'</span><span class="p">,</span> <span class="n">ec</span><span class="o">=</span><span class="s1">'k'</span><span class="p">)</span>
|
||||
|
||||
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">set_xticks</span><span class="p">(</span><span class="n">xticks</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">(</span><span class="n">xtickslabels</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">set_xlim</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span><span class="n">rules_by_axis</span><span class="o">*</span><span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="o">+</span><span class="mi">1</span><span class="p">])</span>
|
||||
|
||||
<span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
|
||||
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="draw_sets_on_axis"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.draw_sets_on_axis">[docs]</a><span class="k">def</span> <span class="nf">draw_sets_on_axis</span><span class="p">(</span><span class="n">axis</span><span class="p">,</span> <span class="n">model</span><span class="p">,</span> <span class="n">size</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">axis</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">fig</span><span class="p">,</span> <span class="n">axis</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">nrows</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">ncols</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="n">size</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">key</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">):</span>
|
||||
<span class="n">fs</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span>
|
||||
<span class="n">axis</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span> <span class="n">fs</span><span class="o">.</span><span class="n">parameters</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">fs</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
|
||||
<span class="n">axis</span><span class="o">.</span><span class="n">axhline</span><span class="p">(</span><span class="n">fs</span><span class="o">.</span><span class="n">centroid</span><span class="p">,</span> <span class="n">c</span><span class="o">=</span><span class="s2">"lightgray"</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.5</span><span class="p">)</span>
|
||||
<span class="n">axis</span><span class="o">.</span><span class="n">set_xlim</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">)])</span>
|
||||
<span class="n">axis</span><span class="o">.</span><span class="n">set_xticks</span><span class="p">(</span><span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">)))</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[</span><span class="s1">''</span><span class="p">]</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">)</span>
|
||||
<span class="n">axis</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="n">axis</span><span class="o">.</span><span class="n">set_ylim</span><span class="p">([</span><span class="n">model</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">min</span><span class="p">,</span> <span class="n">model</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">max</span><span class="p">])</span>
|
||||
<span class="n">axis</span><span class="o">.</span><span class="n">set_yticks</span><span class="p">([</span><span class="n">model</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">k</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">model</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">])</span>
|
||||
<span class="n">axis</span><span class="o">.</span><span class="n">set_yticklabels</span><span class="p">([</span><span class="nb">str</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">k</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span><span class="p">,</span> <span class="mi">1</span><span class="p">))</span> <span class="o">+</span> <span class="s2">" - "</span> <span class="o">+</span> <span class="n">k</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">model</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">])</span></div>
|
||||
|
||||
|
||||
<span class="n">current_milli_time</span> <span class="o">=</span> <span class="k">lambda</span><span class="p">:</span> <span class="nb">int</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span> <span class="o">*</span> <span class="mi">1000</span><span class="p">))</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="uniquefilename"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.uniquefilename">[docs]</a><span class="k">def</span> <span class="nf">uniquefilename</span><span class="p">(</span><span class="n">name</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="s1">'.'</span> <span class="ow">in</span> <span class="n">name</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">name</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">'.'</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">tmp</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">current_milli_time</span><span class="p">())</span> <span class="o">+</span> <span class="s1">'.'</span> <span class="o">+</span> <span class="n">tmp</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">name</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">current_milli_time</span><span class="p">())</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="show_and_save_image"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.show_and_save_image">[docs]</a><span class="k">def</span> <span class="nf">show_and_save_image</span><span class="p">(</span><span class="n">fig</span><span class="p">,</span> <span class="n">file</span><span class="p">,</span> <span class="n">flag</span><span class="p">,</span> <span class="n">lgd</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Show and image and save on file</span>
|
||||
|
||||
<span class="sd"> :param fig: Matplotlib Figure object</span>
|
||||
<span class="sd"> :param file: filename to save the picture</span>
|
||||
<span class="sd"> :param flag: if True the image will be saved</span>
|
||||
<span class="sd"> :param lgd: legend</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">if</span> <span class="n">flag</span><span class="p">:</span>
|
||||
<span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
|
||||
<span class="k">if</span> <span class="n">lgd</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">fig</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">file</span><span class="p">,</span> <span class="n">additional_artists</span><span class="o">=</span><span class="n">lgd</span><span class="p">,</span><span class="n">bbox_inches</span><span class="o">=</span><span class="s1">'tight'</span><span class="p">)</span> <span class="c1">#bbox_extra_artists=(lgd,), )</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">fig</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">file</span><span class="p">)</span>
|
||||
<span class="n">plt</span><span class="o">.</span><span class="n">close</span><span class="p">(</span><span class="n">fig</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="enumerate2"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.enumerate2">[docs]</a><span class="k">def</span> <span class="nf">enumerate2</span><span class="p">(</span><span class="n">xs</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">step</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">xs</span><span class="p">:</span>
|
||||
<span class="k">yield</span> <span class="p">(</span><span class="n">start</span><span class="p">,</span> <span class="n">x</span><span class="p">)</span>
|
||||
<span class="n">start</span> <span class="o">+=</span> <span class="n">step</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="sliding_window"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.sliding_window">[docs]</a><span class="k">def</span> <span class="nf">sliding_window</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">windowsize</span><span class="p">,</span> <span class="n">train</span><span class="o">=</span><span class="mf">0.8</span><span class="p">,</span> <span class="n">inc</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Sliding window method of cross validation for time series</span>
|
||||
|
||||
<span class="sd"> :param data: the entire dataset</span>
|
||||
<span class="sd"> :param windowsize: window size</span>
|
||||
<span class="sd"> :param train: percentual of the window size will be used for training the models</span>
|
||||
<span class="sd"> :param inc: percentual of data used for slide the window</span>
|
||||
<span class="sd"> :return: window count, training set, test set</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">ttrain</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">windowsize</span> <span class="o">*</span> <span class="n">train</span><span class="p">,</span> <span class="mi">0</span><span class="p">))</span>
|
||||
<span class="n">ic</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">windowsize</span> <span class="o">*</span> <span class="n">inc</span><span class="p">,</span> <span class="mi">0</span><span class="p">))</span>
|
||||
|
||||
<span class="n">progressbar</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'progress'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="n">rng</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="n">l</span><span class="o">-</span><span class="n">windowsize</span><span class="o">+</span><span class="n">ic</span><span class="p">,</span><span class="n">ic</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">progressbar</span><span class="p">:</span>
|
||||
<span class="kn">from</span> <span class="nn">tqdm</span> <span class="k">import</span> <span class="n">tqdm</span>
|
||||
<span class="n">rng</span> <span class="o">=</span> <span class="n">tqdm</span><span class="p">(</span><span class="n">rng</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">count</span> <span class="ow">in</span> <span class="n">rng</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">count</span> <span class="o">+</span> <span class="n">windowsize</span> <span class="o">></span> <span class="n">l</span><span class="p">:</span>
|
||||
<span class="n">_end</span> <span class="o">=</span> <span class="n">l</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">_end</span> <span class="o">=</span> <span class="n">count</span> <span class="o">+</span> <span class="n">windowsize</span>
|
||||
<span class="k">yield</span> <span class="p">(</span><span class="n">count</span><span class="p">,</span> <span class="n">data</span><span class="p">[</span><span class="n">count</span> <span class="p">:</span> <span class="n">count</span> <span class="o">+</span> <span class="n">ttrain</span><span class="p">],</span> <span class="n">data</span><span class="p">[</span><span class="n">count</span> <span class="o">+</span> <span class="n">ttrain</span> <span class="p">:</span> <span class="n">_end</span><span class="p">]</span> <span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="persist_obj"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.persist_obj">[docs]</a><span class="k">def</span> <span class="nf">persist_obj</span><span class="p">(</span><span class="n">obj</span><span class="p">,</span> <span class="n">file</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Persist an object on filesystem. This function depends on Dill package</span>
|
||||
|
||||
<span class="sd"> :param obj: object on memory</span>
|
||||
<span class="sd"> :param file: file name to store the object</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">file</span><span class="p">,</span> <span class="s1">'wb'</span><span class="p">)</span> <span class="k">as</span> <span class="n">_file</span><span class="p">:</span>
|
||||
<span class="n">dill</span><span class="o">.</span><span class="n">dump</span><span class="p">(</span><span class="n">obj</span><span class="p">,</span> <span class="n">_file</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="load_obj"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.load_obj">[docs]</a><span class="k">def</span> <span class="nf">load_obj</span><span class="p">(</span><span class="n">file</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Load to memory an object stored filesystem. This function depends on Dill package</span>
|
||||
|
||||
<span class="sd"> :param file: file name where the object is stored</span>
|
||||
<span class="sd"> :return: object</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">with</span> <span class="nb">open</span><span class="p">(</span><span class="n">file</span><span class="p">,</span> <span class="s1">'rb'</span><span class="p">)</span> <span class="k">as</span> <span class="n">_file</span><span class="p">:</span>
|
||||
<span class="n">obj</span> <span class="o">=</span> <span class="n">dill</span><span class="o">.</span><span class="n">load</span><span class="p">(</span><span class="n">_file</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">obj</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="persist_env"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.persist_env">[docs]</a><span class="k">def</span> <span class="nf">persist_env</span><span class="p">(</span><span class="n">file</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Persist an entire environment on file. This function depends on Dill package</span>
|
||||
|
||||
<span class="sd"> :param file: file name to store the environment</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">dill</span><span class="o">.</span><span class="n">dump_session</span><span class="p">(</span><span class="n">file</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="load_env"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.load_env">[docs]</a><span class="k">def</span> <span class="nf">load_env</span><span class="p">(</span><span class="n">file</span><span class="p">):</span>
|
||||
<span class="n">dill</span><span class="o">.</span><span class="n">load_session</span><span class="p">(</span><span class="n">file</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="start_dispy_cluster"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.start_dispy_cluster">[docs]</a><span class="k">def</span> <span class="nf">start_dispy_cluster</span><span class="p">(</span><span class="n">method</span><span class="p">,</span> <span class="n">nodes</span><span class="p">):</span>
|
||||
<span class="kn">import</span> <span class="nn">dispy</span><span class="o">,</span> <span class="nn">dispy.httpd</span><span class="o">,</span> <span class="nn">logging</span>
|
||||
|
||||
<span class="n">cluster</span> <span class="o">=</span> <span class="n">dispy</span><span class="o">.</span><span class="n">JobCluster</span><span class="p">(</span><span class="n">method</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="n">nodes</span><span class="p">,</span> <span class="n">loglevel</span><span class="o">=</span><span class="n">logging</span><span class="o">.</span><span class="n">DEBUG</span><span class="p">,</span> <span class="n">ping_interval</span><span class="o">=</span><span class="mi">1000</span><span class="p">)</span>
|
||||
|
||||
<span class="n">http_server</span> <span class="o">=</span> <span class="n">dispy</span><span class="o">.</span><span class="n">httpd</span><span class="o">.</span><span class="n">DispyHTTPServer</span><span class="p">(</span><span class="n">cluster</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">cluster</span><span class="p">,</span> <span class="n">http_server</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="stop_dispy_cluster"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.stop_dispy_cluster">[docs]</a><span class="k">def</span> <span class="nf">stop_dispy_cluster</span><span class="p">(</span><span class="n">cluster</span><span class="p">,</span> <span class="n">http_server</span><span class="p">):</span>
|
||||
<span class="n">cluster</span><span class="o">.</span><span class="n">wait</span><span class="p">()</span> <span class="c1"># wait for all jobs to finish</span>
|
||||
|
||||
<span class="n">cluster</span><span class="o">.</span><span class="n">print_status</span><span class="p">()</span>
|
||||
|
||||
<span class="n">http_server</span><span class="o">.</span><span class="n">shutdown</span><span class="p">()</span> <span class="c1"># this waits until browser gets all updates</span>
|
||||
<span class="n">cluster</span><span class="o">.</span><span class="n">close</span><span class="p">()</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="simple_model_train"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.simple_model_train">[docs]</a><span class="k">def</span> <span class="nf">simple_model_train</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">parameters</span><span class="p">):</span>
|
||||
<span class="n">model</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">parameters</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">model</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="distributed_train"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.distributed_train">[docs]</a><span class="k">def</span> <span class="nf">distributed_train</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">train_method</span><span class="p">,</span> <span class="n">nodes</span><span class="p">,</span> <span class="n">fts_method</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">num_batches</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span>
|
||||
<span class="n">train_parameters</span><span class="o">=</span><span class="p">{},</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="kn">import</span> <span class="nn">dispy</span><span class="o">,</span> <span class="nn">dispy.httpd</span><span class="o">,</span> <span class="nn">datetime</span>
|
||||
|
||||
<span class="n">batch_save</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'batch_save'</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span> <span class="c1"># save model between batches</span>
|
||||
|
||||
<span class="n">batch_save_interval</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'batch_save_interval'</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
|
||||
|
||||
<span class="n">file_path</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'file_path'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="n">cluster</span><span class="p">,</span> <span class="n">http_server</span> <span class="o">=</span> <span class="n">start_dispy_cluster</span><span class="p">(</span><span class="n">train_method</span><span class="p">,</span> <span class="n">nodes</span><span class="p">)</span>
|
||||
|
||||
<span class="nb">print</span><span class="p">(</span><span class="s2">"[{0: %H:%M:%S}] Distrituted Train Started"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">()))</span>
|
||||
|
||||
<span class="n">jobs</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">n</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">batch_size</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">n</span> <span class="o">/</span> <span class="n">num_batches</span><span class="p">)</span>
|
||||
<span class="n">bcount</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="k">for</span> <span class="n">ct</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">model</span><span class="o">.</span><span class="n">is_multivariate</span><span class="p">:</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">ct</span> <span class="o">-</span> <span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">:</span><span class="n">ct</span> <span class="o">+</span> <span class="n">batch_size</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">ct</span> <span class="o">-</span> <span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">:</span> <span class="n">ct</span> <span class="o">+</span> <span class="n">batch_size</span><span class="p">]</span>
|
||||
|
||||
<span class="n">tmp_model</span> <span class="o">=</span> <span class="n">fts_method</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">bcount</span><span class="p">))</span>
|
||||
|
||||
<span class="n">tmp_model</span><span class="o">.</span><span class="n">clone_parameters</span><span class="p">(</span><span class="n">model</span><span class="p">)</span>
|
||||
|
||||
<span class="n">job</span> <span class="o">=</span> <span class="n">cluster</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">tmp_model</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="n">train_parameters</span><span class="p">)</span>
|
||||
<span class="n">job</span><span class="o">.</span><span class="n">id</span> <span class="o">=</span> <span class="n">bcount</span> <span class="c1"># associate an ID to identify jobs (if needed later)</span>
|
||||
<span class="n">jobs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">job</span><span class="p">)</span>
|
||||
|
||||
<span class="n">bcount</span> <span class="o">+=</span> <span class="mi">1</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">job</span> <span class="ow">in</span> <span class="n">jobs</span><span class="p">:</span>
|
||||
<span class="nb">print</span><span class="p">(</span><span class="s2">"[{0: %H:%M:%S}] Processing batch "</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">())</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">job</span><span class="o">.</span><span class="n">id</span><span class="p">))</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">job</span><span class="p">()</span>
|
||||
<span class="k">if</span> <span class="n">job</span><span class="o">.</span><span class="n">status</span> <span class="o">==</span> <span class="n">dispy</span><span class="o">.</span><span class="n">DispyJob</span><span class="o">.</span><span class="n">Finished</span> <span class="ow">and</span> <span class="n">tmp</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">model</span><span class="o">.</span><span class="n">merge</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">batch_save</span> <span class="ow">and</span> <span class="p">(</span><span class="n">job</span><span class="o">.</span><span class="n">id</span> <span class="o">%</span> <span class="n">batch_save_interval</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">persist_obj</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">file_path</span><span class="p">)</span>
|
||||
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="nb">print</span><span class="p">(</span><span class="n">job</span><span class="o">.</span><span class="n">exception</span><span class="p">)</span>
|
||||
<span class="nb">print</span><span class="p">(</span><span class="n">job</span><span class="o">.</span><span class="n">stdout</span><span class="p">)</span>
|
||||
|
||||
<span class="nb">print</span><span class="p">(</span><span class="s2">"[{0: %H:%M:%S}] Finished batch "</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">())</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">job</span><span class="o">.</span><span class="n">id</span><span class="p">))</span>
|
||||
|
||||
<span class="nb">print</span><span class="p">(</span><span class="s2">"[{0: %H:%M:%S}] Distrituted Train Finished"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">()))</span>
|
||||
|
||||
<span class="n">stop_dispy_cluster</span><span class="p">(</span><span class="n">cluster</span><span class="p">,</span> <span class="n">http_server</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">model</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="simple_model_predict"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.simple_model_predict">[docs]</a><span class="k">def</span> <span class="nf">simple_model_predict</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">parameters</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">parameters</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
<div class="viewcode-block" id="distributed_predict"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.distributed_predict">[docs]</a><span class="k">def</span> <span class="nf">distributed_predict</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">parameters</span><span class="p">,</span> <span class="n">nodes</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">num_batches</span><span class="p">):</span>
|
||||
<span class="kn">import</span> <span class="nn">dispy</span><span class="o">,</span> <span class="nn">dispy.httpd</span>
|
||||
|
||||
<span class="n">cluster</span><span class="p">,</span> <span class="n">http_server</span> <span class="o">=</span> <span class="n">start_dispy_cluster</span><span class="p">(</span><span class="n">simple_model_predict</span><span class="p">,</span> <span class="n">nodes</span><span class="p">)</span>
|
||||
|
||||
<span class="n">jobs</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">n</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">batch_size</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">n</span> <span class="o">/</span> <span class="n">num_batches</span><span class="p">)</span>
|
||||
<span class="n">bcount</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="k">for</span> <span class="n">ct</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">model</span><span class="o">.</span><span class="n">is_multivariate</span><span class="p">:</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">ct</span> <span class="o">-</span> <span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">:</span><span class="n">ct</span> <span class="o">+</span> <span class="n">batch_size</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">ct</span> <span class="o">-</span> <span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">:</span> <span class="n">ct</span> <span class="o">+</span> <span class="n">batch_size</span><span class="p">]</span>
|
||||
|
||||
<span class="n">job</span> <span class="o">=</span> <span class="n">cluster</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="n">parameters</span><span class="p">)</span>
|
||||
<span class="n">job</span><span class="o">.</span><span class="n">id</span> <span class="o">=</span> <span class="n">bcount</span> <span class="c1"># associate an ID to identify jobs (if needed later)</span>
|
||||
<span class="n">jobs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">job</span><span class="p">)</span>
|
||||
|
||||
<span class="n">bcount</span> <span class="o">+=</span> <span class="mi">1</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">job</span> <span class="ow">in</span> <span class="n">jobs</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">job</span><span class="p">()</span>
|
||||
<span class="k">if</span> <span class="n">job</span><span class="o">.</span><span class="n">status</span> <span class="o">==</span> <span class="n">dispy</span><span class="o">.</span><span class="n">DispyJob</span><span class="o">.</span><span class="n">Finished</span> <span class="ow">and</span> <span class="n">tmp</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">job</span><span class="o">.</span><span class="n">id</span> <span class="o"><</span> <span class="n">batch_size</span><span class="p">:</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">tmp</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="nb">print</span><span class="p">(</span><span class="n">job</span><span class="o">.</span><span class="n">exception</span><span class="p">)</span>
|
||||
<span class="nb">print</span><span class="p">(</span><span class="n">job</span><span class="o">.</span><span class="n">stdout</span><span class="p">)</span>
|
||||
|
||||
<span class="n">stop_dispy_cluster</span><span class="p">(</span><span class="n">cluster</span><span class="p">,</span> <span class="n">http_server</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
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|
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<h1>Source code for pyFTS.common.flrg</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="FLRG"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.flrg.FLRG">[docs]</a><span class="k">class</span> <span class="nc">FLRG</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Fuzzy Logical Relationship Group</span>
|
||||
|
||||
<span class="sd"> Group a set of FLR's with the same LHS. Represents the temporal patterns for time t+1 (the RHS fuzzy sets)</span>
|
||||
<span class="sd"> when the LHS pattern is identified on time t.</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="sd">"""Left Hand Side of the rule"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="sd">"""Right Hand Side of the rule"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="n">order</span>
|
||||
<span class="sd">"""Number of lags on LHS"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">midpoint</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">lower</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">upper</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">key</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
|
||||
<div class="viewcode-block" id="FLRG.append_rhs"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.flrg.FLRG.append_rhs">[docs]</a> <span class="k">def</span> <span class="nf">append_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="nb">set</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">pass</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FLRG.get_key"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.flrg.FLRG.get_key">[docs]</a> <span class="k">def</span> <span class="nf">get_key</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="sd">"""Returns a unique identifier for this FLRG"""</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">key</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="nb">set</span><span class="p">)):</span>
|
||||
<span class="n">names</span> <span class="o">=</span> <span class="p">[</span><span class="n">c</span> <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span>
|
||||
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span>
|
||||
<span class="n">names</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">names</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">key</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="n">names</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">key</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">key</span> <span class="o">+=</span> <span class="s2">","</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">key</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">key</span> <span class="o">+</span> <span class="n">n</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">key</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FLRG.get_membership"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.flrg.FLRG.get_membership">[docs]</a> <span class="k">def</span> <span class="nf">get_membership</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Returns the membership value of the FLRG for the input data</span>
|
||||
|
||||
<span class="sd"> :param data: input data</span>
|
||||
<span class="sd"> :param sets: fuzzy sets</span>
|
||||
<span class="sd"> :return: the membership value</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="mf">0.0</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="nb">set</span><span class="p">)):</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmin</span><span class="p">([</span><span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="n">ct</span><span class="p">]]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">dat</span><span class="p">)</span> <span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">dat</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">data</span><span class="p">)])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FLRG.get_midpoint"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.flrg.FLRG.get_midpoint">[docs]</a> <span class="k">def</span> <span class="nf">get_midpoint</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Returns the midpoint value for the RHS fuzzy sets</span>
|
||||
|
||||
<span class="sd"> :param sets: fuzzy sets</span>
|
||||
<span class="sd"> :return: the midpoint value</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">midpoint</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">midpoint</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmean</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">get_midpoints</span><span class="p">(</span><span class="n">sets</span><span class="p">))</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">midpoint</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FLRG.get_midpoints"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.flrg.FLRG.get_midpoints">[docs]</a> <span class="k">def</span> <span class="nf">get_midpoints</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="nb">set</span><span class="p">)):</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">])</span>
|
||||
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">s</span><span class="p">]]</span><span class="o">.</span><span class="n">centroid</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()])</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FLRG.get_lower"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.flrg.FLRG.get_lower">[docs]</a> <span class="k">def</span> <span class="nf">get_lower</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Returns the lower bound value for the RHS fuzzy sets</span>
|
||||
|
||||
<span class="sd"> :param sets: fuzzy sets</span>
|
||||
<span class="sd"> :return: lower bound value</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">lower</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">lower</span> <span class="o">=</span> <span class="nb">min</span><span class="p">([</span><span class="n">sets</span><span class="p">[</span><span class="n">rhs</span><span class="p">]</span><span class="o">.</span><span class="n">lower</span> <span class="k">for</span> <span class="n">rhs</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">])</span>
|
||||
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">lower</span> <span class="o">=</span> <span class="nb">min</span><span class="p">([</span><span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">s</span><span class="p">]]</span><span class="o">.</span><span class="n">lower</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()])</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">lower</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FLRG.get_upper"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.flrg.FLRG.get_upper">[docs]</a> <span class="k">def</span> <span class="nf">get_upper</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Returns the upper bound value for the RHS fuzzy sets</span>
|
||||
|
||||
<span class="sd"> :param sets: fuzzy sets</span>
|
||||
<span class="sd"> :return: upper bound value</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">upper</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">upper</span> <span class="o">=</span> <span class="nb">max</span><span class="p">([</span><span class="n">sets</span><span class="p">[</span><span class="n">rhs</span><span class="p">]</span><span class="o">.</span><span class="n">upper</span> <span class="k">for</span> <span class="n">rhs</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">])</span>
|
||||
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">upper</span> <span class="o">=</span> <span class="nb">max</span><span class="p">([</span><span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">s</span><span class="p">]]</span><span class="o">.</span><span class="n">upper</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()])</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">upper</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
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|
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|
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<h3>Related Topics</h3>
|
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|
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<li><a href="../../../index.html">Documentation overview</a><ul>
|
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<li><a href="../../index.html">Module code</a><ul>
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<h1>Source code for pyFTS.common.fts</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">SortedCollection</span><span class="p">,</span> <span class="n">tree</span><span class="p">,</span> <span class="n">Util</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="FTS"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS">[docs]</a><span class="k">class</span> <span class="nc">FTS</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Fuzzy Time Series object model</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Create a Fuzzy Time Series model</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="sd">"""The list of fuzzy sets used on this model"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="sd">"""The list of Fuzzy Logical Relationship Groups - FLRG"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'order'</span><span class="p">,</span><span class="mi">1</span><span class="p">)</span>
|
||||
<span class="sd">"""A integer with the model order (number of past lags are used on forecasting)"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'name'</span><span class="p">,</span><span class="s2">""</span><span class="p">)</span>
|
||||
<span class="sd">"""A string with a short name or alias for the model"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'name'</span><span class="p">,</span><span class="s2">""</span><span class="p">)</span>
|
||||
<span class="sd">"""A string with the model name"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'name'</span><span class="p">,</span><span class="s2">""</span><span class="p">)</span>
|
||||
<span class="sd">"""A string with the model detailed information"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
<span class="sd">"""A boolean value indicating if the model support orders greater than 1, default: False"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_order</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="sd">"""In high order models, this integer value indicates the minimal order supported for the model, default: 1"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_seasonality</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
<span class="sd">"""A boolean value indicating if the model supports seasonal indexers, default: False"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_point_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="sd">"""A boolean value indicating if the model supports point forecasting, default: True"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_interval_forecasting</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
<span class="sd">"""A boolean value indicating if the model supports interval forecasting, default: False"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_probability_forecasting</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
<span class="sd">"""A boolean value indicating if the model support probabilistic forecasting, default: False"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_multivariate</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
<span class="sd">"""A boolean value indicating if the model support multivariate time series (Pandas DataFrame), default: False"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">dump</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">transformations</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="sd">"""A list with the data transformations (common.Transformations) applied on model pre and post processing, default: []"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">transformations_param</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="sd">"""A list with the specific parameters for each data transformation"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">original_max</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="sd">"""A float with the upper limit of the Universe of Discourse, the maximal value found on training data"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">original_min</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="sd">"""A float with the lower limit of the Universe of Discourse, the minimal value found on training data"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"partitioner"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="sd">"""A pyFTS.partitioners.Partitioner object with the Universe of Discourse partitioner used on the model. This is a mandatory dependecy. """</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span> <span class="o">!=</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">auto_update</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
<span class="sd">"""A boolean value indicating that model is incremental"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">benchmark_only</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
<span class="sd">"""A boolean value indicating a façade for external (non-FTS) model used on benchmarks or ensembles."""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">indexer</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"indexer"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="sd">"""An pyFTS.models.seasonal.Indexer object for indexing the time series data"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">uod_clip</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"uod_clip"</span><span class="p">,</span> <span class="kc">True</span><span class="p">)</span>
|
||||
<span class="sd">"""Flag indicating if the test data will be clipped inside the training Universe of Discourse"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">alpha_cut</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"alpha_cut"</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">)</span>
|
||||
<span class="sd">"""A float with the minimal membership to be considered on fuzzyfication process"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span>
|
||||
<span class="sd">"""A integer indicating the largest lag used by the model. This value also indicates the minimum number of past lags </span>
|
||||
<span class="sd"> needed to forecast a single step ahead"""</span>
|
||||
|
||||
<div class="viewcode-block" id="FTS.fuzzy"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.fuzzy">[docs]</a> <span class="k">def</span> <span class="nf">fuzzy</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Fuzzify a data point</span>
|
||||
|
||||
<span class="sd"> :param data: data point</span>
|
||||
<span class="sd"> :return: maximum membership fuzzy set</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">best</span> <span class="o">=</span> <span class="p">{</span><span class="s2">"fuzzyset"</span><span class="p">:</span> <span class="s2">""</span><span class="p">,</span> <span class="s2">"membership"</span><span class="p">:</span> <span class="mf">0.0</span><span class="p">}</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">f</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">:</span>
|
||||
<span class="n">fset</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">f</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="n">best</span><span class="p">[</span><span class="s2">"membership"</span><span class="p">]</span> <span class="o"><=</span> <span class="n">fset</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">data</span><span class="p">):</span>
|
||||
<span class="n">best</span><span class="p">[</span><span class="s2">"fuzzyset"</span><span class="p">]</span> <span class="o">=</span> <span class="n">fset</span><span class="o">.</span><span class="n">name</span>
|
||||
<span class="n">best</span><span class="p">[</span><span class="s2">"membership"</span><span class="p">]</span> <span class="o">=</span> <span class="n">fset</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">best</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FTS.predict"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.predict">[docs]</a> <span class="k">def</span> <span class="nf">predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Forecast using trained model</span>
|
||||
|
||||
<span class="sd"> :param data: time series with minimal length to the order of the model</span>
|
||||
|
||||
<span class="sd"> :keyword type: the forecasting type, one of these values: point(default), interval or distribution.</span>
|
||||
<span class="sd"> :keyword steps_ahead: The forecasting horizon, i. e., the number of steps ahead to forecast</span>
|
||||
<span class="sd"> :keyword start: in the multi step forecasting, the index of the data where to start forecasting</span>
|
||||
<span class="sd"> :keyword distributed: boolean, indicate if the forecasting procedure will be distributed in a dispy cluster</span>
|
||||
<span class="sd"> :keyword nodes: a list with the dispy cluster nodes addresses</span>
|
||||
|
||||
<span class="sd"> :return: a numpy array with the forecasted data</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_multivariate</span><span class="p">:</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">data</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">apply_transformations</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">uod_clip</span><span class="p">:</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">clip</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_min</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_max</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="s1">'distributed'</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
|
||||
<span class="n">distributed</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'distributed'</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">distributed</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">distributed</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">or</span> <span class="n">distributed</span> <span class="o">==</span> <span class="kc">False</span><span class="p">:</span>
|
||||
|
||||
<span class="k">if</span> <span class="s1">'type'</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
|
||||
<span class="nb">type</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s2">"type"</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="nb">type</span> <span class="o">=</span> <span class="s1">'point'</span>
|
||||
|
||||
<span class="n">steps_ahead</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"steps_ahead"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">steps_ahead</span> <span class="o">==</span> <span class="kc">None</span> <span class="ow">or</span> <span class="n">steps_ahead</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="nb">type</span> <span class="o">==</span> <span class="s1">'point'</span><span class="p">:</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="nb">type</span> <span class="o">==</span> <span class="s1">'interval'</span><span class="p">:</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast_interval</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="nb">type</span> <span class="o">==</span> <span class="s1">'distribution'</span><span class="p">:</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast_distribution</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="n">steps_ahead</span> <span class="o">></span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="nb">type</span> <span class="o">==</span> <span class="s1">'point'</span><span class="p">:</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast_ahead</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="n">steps_ahead</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="nb">type</span> <span class="o">==</span> <span class="s1">'interval'</span><span class="p">:</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast_ahead_interval</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="n">steps_ahead</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="nb">type</span> <span class="o">==</span> <span class="s1">'distribution'</span><span class="p">:</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast_ahead_distribution</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="n">steps_ahead</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="ow">not</span> <span class="p">[</span><span class="s1">'point'</span><span class="p">,</span> <span class="s1">'interval'</span><span class="p">,</span> <span class="s1">'distribution'</span><span class="p">]</span><span class="o">.</span><span class="fm">__contains__</span><span class="p">(</span><span class="nb">type</span><span class="p">):</span>
|
||||
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s1">'The argument </span><span class="se">\'</span><span class="s1">type</span><span class="se">\'</span><span class="s1"> has an unknown value.'</span><span class="p">)</span>
|
||||
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
|
||||
<span class="n">nodes</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"nodes"</span><span class="p">,</span> <span class="p">[</span><span class="s1">'127.0.0.1'</span><span class="p">])</span>
|
||||
<span class="n">num_batches</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'num_batches'</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="n">Util</span><span class="o">.</span><span class="n">distributed_predict</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">kwargs</span><span class="p">,</span> <span class="n">nodes</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="n">num_batches</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_multivariate</span><span class="p">:</span>
|
||||
<span class="n">kwargs</span><span class="p">[</span><span class="s1">'type'</span><span class="p">]</span> <span class="o">=</span> <span class="nb">type</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">apply_inverse_transformations</span><span class="p">(</span><span class="n">ret</span><span class="p">,</span> <span class="n">params</span><span class="o">=</span><span class="p">[</span><span class="n">data</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">-</span> <span class="mi">1</span><span class="p">:]],</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FTS.forecast"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Point forecast one step ahead</span>
|
||||
|
||||
<span class="sd"> :param data: time series data with the minimal length equal to the max_lag of the model</span>
|
||||
<span class="sd"> :param kwargs: model specific parameters</span>
|
||||
<span class="sd"> :return: a list with the forecasted values</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="s1">'This model do not perform one step ahead point forecasts!'</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FTS.forecast_interval"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Interval forecast one step ahead</span>
|
||||
|
||||
<span class="sd"> :param data: time series data with the minimal length equal to the max_lag of the model</span>
|
||||
<span class="sd"> :param kwargs: model specific parameters</span>
|
||||
<span class="sd"> :return: a list with the forecasted intervals</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="s1">'This model do not perform one step ahead interval forecasts!'</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FTS.forecast_distribution"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_distribution">[docs]</a> <span class="k">def</span> <span class="nf">forecast_distribution</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Probabilistic forecast one step ahead</span>
|
||||
|
||||
<span class="sd"> :param data: time series data with the minimal length equal to the max_lag of the model</span>
|
||||
<span class="sd"> :param kwargs: model specific parameters</span>
|
||||
<span class="sd"> :return: a list with the forecasted Probability Distributions</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="s1">'This model do not perform one step ahead distribution forecasts!'</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FTS.forecast_ahead"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_ahead">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Point forecast n steps ahead</span>
|
||||
|
||||
<span class="sd"> :param data: time series data with the minimal length equal to the max_lag of the model</span>
|
||||
<span class="sd"> :param steps: the number of steps ahead to forecast</span>
|
||||
<span class="sd"> :param kwargs: model specific parameters</span>
|
||||
<span class="sd"> :return: a list with the forecasted values</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="n">steps</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">:],</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">tmp</span><span class="p">,(</span><span class="nb">list</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">tmp</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="n">data</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FTS.forecast_ahead_interval"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_ahead_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Interval forecast n steps ahead</span>
|
||||
|
||||
<span class="sd"> :param data: time series data with the minimal length equal to the max_lag of the model</span>
|
||||
<span class="sd"> :param steps: the number of steps ahead to forecast</span>
|
||||
<span class="sd"> :param kwargs: model specific parameters</span>
|
||||
<span class="sd"> :return: a list with the forecasted intervals</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="s1">'This model do not perform multi step ahead interval forecasts!'</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FTS.forecast_ahead_distribution"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.forecast_ahead_distribution">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead_distribution</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Probabilistic forecast n steps ahead</span>
|
||||
|
||||
<span class="sd"> :param data: time series data with the minimal length equal to the max_lag of the model</span>
|
||||
<span class="sd"> :param steps: the number of steps ahead to forecast</span>
|
||||
<span class="sd"> :param kwargs: model specific parameters</span>
|
||||
<span class="sd"> :return: a list with the forecasted Probability Distributions</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">(</span><span class="s1">'This model do not perform multi step ahead distribution forecasts!'</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FTS.train"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Method specific parameter fitting</span>
|
||||
|
||||
<span class="sd"> :param data: training time series data</span>
|
||||
<span class="sd"> :param kwargs: Method specific parameters</span>
|
||||
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">pass</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FTS.fit"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.fit">[docs]</a> <span class="k">def</span> <span class="nf">fit</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Fit the model's parameters based on the training data.</span>
|
||||
|
||||
<span class="sd"> :param ndata: training time series data</span>
|
||||
<span class="sd"> :param kwargs:</span>
|
||||
|
||||
<span class="sd"> :keyword num_batches: split the training data in num_batches to save memory during the training process</span>
|
||||
<span class="sd"> :keyword save_model: save final model on disk</span>
|
||||
<span class="sd"> :keyword batch_save: save the model between each batch</span>
|
||||
<span class="sd"> :keyword file_path: path to save the model</span>
|
||||
<span class="sd"> :keyword distributed: boolean, indicate if the training procedure will be distributed in a dispy cluster</span>
|
||||
<span class="sd"> :keyword nodes: a list with the dispy cluster nodes addresses</span>
|
||||
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">datetime</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_multivariate</span><span class="p">:</span>
|
||||
<span class="n">data</span> <span class="o">=</span> <span class="n">ndata</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">data</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">apply_transformations</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">original_min</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmin</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">original_max</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmax</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="s1">'sets'</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'sets'</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="s1">'partitioner'</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'partitioner'</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">or</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">)</span> <span class="ow">and</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">benchmark_only</span> <span class="ow">and</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_multivariate</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">"Fuzzy sets were not provided for the model. Use 'sets' parameter or 'partitioner'. "</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="s1">'order'</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'order'</span><span class="p">)</span>
|
||||
|
||||
<span class="n">dump</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'dump'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="n">num_batches</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'num_batches'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="n">save</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'save_model'</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span> <span class="c1"># save model on disk</span>
|
||||
|
||||
<span class="n">batch_save</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'batch_save'</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span> <span class="c1">#save model between batches</span>
|
||||
|
||||
<span class="n">file_path</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'file_path'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="n">distributed</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'distributed'</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span>
|
||||
|
||||
<span class="n">batch_save_interval</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'batch_save_interval'</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">distributed</span><span class="p">:</span>
|
||||
<span class="n">nodes</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'nodes'</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span>
|
||||
<span class="n">train_method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'train_method'</span><span class="p">,</span> <span class="n">Util</span><span class="o">.</span><span class="n">simple_model_train</span><span class="p">)</span>
|
||||
<span class="n">Util</span><span class="o">.</span><span class="n">distributed_train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">train_method</span><span class="p">,</span> <span class="n">nodes</span><span class="p">,</span> <span class="nb">type</span><span class="p">(</span><span class="bp">self</span><span class="p">),</span> <span class="n">data</span><span class="p">,</span> <span class="n">num_batches</span><span class="p">,</span> <span class="p">{},</span>
|
||||
<span class="n">batch_save</span><span class="o">=</span><span class="n">batch_save</span><span class="p">,</span> <span class="n">file_path</span><span class="o">=</span><span class="n">file_path</span><span class="p">,</span>
|
||||
<span class="n">batch_save_interval</span><span class="o">=</span><span class="n">batch_save_interval</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">dump</span> <span class="o">==</span> <span class="s1">'time'</span><span class="p">:</span>
|
||||
<span class="nb">print</span><span class="p">(</span><span class="s2">"[{0: %H:%M:%S}] Start training"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">()))</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">num_batches</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">n</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">batch_size</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">n</span> <span class="o">/</span> <span class="n">num_batches</span><span class="p">)</span>
|
||||
<span class="n">bcount</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
|
||||
<span class="n">rng</span> <span class="o">=</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">dump</span> <span class="o">==</span> <span class="s1">'tqdm'</span><span class="p">:</span>
|
||||
<span class="kn">from</span> <span class="nn">tqdm</span> <span class="k">import</span> <span class="n">tqdm</span>
|
||||
|
||||
<span class="n">rng</span> <span class="o">=</span> <span class="n">tqdm</span><span class="p">(</span><span class="n">rng</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">ct</span> <span class="ow">in</span> <span class="n">rng</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">dump</span> <span class="o">==</span> <span class="s1">'time'</span><span class="p">:</span>
|
||||
<span class="nb">print</span><span class="p">(</span><span class="s2">"[{0: %H:%M:%S}] Starting batch "</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">())</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">bcount</span><span class="p">))</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">is_multivariate</span><span class="p">:</span>
|
||||
<span class="n">mdata</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">ct</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">:</span><span class="n">ct</span> <span class="o">+</span> <span class="n">batch_size</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">mdata</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">ct</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="p">:</span> <span class="n">ct</span> <span class="o">+</span> <span class="n">batch_size</span><span class="p">]</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="n">mdata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">batch_save</span><span class="p">:</span>
|
||||
<span class="n">Util</span><span class="o">.</span><span class="n">persist_obj</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">file_path</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">dump</span> <span class="o">==</span> <span class="s1">'time'</span><span class="p">:</span>
|
||||
<span class="nb">print</span><span class="p">(</span><span class="s2">"[{0: %H:%M:%S}] Finish batch "</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">())</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">bcount</span><span class="p">))</span>
|
||||
|
||||
<span class="n">bcount</span> <span class="o">+=</span> <span class="mi">1</span>
|
||||
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">dump</span> <span class="o">==</span> <span class="s1">'time'</span><span class="p">:</span>
|
||||
<span class="nb">print</span><span class="p">(</span><span class="s2">"[{0: %H:%M:%S}] Finish training"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">()))</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">save</span><span class="p">:</span>
|
||||
<span class="n">Util</span><span class="o">.</span><span class="n">persist_obj</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">file_path</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FTS.clone_parameters"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.clone_parameters">[docs]</a> <span class="k">def</span> <span class="nf">clone_parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">model</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Import the parameters values from other model</span>
|
||||
|
||||
<span class="sd"> :param model:</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">order</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">shortname</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">name</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">detail</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">is_high_order</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_order</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">min_order</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_seasonality</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">has_seasonality</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_point_forecasting</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">has_point_forecasting</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_interval_forecasting</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">has_interval_forecasting</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_probability_forecasting</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">has_probability_forecasting</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_multivariate</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">is_multivariate</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">dump</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">dump</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">transformations</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">transformations</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">transformations_param</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">transformations_param</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">original_max</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">original_max</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">original_min</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">original_min</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">partitioner</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">sets</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">auto_update</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">auto_update</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">benchmark_only</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">benchmark_only</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">indexer</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">indexer</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FTS.merge"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.merge">[docs]</a> <span class="k">def</span> <span class="nf">merge</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">model</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Merge the FLRG rules from other model</span>
|
||||
|
||||
<span class="sd"> :param model: source model</span>
|
||||
<span class="sd"> :return:</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">key</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span> <span class="o">=</span> <span class="n">flrg</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">RHS</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="nb">set</span><span class="p">)):</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">flrg</span><span class="o">.</span><span class="n">RHS</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">RHS</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">flrg</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">k</span><span class="p">])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FTS.append_transformation"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.append_transformation">[docs]</a> <span class="k">def</span> <span class="nf">append_transformation</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">transformation</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">transformation</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">transformations</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">transformation</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FTS.apply_transformations"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.apply_transformations">[docs]</a> <span class="k">def</span> <span class="nf">apply_transformations</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">params</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">updateUoD</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Apply the data transformations for data preprocessing</span>
|
||||
|
||||
<span class="sd"> :param data: input data</span>
|
||||
<span class="sd"> :param params: transformation parameters</span>
|
||||
<span class="sd"> :param updateUoD:</span>
|
||||
<span class="sd"> :param kwargs:</span>
|
||||
<span class="sd"> :return: preprocessed data</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">data</span>
|
||||
<span class="k">if</span> <span class="n">updateUoD</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="nb">min</span><span class="p">(</span><span class="n">data</span><span class="p">)</span> <span class="o"><</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">original_min</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">data</span><span class="p">)</span> <span class="o">*</span> <span class="mf">1.1</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">original_min</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">data</span><span class="p">)</span> <span class="o">*</span> <span class="mf">0.9</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">max</span><span class="p">(</span><span class="n">data</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">original_max</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">data</span><span class="p">)</span> <span class="o">*</span> <span class="mf">1.1</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">original_max</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">data</span><span class="p">)</span> <span class="o">*</span> <span class="mf">0.9</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">transformations</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">params</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">params</span> <span class="o">=</span> <span class="p">[</span> <span class="kc">None</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">transformations</span><span class="p">]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">c</span><span class="p">,</span> <span class="n">t</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">transformations</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">t</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span><span class="n">params</span><span class="p">[</span><span class="n">c</span><span class="p">])</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ndata</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FTS.apply_inverse_transformations"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.apply_inverse_transformations">[docs]</a> <span class="k">def</span> <span class="nf">apply_inverse_transformations</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">params</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Apply the data transformations for data postprocessing</span>
|
||||
|
||||
<span class="sd"> :param data: input data</span>
|
||||
<span class="sd"> :param params: transformation parameters</span>
|
||||
<span class="sd"> :param updateUoD:</span>
|
||||
<span class="sd"> :param kwargs:</span>
|
||||
<span class="sd"> :return: postprocessed data</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">transformations</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">params</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">params</span> <span class="o">=</span> <span class="p">[</span><span class="kc">None</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">transformations</span><span class="p">]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">c</span><span class="p">,</span> <span class="n">t</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="nb">reversed</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">transformations</span><span class="p">),</span> <span class="n">start</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">t</span><span class="o">.</span><span class="n">inverse</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">params</span><span class="p">[</span><span class="n">c</span><span class="p">],</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ndata</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">data</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FTS.get_UoD"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.get_UoD">[docs]</a> <span class="k">def</span> <span class="nf">get_UoD</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">original_min</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_max</span><span class="p">]</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="sd">"""String representation of the model"""</span>
|
||||
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">+</span> <span class="s2">":</span><span class="se">\n</span><span class="s2">"</span>
|
||||
<span class="k">for</span> <span class="n">r</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">key</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">tmp</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">r</span><span class="p">])</span> <span class="o">+</span> <span class="s2">"</span><span class="se">\n</span><span class="s2">"</span>
|
||||
<span class="k">return</span> <span class="n">tmp</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> The length (number of rules) of the model</span>
|
||||
|
||||
<span class="sd"> :return: number of rules</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="FTS.len_total"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.fts.FTS.len_total">[docs]</a> <span class="k">def</span> <span class="nf">len_total</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">sum</span><span class="p">([</span><span class="nb">len</span><span class="p">(</span><span class="n">k</span><span class="p">)</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">])</span></div></div>
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
|
||||
<div class="sphinxsidebarwrapper"><div class="relations">
|
||||
<h3>Related Topics</h3>
|
||||
<ul>
|
||||
<li><a href="../../../index.html">Documentation overview</a><ul>
|
||||
<li><a href="../../index.html">Module code</a><ul>
|
||||
</ul></li>
|
||||
</ul></li>
|
||||
</ul>
|
||||
</div>
|
||||
<div id="searchbox" style="display: none" role="search">
|
||||
<h3>Quick search</h3>
|
||||
<div class="searchformwrapper">
|
||||
<form class="search" action="../../../search.html" method="get">
|
||||
<input type="text" name="q" />
|
||||
<input type="submit" value="Go" />
|
||||
<input type="hidden" name="check_keywords" value="yes" />
|
||||
<input type="hidden" name="area" value="default" />
|
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</form>
|
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</div>
|
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</div>
|
||||
<script type="text/javascript">$('#searchbox').show(0);</script>
|
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</div>
|
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</div>
|
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<div class="clearer"></div>
|
||||
</div>
|
||||
<div class="footer">
|
||||
©2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
|
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|
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|
|
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Powered by <a href="http://sphinx-doc.org/">Sphinx 1.7.2</a>
|
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& <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.10</a>
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|
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</div>
|
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|
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|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
151
docs/_build/html/_modules/pyFTS/common/tree.html
vendored
Normal file
151
docs/_build/html/_modules/pyFTS/common/tree.html
vendored
Normal file
@ -0,0 +1,151 @@
|
||||
|
||||
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
|
||||
"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
|
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|
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<html xmlns="http://www.w3.org/1999/xhtml">
|
||||
<head>
|
||||
<meta http-equiv="X-UA-Compatible" content="IE=Edge" />
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<title>pyFTS.common.tree — pyFTS 1.2.3 documentation</title>
|
||||
<link rel="stylesheet" href="../../../_static/alabaster.css" type="text/css" />
|
||||
<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
|
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<script type="text/javascript" src="../../../_static/documentation_options.js"></script>
|
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<script type="text/javascript" src="../../../_static/jquery.js"></script>
|
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<script type="text/javascript" src="../../../_static/underscore.js"></script>
|
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<script type="text/javascript" src="../../../_static/doctools.js"></script>
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<script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script>
|
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<link rel="index" title="Index" href="../../../genindex.html" />
|
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<link rel="search" title="Search" href="../../../search.html" />
|
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|
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<link rel="stylesheet" href="../../../_static/custom.css" type="text/css" />
|
||||
|
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|
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<meta name="viewport" content="width=device-width, initial-scale=0.9, maximum-scale=0.9" />
|
||||
|
||||
</head><body>
|
||||
|
||||
|
||||
<div class="document">
|
||||
<div class="documentwrapper">
|
||||
<div class="bodywrapper">
|
||||
<div class="body" role="main">
|
||||
|
||||
<h1>Source code for pyFTS.common.tree</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">Tree data structure</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="k">import</span> <span class="o">*</span>
|
||||
<span class="kn">from</span> <span class="nn">functools</span> <span class="k">import</span> <span class="n">reduce</span>
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="FLRGTreeNode"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.tree.FLRGTreeNode">[docs]</a><span class="k">class</span> <span class="nc">FLRGTreeNode</span><span class="p">:</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Tree node for</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">isRoot</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">children</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">value</span> <span class="o">=</span> <span class="n">value</span>
|
||||
|
||||
<div class="viewcode-block" id="FLRGTreeNode.appendChild"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.tree.FLRGTreeNode.appendChild">[docs]</a> <span class="k">def</span> <span class="nf">appendChild</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">child</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">children</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">child</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FLRGTreeNode.getChildren"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.tree.FLRGTreeNode.getChildren">[docs]</a> <span class="k">def</span> <span class="nf">getChildren</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">child</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">children</span><span class="p">:</span>
|
||||
<span class="k">yield</span> <span class="n">child</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FLRGTreeNode.paths"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.tree.FLRGTreeNode.paths">[docs]</a> <span class="k">def</span> <span class="nf">paths</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">acc</span><span class="o">=</span><span class="p">[]):</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">children</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="k">yield</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">]</span> <span class="o">+</span> <span class="n">acc</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">child</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">children</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">leaf_path</span> <span class="ow">in</span> <span class="n">child</span><span class="o">.</span><span class="n">paths</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">]</span> <span class="o">+</span> <span class="n">acc</span><span class="p">):</span> <span class="c1"># these two</span>
|
||||
<span class="k">yield</span> <span class="n">leaf_path</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FLRGTreeNode.getStr"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.tree.FLRGTreeNode.getStr">[docs]</a> <span class="k">def</span> <span class="nf">getStr</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">isRoot</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="s2">"</span><span class="se">\\</span><span class="s2">"</span> <span class="o">+</span> <span class="p">(</span><span class="s2">"-"</span> <span class="o">*</span> <span class="n">k</span><span class="p">)</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">value</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">child</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">getChildren</span><span class="p">():</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">tmp</span> <span class="o">+</span> <span class="s2">"</span><span class="se">\n</span><span class="s2">"</span> <span class="o">+</span> <span class="n">child</span><span class="o">.</span><span class="n">getStr</span><span class="p">(</span><span class="n">k</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">tmp</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">getStr</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="FLRGTree"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.tree.FLRGTree">[docs]</a><span class="k">class</span> <span class="nc">FLRGTree</span><span class="p">:</span>
|
||||
<span class="sd">"""Represents a FLRG set with a tree structure"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">root</span> <span class="o">=</span> <span class="n">FLRGTreeNode</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="flat"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.tree.flat">[docs]</a><span class="k">def</span> <span class="nf">flat</span><span class="p">(</span><span class="n">dados</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">inst</span> <span class="ow">in</span> <span class="n">dados</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">)):</span>
|
||||
<span class="n">x</span> <span class="o">=</span> <span class="n">flat</span><span class="p">(</span><span class="n">inst</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">x</span><span class="p">:</span>
|
||||
<span class="k">yield</span> <span class="n">k</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">yield</span> <span class="n">inst</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="build_tree_without_order"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.tree.build_tree_without_order">[docs]</a><span class="k">def</span> <span class="nf">build_tree_without_order</span><span class="p">(</span><span class="n">node</span><span class="p">,</span> <span class="n">lags</span><span class="p">,</span> <span class="n">level</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">level</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">lags</span><span class="p">:</span>
|
||||
<span class="k">return</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">lags</span><span class="p">[</span><span class="n">level</span><span class="p">]:</span>
|
||||
<span class="n">node</span><span class="o">.</span><span class="n">appendChild</span><span class="p">(</span><span class="n">FLRGTreeNode</span><span class="p">(</span><span class="n">s</span><span class="p">))</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">child</span> <span class="ow">in</span> <span class="n">node</span><span class="o">.</span><span class="n">getChildren</span><span class="p">():</span>
|
||||
<span class="n">build_tree_without_order</span><span class="p">(</span><span class="n">child</span><span class="p">,</span> <span class="n">lags</span><span class="p">,</span> <span class="n">level</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span></div>
|
||||
</pre></div>
|
||||
|
||||
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|
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|
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|
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|
||||
104
docs/_build/html/_modules/pyFTS/data/AirPassengers.html
vendored
Normal file
104
docs/_build/html/_modules/pyFTS/data/AirPassengers.html
vendored
Normal file
@ -0,0 +1,104 @@
|
||||
|
||||
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
|
||||
"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
|
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<meta http-equiv="X-UA-Compatible" content="IE=Edge" />
|
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<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
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<title>pyFTS.data.AirPassengers — pyFTS 1.2.3 documentation</title>
|
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|
||||
<div class="bodywrapper">
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||||
<div class="body" role="main">
|
||||
|
||||
<h1>Source code for pyFTS.data.AirPassengers</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.AirPassengers.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">():</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Get a simple univariate time series data.</span>
|
||||
|
||||
<span class="sd"> :return: numpy array</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">get_dataframe</span><span class="p">()</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="s2">"Passengers"</span><span class="p">])</span>
|
||||
<span class="k">return</span> <span class="n">dat</span></div>
|
||||
|
||||
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.AirPassengers.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Get the complete multivariate time series data.</span>
|
||||
|
||||
<span class="sd"> :return: Pandas DataFrame</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">get_dataframe</span><span class="p">(</span><span class="s1">'AirPassengers.csv'</span><span class="p">,</span>
|
||||
<span class="s1">'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/AirPassengers.csv'</span><span class="p">,</span>
|
||||
<span class="n">sep</span><span class="o">=</span><span class="s2">","</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">dat</span></div>
|
||||
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
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|
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|
||||
<h3>Related Topics</h3>
|
||||
<ul>
|
||||
<li><a href="../../../index.html">Documentation overview</a><ul>
|
||||
<li><a href="../../index.html">Module code</a><ul>
|
||||
</ul></li>
|
||||
</ul></li>
|
||||
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|
||||
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|
||||
<div id="searchbox" style="display: none" role="search">
|
||||
<h3>Quick search</h3>
|
||||
<div class="searchformwrapper">
|
||||
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|
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||||
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|
||||
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|
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<script type="text/javascript">$('#searchbox').show(0);</script>
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|
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|
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|
||||
|
|
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|
||||
|
||||
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
99
docs/_build/html/_modules/pyFTS/data/Enrollments.html
vendored
Normal file
99
docs/_build/html/_modules/pyFTS/data/Enrollments.html
vendored
Normal file
@ -0,0 +1,99 @@
|
||||
|
||||
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
|
||||
"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
|
||||
|
||||
<html xmlns="http://www.w3.org/1999/xhtml">
|
||||
<head>
|
||||
<meta http-equiv="X-UA-Compatible" content="IE=Edge" />
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<title>pyFTS.data.Enrollments — pyFTS 1.2.3 documentation</title>
|
||||
<link rel="stylesheet" href="../../../_static/alabaster.css" type="text/css" />
|
||||
<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
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|
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<script type="text/javascript" src="../../../_static/jquery.js"></script>
|
||||
<script type="text/javascript" src="../../../_static/underscore.js"></script>
|
||||
<script type="text/javascript" src="../../../_static/doctools.js"></script>
|
||||
<script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script>
|
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<link rel="index" title="Index" href="../../../genindex.html" />
|
||||
<link rel="search" title="Search" href="../../../search.html" />
|
||||
|
||||
<link rel="stylesheet" href="../../../_static/custom.css" type="text/css" />
|
||||
|
||||
|
||||
<meta name="viewport" content="width=device-width, initial-scale=0.9, maximum-scale=0.9" />
|
||||
|
||||
</head><body>
|
||||
|
||||
|
||||
<div class="document">
|
||||
<div class="documentwrapper">
|
||||
<div class="bodywrapper">
|
||||
<div class="body" role="main">
|
||||
|
||||
<h1>Source code for pyFTS.data.Enrollments</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Enrollments.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">():</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Get a simple univariate time series data.</span>
|
||||
|
||||
<span class="sd"> :return: numpy array</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">get_dataframe</span><span class="p">()</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="s2">"Enrollments"</span><span class="p">])</span>
|
||||
<span class="k">return</span> <span class="n">dat</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Enrollments.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">get_dataframe</span><span class="p">(</span><span class="s1">'Enrollments.csv'</span><span class="p">,</span>
|
||||
<span class="s1">'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/Enrollments.csv'</span><span class="p">,</span>
|
||||
<span class="n">sep</span><span class="o">=</span><span class="s2">";"</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">dat</span></div>
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
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|
||||
<div class="sphinxsidebarwrapper"><div class="relations">
|
||||
<h3>Related Topics</h3>
|
||||
<ul>
|
||||
<li><a href="../../../index.html">Documentation overview</a><ul>
|
||||
<li><a href="../../index.html">Module code</a><ul>
|
||||
</ul></li>
|
||||
</ul></li>
|
||||
</ul>
|
||||
</div>
|
||||
<div id="searchbox" style="display: none" role="search">
|
||||
<h3>Quick search</h3>
|
||||
<div class="searchformwrapper">
|
||||
<form class="search" action="../../../search.html" method="get">
|
||||
<input type="text" name="q" />
|
||||
<input type="submit" value="Go" />
|
||||
<input type="hidden" name="check_keywords" value="yes" />
|
||||
<input type="hidden" name="area" value="default" />
|
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|
||||
</div>
|
||||
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|
||||
<script type="text/javascript">$('#searchbox').show(0);</script>
|
||||
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|
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|
||||
<div class="clearer"></div>
|
||||
</div>
|
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<div class="footer">
|
||||
©2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
|
||||
|
||||
|
|
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Powered by <a href="http://sphinx-doc.org/">Sphinx 1.7.2</a>
|
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& <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.10</a>
|
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|
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</div>
|
||||
|
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|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
101
docs/_build/html/_modules/pyFTS/data/INMET.html
vendored
Normal file
101
docs/_build/html/_modules/pyFTS/data/INMET.html
vendored
Normal file
@ -0,0 +1,101 @@
|
||||
|
||||
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
|
||||
"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
|
||||
|
||||
<html xmlns="http://www.w3.org/1999/xhtml">
|
||||
<head>
|
||||
<meta http-equiv="X-UA-Compatible" content="IE=Edge" />
|
||||
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<title>pyFTS.data.INMET — pyFTS 1.2.3 documentation</title>
|
||||
<link rel="stylesheet" href="../../../_static/alabaster.css" type="text/css" />
|
||||
<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
|
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<script type="text/javascript" src="../../../_static/documentation_options.js"></script>
|
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<script type="text/javascript" src="../../../_static/jquery.js"></script>
|
||||
<script type="text/javascript" src="../../../_static/underscore.js"></script>
|
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<script type="text/javascript" src="../../../_static/doctools.js"></script>
|
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<script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script>
|
||||
<link rel="index" title="Index" href="../../../genindex.html" />
|
||||
<link rel="search" title="Search" href="../../../search.html" />
|
||||
|
||||
<link rel="stylesheet" href="../../../_static/custom.css" type="text/css" />
|
||||
|
||||
|
||||
<meta name="viewport" content="width=device-width, initial-scale=0.9, maximum-scale=0.9" />
|
||||
|
||||
</head><body>
|
||||
|
||||
|
||||
<div class="document">
|
||||
<div class="documentwrapper">
|
||||
<div class="bodywrapper">
|
||||
<div class="body" role="main">
|
||||
|
||||
<h1>Source code for pyFTS.data.INMET</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">INMET - Instituto Nacional Meteorologia / Brasil</span>
|
||||
|
||||
<span class="sd">Belo Horizonte station, from 2000-01-01 to 31/12/2012</span>
|
||||
|
||||
<span class="sd">Source: http://www.inmet.gov.br</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.INMET.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Get the complete multivariate time series data.</span>
|
||||
|
||||
<span class="sd"> :return: Pandas DataFrame</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">get_dataframe</span><span class="p">(</span><span class="s1">'INMET.csv.bz2'</span><span class="p">,</span>
|
||||
<span class="s1">'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/INMET.csv.bz2'</span><span class="p">,</span>
|
||||
<span class="n">sep</span><span class="o">=</span><span class="s2">";"</span><span class="p">,</span> <span class="n">compression</span><span class="o">=</span><span class="s1">'bz2'</span><span class="p">)</span>
|
||||
<span class="n">dat</span><span class="p">[</span><span class="s2">"DataHora"</span><span class="p">]</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="s2">"DataHora"</span><span class="p">],</span> <span class="nb">format</span><span class="o">=</span><span class="s1">'</span><span class="si">%d</span><span class="s1">/%m/%Y %H:%M'</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">dat</span></div>
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
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|
||||
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|
||||
<h3>Related Topics</h3>
|
||||
<ul>
|
||||
<li><a href="../../../index.html">Documentation overview</a><ul>
|
||||
<li><a href="../../index.html">Module code</a><ul>
|
||||
</ul></li>
|
||||
</ul></li>
|
||||
</ul>
|
||||
</div>
|
||||
<div id="searchbox" style="display: none" role="search">
|
||||
<h3>Quick search</h3>
|
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Powered by <a href="http://sphinx-doc.org/">Sphinx 1.7.2</a>
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106
docs/_build/html/_modules/pyFTS/data/NASDAQ.html
vendored
Normal file
106
docs/_build/html/_modules/pyFTS/data/NASDAQ.html
vendored
Normal file
@ -0,0 +1,106 @@
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
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<h1>Source code for pyFTS.data.NASDAQ</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.NASDAQ.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="o">=</span><span class="s2">"avg"</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Get a simple univariate time series data.</span>
|
||||
|
||||
<span class="sd"> :param field: the dataset field name to extract</span>
|
||||
<span class="sd"> :return: numpy array</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">get_dataframe</span><span class="p">()</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="n">field</span><span class="p">])</span>
|
||||
<span class="k">return</span> <span class="n">dat</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.NASDAQ.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Get the complete multivariate time series data.</span>
|
||||
|
||||
<span class="sd"> :return: Pandas DataFrame</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">get_dataframe</span><span class="p">(</span><span class="s1">'NASDAQ.csv.bz2'</span><span class="p">,</span>
|
||||
<span class="s1">'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/NASDAQ.csv.bz2'</span><span class="p">,</span>
|
||||
<span class="n">sep</span><span class="o">=</span><span class="s2">","</span><span class="p">,</span> <span class="n">compression</span><span class="o">=</span><span class="s1">'bz2'</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">dat</span></div>
|
||||
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
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|
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|
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|
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|
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|
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<li><a href="../../index.html">Module code</a><ul>
|
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|
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|
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|
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|
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©2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
|
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Powered by <a href="http://sphinx-doc.org/">Sphinx 1.7.2</a>
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|
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|
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|
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|
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|
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</html>
|
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115
docs/_build/html/_modules/pyFTS/data/SONDA.html
vendored
Normal file
115
docs/_build/html/_modules/pyFTS/data/SONDA.html
vendored
Normal file
@ -0,0 +1,115 @@
|
||||
|
||||
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
|
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"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
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|
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<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
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<title>pyFTS.data.SONDA — pyFTS 1.2.3 documentation</title>
|
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<h1>Source code for pyFTS.data.SONDA</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">SONDA - Sistema de Organização Nacional de Dados Ambientais, from INPE - Instituto Nacional de Pesquisas Espaciais, Brasil.</span>
|
||||
|
||||
<span class="sd">Brasilia station</span>
|
||||
|
||||
<span class="sd">Source: http://sonda.ccst.inpe.br/</span>
|
||||
|
||||
<span class="sd">"""</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.SONDA.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">field</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Get a simple univariate time series data.</span>
|
||||
|
||||
<span class="sd"> :param field: the dataset field name to extract</span>
|
||||
<span class="sd"> :return: numpy array</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">get_dataframe</span><span class="p">()</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="n">field</span><span class="p">])</span>
|
||||
<span class="k">return</span> <span class="n">dat</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.SONDA.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Get the complete multivariate time series data.</span>
|
||||
|
||||
<span class="sd"> :return: Pandas DataFrame</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">get_dataframe</span><span class="p">(</span><span class="s1">'SONDA_BSB.csv.bz2'</span><span class="p">,</span>
|
||||
<span class="s1">'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/SONDA_BSB.csv.bz2'</span><span class="p">,</span>
|
||||
<span class="n">sep</span><span class="o">=</span><span class="s2">";"</span><span class="p">,</span> <span class="n">compression</span><span class="o">=</span><span class="s1">'bz2'</span><span class="p">)</span>
|
||||
<span class="n">dat</span><span class="p">[</span><span class="s2">"datahora"</span><span class="p">]</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="s2">"datahora"</span><span class="p">],</span> <span class="nb">format</span><span class="o">=</span><span class="s1">'%Y-%m-</span><span class="si">%d</span><span class="s1"> %H:%M:%S'</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">dat</span></div>
|
||||
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
|
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<div class="sphinxsidebarwrapper"><div class="relations">
|
||||
<h3>Related Topics</h3>
|
||||
<ul>
|
||||
<li><a href="../../../index.html">Documentation overview</a><ul>
|
||||
<li><a href="../../index.html">Module code</a><ul>
|
||||
</ul></li>
|
||||
</ul></li>
|
||||
</ul>
|
||||
</div>
|
||||
<div id="searchbox" style="display: none" role="search">
|
||||
<h3>Quick search</h3>
|
||||
<div class="searchformwrapper">
|
||||
<form class="search" action="../../../search.html" method="get">
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<input type="text" name="q" />
|
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<input type="submit" value="Go" />
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<script type="text/javascript">$('#searchbox').show(0);</script>
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|
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|
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|
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<div class="footer">
|
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©2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
|
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|
||||
|
|
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Powered by <a href="http://sphinx-doc.org/">Sphinx 1.7.2</a>
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& <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.10</a>
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</div>
|
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|
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|
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|
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|
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</body>
|
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</html>
|
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104
docs/_build/html/_modules/pyFTS/data/SP500.html
vendored
Normal file
104
docs/_build/html/_modules/pyFTS/data/SP500.html
vendored
Normal file
@ -0,0 +1,104 @@
|
||||
|
||||
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
|
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"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
|
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<html xmlns="http://www.w3.org/1999/xhtml">
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<head>
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<meta http-equiv="X-UA-Compatible" content="IE=Edge" />
|
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<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
||||
<title>pyFTS.data.SP500 — pyFTS 1.2.3 documentation</title>
|
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<link rel="stylesheet" href="../../../_static/alabaster.css" type="text/css" />
|
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<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
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<script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script>
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<link rel="search" title="Search" href="../../../search.html" />
|
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<link rel="stylesheet" href="../../../_static/custom.css" type="text/css" />
|
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|
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|
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<meta name="viewport" content="width=device-width, initial-scale=0.9, maximum-scale=0.9" />
|
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|
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</head><body>
|
||||
|
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|
||||
<div class="document">
|
||||
<div class="documentwrapper">
|
||||
<div class="bodywrapper">
|
||||
<div class="body" role="main">
|
||||
|
||||
<h1>Source code for pyFTS.data.SP500</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.SP500.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">():</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Get the univariate time series data.</span>
|
||||
|
||||
<span class="sd"> :return: numpy array</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">get_dataframe</span><span class="p">()</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="s2">"Avg"</span><span class="p">])</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.SP500.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Get the complete multivariate time series data.</span>
|
||||
|
||||
<span class="sd"> :return: Pandas DataFrame</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">get_dataframe</span><span class="p">(</span><span class="s1">'SP500.csv.bz2'</span><span class="p">,</span>
|
||||
<span class="s1">'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/SP500.csv.bz2'</span><span class="p">,</span>
|
||||
<span class="n">sep</span><span class="o">=</span><span class="s2">","</span><span class="p">,</span> <span class="n">compression</span><span class="o">=</span><span class="s1">'bz2'</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">dat</span></div>
|
||||
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
|
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<div class="sphinxsidebarwrapper"><div class="relations">
|
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<h3>Related Topics</h3>
|
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<ul>
|
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106
docs/_build/html/_modules/pyFTS/data/TAIEX.html
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106
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<h1>Source code for pyFTS.data.TAIEX</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.TAIEX.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">():</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Get the univariate time series data.</span>
|
||||
|
||||
<span class="sd"> :return: numpy array</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">get_dataframe</span><span class="p">()</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="s2">"avg"</span><span class="p">])</span>
|
||||
<span class="k">return</span> <span class="n">dat</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.TAIEX.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Get the complete multivariate time series data.</span>
|
||||
|
||||
<span class="sd"> :return: Pandas DataFrame</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">get_dataframe</span><span class="p">(</span><span class="s1">'TAIEX.csv.bz2'</span><span class="p">,</span>
|
||||
<span class="s1">'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/TAIEX.csv.bz2'</span><span class="p">,</span>
|
||||
<span class="n">sep</span><span class="o">=</span><span class="s2">","</span><span class="p">,</span> <span class="n">compression</span><span class="o">=</span><span class="s1">'bz2'</span><span class="p">)</span>
|
||||
<span class="n">dat</span><span class="p">[</span><span class="s2">"Date"</span><span class="p">]</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">to_datetime</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="s2">"Date"</span><span class="p">])</span>
|
||||
<span class="k">return</span> <span class="n">dat</span></div>
|
||||
|
||||
</pre></div>
|
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|
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|
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|
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<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
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<div class="sphinxsidebarwrapper"><div class="relations">
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<h3>Related Topics</h3>
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<li><a href="../../../index.html">Documentation overview</a><ul>
|
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158
docs/_build/html/_modules/pyFTS/data/artificial.html
vendored
Normal file
158
docs/_build/html/_modules/pyFTS/data/artificial.html
vendored
Normal file
@ -0,0 +1,158 @@
|
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|
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
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|
||||
<h1>Source code for pyFTS.data.artificial</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">Facilities to generate synthetic stochastic processes</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="generate_gaussian_linear"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.artificial.generate_gaussian_linear">[docs]</a><span class="k">def</span> <span class="nf">generate_gaussian_linear</span><span class="p">(</span><span class="n">mu_ini</span><span class="p">,</span> <span class="n">sigma_ini</span><span class="p">,</span> <span class="n">mu_inc</span><span class="p">,</span> <span class="n">sigma_inc</span><span class="p">,</span> <span class="n">it</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">num</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">vmin</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">vmax</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Generate data sampled from Gaussian distribution, with constant or linear changing parameters</span>
|
||||
|
||||
<span class="sd"> :param mu_ini: Initial mean</span>
|
||||
<span class="sd"> :param sigma_ini: Initial variance</span>
|
||||
<span class="sd"> :param mu_inc: Mean increment after 'num' samples</span>
|
||||
<span class="sd"> :param sigma_inc: Variance increment after 'num' samples</span>
|
||||
<span class="sd"> :param it: Number of iterations</span>
|
||||
<span class="sd"> :param num: Number of samples generated on each iteration</span>
|
||||
<span class="sd"> :param vmin: Lower bound value of generated data</span>
|
||||
<span class="sd"> :param vmax: Upper bound value of generated data</span>
|
||||
<span class="sd"> :return: A list of it*num float values</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">mu</span> <span class="o">=</span> <span class="n">mu_ini</span>
|
||||
<span class="n">sigma</span> <span class="o">=</span> <span class="n">sigma_ini</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="n">it</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">normal</span><span class="p">(</span><span class="n">mu</span><span class="p">,</span> <span class="n">sigma</span><span class="p">,</span> <span class="n">num</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">vmin</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">maximum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">full</span><span class="p">(</span><span class="n">num</span><span class="p">,</span> <span class="n">vmin</span><span class="p">),</span> <span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">vmax</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">minimum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">full</span><span class="p">(</span><span class="n">num</span><span class="p">,</span> <span class="n">vmax</span><span class="p">),</span> <span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="n">mu</span> <span class="o">+=</span> <span class="n">mu_inc</span>
|
||||
<span class="n">sigma</span> <span class="o">+=</span> <span class="n">sigma_inc</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="generate_uniform_linear"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.artificial.generate_uniform_linear">[docs]</a><span class="k">def</span> <span class="nf">generate_uniform_linear</span><span class="p">(</span><span class="n">min_ini</span><span class="p">,</span> <span class="n">max_ini</span><span class="p">,</span> <span class="n">min_inc</span><span class="p">,</span> <span class="n">max_inc</span><span class="p">,</span> <span class="n">it</span><span class="o">=</span><span class="mi">100</span><span class="p">,</span> <span class="n">num</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">vmin</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">vmax</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Generate data sampled from Uniform distribution, with constant or linear changing bounds</span>
|
||||
|
||||
<span class="sd"> :param mu_ini: Initial mean</span>
|
||||
<span class="sd"> :param sigma_ini: Initial variance</span>
|
||||
<span class="sd"> :param mu_inc: Mean increment after 'num' samples</span>
|
||||
<span class="sd"> :param sigma_inc: Variance increment after 'num' samples</span>
|
||||
<span class="sd"> :param it: Number of iterations</span>
|
||||
<span class="sd"> :param num: Number of samples generated on each iteration</span>
|
||||
<span class="sd"> :param vmin: Lower bound value of generated data</span>
|
||||
<span class="sd"> :param vmax: Upper bound value of generated data</span>
|
||||
<span class="sd"> :return: A list of it*num float values</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">_min</span> <span class="o">=</span> <span class="n">min_ini</span>
|
||||
<span class="n">_max</span> <span class="o">=</span> <span class="n">max_ini</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="n">it</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">uniform</span><span class="p">(</span><span class="n">_min</span><span class="p">,</span> <span class="n">_max</span><span class="p">,</span> <span class="n">num</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">vmin</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">maximum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">full</span><span class="p">(</span><span class="n">num</span><span class="p">,</span> <span class="n">vmin</span><span class="p">),</span> <span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">vmax</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">minimum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">full</span><span class="p">(</span><span class="n">num</span><span class="p">,</span> <span class="n">vmax</span><span class="p">),</span> <span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="n">_min</span> <span class="o">+=</span> <span class="n">min_inc</span>
|
||||
<span class="n">_max</span> <span class="o">+=</span> <span class="n">max_inc</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="white_noise"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.artificial.white_noise">[docs]</a><span class="k">def</span> <span class="nf">white_noise</span><span class="p">(</span><span class="n">n</span><span class="o">=</span><span class="mi">500</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">normal</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="n">n</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="random_walk"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.artificial.random_walk">[docs]</a><span class="k">def</span> <span class="nf">random_walk</span><span class="p">(</span><span class="n">n</span><span class="o">=</span><span class="mi">500</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="s1">'gaussian'</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">type</span> <span class="o">==</span> <span class="s1">'gaussian'</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">generate_gaussian_linear</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="n">it</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">num</span><span class="o">=</span><span class="n">n</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">generate_uniform_linear</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="n">it</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">num</span><span class="o">=</span><span class="n">n</span><span class="p">)</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n</span><span class="p">):</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">+</span> <span class="n">ret</span><span class="p">[</span><span class="n">i</span><span class="p">])</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
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|
||||
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
|
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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108
docs/_build/html/_modules/pyFTS/data/common.html
vendored
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108
docs/_build/html/_modules/pyFTS/data/common.html
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Normal file
@ -0,0 +1,108 @@
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|
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
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|
||||
<h1>Source code for pyFTS.data.common</h1><div class="highlight"><pre>
|
||||
<span></span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">os</span>
|
||||
<span class="kn">import</span> <span class="nn">pkg_resources</span>
|
||||
<span class="kn">from</span> <span class="nn">pathlib</span> <span class="k">import</span> <span class="n">Path</span>
|
||||
<span class="kn">from</span> <span class="nn">urllib</span> <span class="k">import</span> <span class="n">request</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.common.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">(</span><span class="n">filename</span><span class="p">,</span> <span class="n">url</span><span class="p">,</span> <span class="n">sep</span><span class="o">=</span><span class="s2">";"</span><span class="p">,</span> <span class="n">compression</span><span class="o">=</span><span class="s1">'infer'</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> This method check if filename already exists, read the file and return its data.</span>
|
||||
<span class="sd"> If the file don't already exists, it will be downloaded and decompressed.</span>
|
||||
|
||||
<span class="sd"> :param filename: dataset local filename</span>
|
||||
<span class="sd"> :param url: dataset internet URL</span>
|
||||
<span class="sd"> :param sep: CSV field separator</span>
|
||||
<span class="sd"> :param compression: type of compression</span>
|
||||
<span class="sd"> :return: Pandas dataset</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="n">tmp_file</span> <span class="o">=</span> <span class="n">Path</span><span class="p">(</span><span class="n">filename</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">tmp_file</span><span class="o">.</span><span class="n">is_file</span><span class="p">():</span>
|
||||
<span class="k">return</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="n">filename</span><span class="p">,</span> <span class="n">sep</span><span class="o">=</span><span class="n">sep</span><span class="p">,</span> <span class="n">compression</span><span class="o">=</span><span class="n">compression</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">request</span><span class="o">.</span><span class="n">urlretrieve</span><span class="p">(</span><span class="n">url</span><span class="p">,</span> <span class="n">filename</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="n">filename</span><span class="p">,</span> <span class="n">sep</span><span class="o">=</span><span class="n">sep</span><span class="p">,</span> <span class="n">compression</span><span class="o">=</span><span class="n">compression</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
|
||||
<div class="sphinxsidebarwrapper"><div class="relations">
|
||||
<h3>Related Topics</h3>
|
||||
<ul>
|
||||
<li><a href="../../../index.html">Documentation overview</a><ul>
|
||||
<li><a href="../../index.html">Module code</a><ul>
|
||||
</ul></li>
|
||||
</ul></li>
|
||||
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|
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|
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|
||||
<h3>Quick search</h3>
|
||||
<div class="searchformwrapper">
|
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||||
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|
||||
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|
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|
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|
||||
<script type="text/javascript">$('#searchbox').show(0);</script>
|
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|
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|
||||
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|
||||
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|
||||
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|
||||
©2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
|
||||
|
||||
|
|
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Powered by <a href="http://sphinx-doc.org/">Sphinx 1.7.2</a>
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|
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|
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|
||||
|
||||
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
108
docs/_build/html/_modules/pyFTS/data/henon.html
vendored
Normal file
108
docs/_build/html/_modules/pyFTS/data/henon.html
vendored
Normal file
@ -0,0 +1,108 @@
|
||||
|
||||
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
|
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"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
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<head>
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<meta http-equiv="X-UA-Compatible" content="IE=Edge" />
|
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<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
|
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<title>pyFTS.data.henon — pyFTS 1.2.3 documentation</title>
|
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<link rel="stylesheet" href="../../../_static/alabaster.css" type="text/css" />
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<script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script>
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<link rel="search" title="Search" href="../../../search.html" />
|
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<link rel="stylesheet" href="../../../_static/custom.css" type="text/css" />
|
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||||
|
||||
<meta name="viewport" content="width=device-width, initial-scale=0.9, maximum-scale=0.9" />
|
||||
|
||||
</head><body>
|
||||
|
||||
|
||||
<div class="document">
|
||||
<div class="documentwrapper">
|
||||
<div class="bodywrapper">
|
||||
<div class="body" role="main">
|
||||
|
||||
<h1>Source code for pyFTS.data.henon</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.henon.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">var</span><span class="p">,</span> <span class="n">a</span><span class="o">=</span><span class="mf">1.4</span><span class="p">,</span> <span class="n">b</span><span class="o">=</span><span class="mf">0.3</span><span class="p">,</span> <span class="n">initial_values</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">1000</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">get_dataframe</span><span class="p">(</span><span class="n">a</span><span class="p">,</span><span class="n">b</span><span class="p">,</span> <span class="n">initial_values</span><span class="p">,</span> <span class="n">iterations</span><span class="p">)[</span><span class="n">var</span><span class="p">]</span><span class="o">.</span><span class="n">values</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.henon.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">(</span><span class="n">a</span><span class="o">=</span><span class="mf">1.4</span><span class="p">,</span> <span class="n">b</span><span class="o">=</span><span class="mf">0.3</span><span class="p">,</span> <span class="n">initial_values</span> <span class="o">=</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">],</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">1000</span><span class="p">):</span>
|
||||
<span class="sd">'''</span>
|
||||
<span class="sd"> M. Hénon. "A two-dimensional mapping with a strange attractor". Commun. Math. Phys. 50, 69-77 (1976)</span>
|
||||
|
||||
<span class="sd"> dx/dt = a + by(t-1) - x(t-1)^2</span>
|
||||
<span class="sd"> dy/dt = x</span>
|
||||
|
||||
<span class="sd"> :param a: Equation coefficient</span>
|
||||
<span class="sd"> :param b: Equation coefficient</span>
|
||||
<span class="sd"> :param initial_values: numpy array with the initial values of x and y. Default: [1, 1]</span>
|
||||
<span class="sd"> :param iterations: number of iterations. Default: 1000</span>
|
||||
<span class="sd"> :return: Panda dataframe with the x and y values</span>
|
||||
<span class="sd"> '''</span>
|
||||
|
||||
<span class="n">x</span> <span class="o">=</span> <span class="p">[</span><span class="n">initial_values</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span>
|
||||
<span class="n">y</span> <span class="o">=</span> <span class="p">[</span><span class="n">initial_values</span><span class="p">[</span><span class="mi">1</span><span class="p">]]</span>
|
||||
<span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">iterations</span><span class="p">):</span>
|
||||
<span class="n">xx</span> <span class="o">=</span> <span class="n">a</span> <span class="o">+</span> <span class="n">b</span> <span class="o">*</span> <span class="n">y</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">-</span> <span class="n">x</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">**</span> <span class="mi">2</span>
|
||||
<span class="n">y</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="n">t</span><span class="p">])</span>
|
||||
<span class="n">x</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">xx</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span><span class="s1">'x'</span><span class="p">:</span> <span class="n">x</span><span class="p">,</span> <span class="s1">'y'</span><span class="p">:</span><span class="n">y</span><span class="p">})</span></div>
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
|
||||
<div class="sphinxsidebarwrapper"><div class="relations">
|
||||
<h3>Related Topics</h3>
|
||||
<ul>
|
||||
<li><a href="../../../index.html">Documentation overview</a><ul>
|
||||
<li><a href="../../index.html">Module code</a><ul>
|
||||
</ul></li>
|
||||
</ul></li>
|
||||
</ul>
|
||||
</div>
|
||||
<div id="searchbox" style="display: none" role="search">
|
||||
<h3>Quick search</h3>
|
||||
<div class="searchformwrapper">
|
||||
<form class="search" action="../../../search.html" method="get">
|
||||
<input type="text" name="q" />
|
||||
<input type="submit" value="Go" />
|
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|
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|
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|
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|
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|
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|
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|
||||
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|
||||
|
||||
|
|
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Powered by <a href="http://sphinx-doc.org/">Sphinx 1.7.2</a>
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|
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|
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|
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</body>
|
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</html>
|
||||
100
docs/_build/html/_modules/pyFTS/data/logistic_map.html
vendored
Normal file
100
docs/_build/html/_modules/pyFTS/data/logistic_map.html
vendored
Normal file
@ -0,0 +1,100 @@
|
||||
|
||||
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
|
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"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
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<meta http-equiv="X-UA-Compatible" content="IE=Edge" />
|
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|
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<title>pyFTS.data.logistic_map — pyFTS 1.2.3 documentation</title>
|
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<link rel="stylesheet" href="../../../_static/alabaster.css" type="text/css" />
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<h1>Source code for pyFTS.data.logistic_map</h1><div class="highlight"><pre>
|
||||
<span></span><span class="c1">#</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.logistic_map.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">r</span> <span class="o">=</span> <span class="mi">4</span><span class="p">,</span> <span class="n">initial_value</span> <span class="o">=</span> <span class="mf">0.3</span><span class="p">,</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">100</span><span class="p">):</span>
|
||||
<span class="sd">'''</span>
|
||||
<span class="sd"> May, Robert M. (1976). "Simple mathematical models with very complicated dynamics".</span>
|
||||
<span class="sd"> Nature. 261 (5560): 459–467. doi:10.1038/261459a0.</span>
|
||||
|
||||
<span class="sd"> x(t) = r * x(t-1) * (1 - x(t -1) )</span>
|
||||
|
||||
<span class="sd"> :param r: Equation coefficient</span>
|
||||
<span class="sd"> :param initial_value: Initial value of x. Default: 0.3</span>
|
||||
<span class="sd"> :param iterations: number of iterations. Default: 100</span>
|
||||
<span class="sd"> :return:</span>
|
||||
<span class="sd"> '''</span>
|
||||
<span class="n">x</span> <span class="o">=</span> <span class="p">[</span><span class="n">initial_value</span><span class="p">]</span>
|
||||
<span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="n">iterations</span><span class="p">):</span>
|
||||
<span class="n">x</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">r</span> <span class="o">*</span> <span class="n">x</span><span class="p">[</span><span class="n">t</span><span class="p">]</span><span class="o">*</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">x</span><span class="p">[</span><span class="n">t</span><span class="p">]))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">x</span></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
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|
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|
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119
docs/_build/html/_modules/pyFTS/data/lorentz.html
vendored
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119
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Normal file
@ -0,0 +1,119 @@
|
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|
||||
<h1>Source code for pyFTS.data.lorentz</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.lorentz.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">var</span><span class="p">,</span> <span class="n">a</span> <span class="o">=</span> <span class="mf">10.0</span><span class="p">,</span> <span class="n">b</span> <span class="o">=</span> <span class="mf">28.0</span><span class="p">,</span> <span class="n">c</span> <span class="o">=</span> <span class="mf">8.0</span> <span class="o">/</span> <span class="mf">3.0</span><span class="p">,</span> <span class="n">dt</span> <span class="o">=</span> <span class="mf">0.01</span><span class="p">,</span>
|
||||
<span class="n">initial_values</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.1</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">1000</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">get_dataframe</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">initial_values</span><span class="p">,</span> <span class="n">iterations</span><span class="p">)[</span><span class="n">var</span><span class="p">]</span><span class="o">.</span><span class="n">values</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.lorentz.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">(</span><span class="n">a</span> <span class="o">=</span> <span class="mf">10.0</span><span class="p">,</span> <span class="n">b</span> <span class="o">=</span> <span class="mf">28.0</span><span class="p">,</span> <span class="n">c</span> <span class="o">=</span> <span class="mf">8.0</span> <span class="o">/</span> <span class="mf">3.0</span><span class="p">,</span> <span class="n">dt</span> <span class="o">=</span> <span class="mf">0.01</span><span class="p">,</span>
|
||||
<span class="n">initial_values</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.1</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">1000</span><span class="p">):</span>
|
||||
<span class="sd">'''</span>
|
||||
<span class="sd"> Lorenz, Edward Norton (1963). "Deterministic nonperiodic flow". Journal of the Atmospheric Sciences. 20 (2): 130–141.</span>
|
||||
<span class="sd"> https://doi.org/10.1175/1520-0469(1963)020<0130:DNF>2.0.CO;2</span>
|
||||
|
||||
<span class="sd"> dx/dt = a(y -x)</span>
|
||||
<span class="sd"> dy/dt = x(b - z) - y</span>
|
||||
<span class="sd"> dz/dt = xy - cz</span>
|
||||
|
||||
<span class="sd"> :param a: Equation coefficient. Default value: 10</span>
|
||||
<span class="sd"> :param b: Equation coefficient. Default value: 28</span>
|
||||
<span class="sd"> :param c: Equation coefficient. Default value: 8.0/3.0</span>
|
||||
<span class="sd"> :param dt: Time differential for continuous time integration. Default value: 0.01</span>
|
||||
<span class="sd"> :param initial_values: numpy array with the initial values of x,y and z. Default: [0.1, 0, 0]</span>
|
||||
<span class="sd"> :param iterations: number of iterations. Default: 1000</span>
|
||||
<span class="sd"> :return: Panda dataframe with the x, y and z values</span>
|
||||
<span class="sd"> '''</span>
|
||||
|
||||
<span class="n">x</span> <span class="o">=</span> <span class="p">[</span><span class="n">initial_values</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span>
|
||||
<span class="n">y</span> <span class="o">=</span> <span class="p">[</span><span class="n">initial_values</span><span class="p">[</span><span class="mi">1</span><span class="p">]]</span>
|
||||
<span class="n">z</span> <span class="o">=</span> <span class="p">[</span><span class="n">initial_values</span><span class="p">[</span><span class="mi">2</span><span class="p">]]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">iterations</span><span class="p">):</span>
|
||||
<span class="n">dxdt</span> <span class="o">=</span> <span class="n">a</span> <span class="o">*</span> <span class="p">(</span><span class="n">y</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">-</span> <span class="n">x</span><span class="p">[</span><span class="n">t</span><span class="p">])</span>
|
||||
<span class="n">dydt</span> <span class="o">=</span> <span class="n">x</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">*</span> <span class="p">(</span><span class="n">b</span> <span class="o">-</span> <span class="n">z</span><span class="p">[</span><span class="n">t</span><span class="p">])</span> <span class="o">-</span> <span class="n">y</span><span class="p">[</span><span class="n">t</span><span class="p">]</span>
|
||||
<span class="n">dzdt</span> <span class="o">=</span> <span class="n">x</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">*</span> <span class="n">y</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">-</span> <span class="n">c</span> <span class="o">*</span> <span class="n">z</span><span class="p">[</span><span class="n">t</span><span class="p">]</span>
|
||||
<span class="n">x</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">+</span> <span class="n">dt</span> <span class="o">*</span> <span class="n">dxdt</span><span class="p">)</span>
|
||||
<span class="n">y</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">y</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">+</span> <span class="n">dt</span> <span class="o">*</span> <span class="n">dydt</span><span class="p">)</span>
|
||||
<span class="n">z</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">z</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">+</span> <span class="n">dt</span> <span class="o">*</span> <span class="n">dzdt</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span><span class="s1">'x'</span><span class="p">:</span> <span class="n">x</span><span class="p">,</span> <span class="s1">'y'</span><span class="p">:</span><span class="n">y</span><span class="p">,</span> <span class="s1">'z'</span><span class="p">:</span> <span class="n">z</span><span class="p">})</span></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
||||
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|
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|
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|
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101
docs/_build/html/_modules/pyFTS/data/mackey_glass.html
vendored
Normal file
101
docs/_build/html/_modules/pyFTS/data/mackey_glass.html
vendored
Normal file
@ -0,0 +1,101 @@
|
||||
|
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
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|
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<h1>Source code for pyFTS.data.mackey_glass</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.mackey_glass.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">b</span><span class="o">=</span><span class="mf">0.1</span><span class="p">,</span> <span class="n">c</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> <span class="n">tau</span><span class="o">=</span><span class="mi">17</span><span class="p">,</span> <span class="n">initial_values</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="mf">0.5</span><span class="p">,</span><span class="mf">1.5</span><span class="p">,</span> <span class="mi">18</span><span class="p">),</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">1000</span><span class="p">):</span>
|
||||
<span class="sd">'''</span>
|
||||
<span class="sd"> Mackey, M. C. and Glass, L. (1977). Oscillation and chaos in physiological control systems.</span>
|
||||
<span class="sd"> Science, 197(4300):287-289.</span>
|
||||
|
||||
<span class="sd"> dy/dt = -by(t)+ cy(t - tau) / 1+y(t-tau)^10</span>
|
||||
|
||||
<span class="sd"> :param b: Equation coefficient</span>
|
||||
<span class="sd"> :param c: Equation coefficient</span>
|
||||
<span class="sd"> :param tau: Lag parameter, default: 17</span>
|
||||
<span class="sd"> :param initial_values: numpy array with the initial values of y. Default: np.linspace(0.5,1.5,18)</span>
|
||||
<span class="sd"> :param iterations: number of iterations. Default: 1000</span>
|
||||
<span class="sd"> :return:</span>
|
||||
<span class="sd"> '''</span>
|
||||
<span class="n">y</span> <span class="o">=</span> <span class="n">initial_values</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">y</span><span class="p">)</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="n">iterations</span><span class="o">+</span><span class="mi">100</span><span class="p">):</span>
|
||||
<span class="n">y</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">y</span><span class="p">[</span><span class="n">n</span><span class="p">]</span> <span class="o">-</span> <span class="n">b</span> <span class="o">*</span> <span class="n">y</span><span class="p">[</span><span class="n">n</span><span class="p">]</span> <span class="o">+</span> <span class="n">c</span> <span class="o">*</span> <span class="n">y</span><span class="p">[</span><span class="n">n</span> <span class="o">-</span> <span class="n">tau</span><span class="p">]</span> <span class="o">/</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="n">y</span><span class="p">[</span><span class="n">n</span> <span class="o">-</span> <span class="n">tau</span><span class="p">]</span> <span class="o">**</span> <span class="mi">10</span><span class="p">))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">y</span><span class="p">[</span><span class="mi">100</span><span class="p">:]</span></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
||||
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|
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|
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|
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|
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|
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|
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|
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118
docs/_build/html/_modules/pyFTS/data/rossler.html
vendored
Normal file
118
docs/_build/html/_modules/pyFTS/data/rossler.html
vendored
Normal file
@ -0,0 +1,118 @@
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|
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||||
<h1>Source code for pyFTS.data.rossler</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.rossler.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="n">var</span><span class="p">,</span> <span class="n">a</span> <span class="o">=</span> <span class="mf">0.2</span><span class="p">,</span> <span class="n">b</span> <span class="o">=</span> <span class="mf">0.2</span><span class="p">,</span> <span class="n">c</span> <span class="o">=</span> <span class="mf">5.7</span><span class="p">,</span> <span class="n">dt</span> <span class="o">=</span> <span class="mf">0.01</span><span class="p">,</span>
|
||||
<span class="n">initial_values</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.001</span><span class="p">,</span> <span class="mf">0.001</span><span class="p">,</span> <span class="mf">0.001</span><span class="p">],</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">5000</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">get_dataframe</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">b</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="n">dt</span><span class="p">,</span> <span class="n">initial_values</span><span class="p">,</span> <span class="n">iterations</span><span class="p">)[</span><span class="n">var</span><span class="p">]</span><span class="o">.</span><span class="n">values</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.rossler.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">(</span><span class="n">a</span> <span class="o">=</span> <span class="mf">0.2</span><span class="p">,</span> <span class="n">b</span> <span class="o">=</span> <span class="mf">0.2</span><span class="p">,</span> <span class="n">c</span> <span class="o">=</span> <span class="mf">5.7</span><span class="p">,</span> <span class="n">dt</span> <span class="o">=</span> <span class="mf">0.01</span><span class="p">,</span>
|
||||
<span class="n">initial_values</span> <span class="o">=</span> <span class="p">[</span><span class="mf">0.001</span><span class="p">,</span> <span class="mf">0.001</span><span class="p">,</span> <span class="mf">0.001</span><span class="p">],</span> <span class="n">iterations</span><span class="o">=</span><span class="mi">5000</span><span class="p">):</span>
|
||||
<span class="sd">'''</span>
|
||||
<span class="sd"> O. E. Rössler, Phys. Lett. 57A, 397 (1976).</span>
|
||||
|
||||
<span class="sd"> dx/dt = -z - y</span>
|
||||
<span class="sd"> dy/dt = x + ay</span>
|
||||
<span class="sd"> dz/dt = b + z( x - c )</span>
|
||||
|
||||
<span class="sd"> :param a: Equation coefficient. Default value: 0.2</span>
|
||||
<span class="sd"> :param b: Equation coefficient. Default value: 0.2</span>
|
||||
<span class="sd"> :param c: Equation coefficient. Default value: 5.7</span>
|
||||
<span class="sd"> :param dt: Time differential for continuous time integration. Default value: 0.01</span>
|
||||
<span class="sd"> :param initial_values: numpy array with the initial values of x,y and z. Default: [0.001, 0.001, 0.001]</span>
|
||||
<span class="sd"> :param iterations: number of iterations. Default: 5000</span>
|
||||
<span class="sd"> :return: Panda dataframe with the x, y and z values</span>
|
||||
<span class="sd"> '''</span>
|
||||
|
||||
<span class="n">x</span> <span class="o">=</span> <span class="p">[</span><span class="n">initial_values</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span>
|
||||
<span class="n">y</span> <span class="o">=</span> <span class="p">[</span><span class="n">initial_values</span><span class="p">[</span><span class="mi">1</span><span class="p">]]</span>
|
||||
<span class="n">z</span> <span class="o">=</span> <span class="p">[</span><span class="n">initial_values</span><span class="p">[</span><span class="mi">2</span><span class="p">]]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">iterations</span><span class="p">):</span>
|
||||
<span class="n">dxdt</span> <span class="o">=</span> <span class="o">-</span> <span class="p">(</span><span class="n">y</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">+</span> <span class="n">z</span><span class="p">[</span><span class="n">t</span><span class="p">])</span>
|
||||
<span class="n">dydt</span> <span class="o">=</span> <span class="n">x</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">+</span> <span class="n">a</span> <span class="o">*</span> <span class="n">y</span><span class="p">[</span><span class="n">t</span><span class="p">]</span>
|
||||
<span class="n">dzdt</span> <span class="o">=</span> <span class="n">b</span> <span class="o">+</span> <span class="n">z</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">*</span> <span class="n">x</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">-</span> <span class="n">z</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">*</span> <span class="n">c</span>
|
||||
<span class="n">x</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">x</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">+</span> <span class="n">dt</span> <span class="o">*</span> <span class="n">dxdt</span><span class="p">)</span>
|
||||
<span class="n">y</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">y</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">+</span> <span class="n">dt</span> <span class="o">*</span> <span class="n">dydt</span><span class="p">)</span>
|
||||
<span class="n">z</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">z</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">+</span> <span class="n">dt</span> <span class="o">*</span> <span class="n">dzdt</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span><span class="s1">'x'</span><span class="p">:</span> <span class="n">x</span><span class="p">,</span> <span class="s1">'y'</span><span class="p">:</span><span class="n">y</span><span class="p">,</span> <span class="s1">'z'</span><span class="p">:</span> <span class="n">z</span><span class="p">})</span></div>
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
|
||||
<div class="sphinxsidebarwrapper"><div class="relations">
|
||||
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|
||||
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|
||||
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|
||||
<li><a href="../../index.html">Module code</a><ul>
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
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|
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103
docs/_build/html/_modules/pyFTS/data/sunspots.html
vendored
Normal file
103
docs/_build/html/_modules/pyFTS/data/sunspots.html
vendored
Normal file
@ -0,0 +1,103 @@
|
||||
|
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
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|
||||
<h1>Source code for pyFTS.data.sunspots</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">from</span> <span class="nn">pyFTS.data</span> <span class="k">import</span> <span class="n">common</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
|
||||
<div class="viewcode-block" id="get_data"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.sunspots.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">():</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Get a simple univariate time series data.</span>
|
||||
|
||||
<span class="sd"> :return: numpy array</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">get_dataframe</span><span class="p">()</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">dat</span><span class="p">[</span><span class="s2">"SUNACTIVITY"</span><span class="p">])</span>
|
||||
<span class="k">return</span> <span class="n">dat</span></div>
|
||||
|
||||
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.sunspots.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Get the complete multivariate time series data.</span>
|
||||
|
||||
<span class="sd"> :return: Pandas DataFrame</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">dat</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">get_dataframe</span><span class="p">(</span><span class="s1">'sunspots.csv'</span><span class="p">,</span>
|
||||
<span class="s1">'https://github.com/petroniocandido/pyFTS/raw/8f20f3634aa6a8f58083bdcd1bbf93795e6ed767/pyFTS/data/sunspots.csv'</span><span class="p">,</span>
|
||||
<span class="n">sep</span><span class="o">=</span><span class="s2">","</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">dat</span></div>
|
||||
|
||||
</pre></div>
|
||||
|
||||
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|
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|
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|
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154
docs/_build/html/_modules/pyFTS/models/chen.html
vendored
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154
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<h1>Source code for pyFTS.models.chen</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">First Order Conventional Fuzzy Time Series by Chen (1996)</span>
|
||||
|
||||
<span class="sd">S.-M. Chen, “Forecasting enrollments based on fuzzy time series,” Fuzzy Sets Syst., vol. 81, no. 3, pp. 311–319, 1996.</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ConventionalFLRG"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.chen.ConventionalFLRG">[docs]</a><span class="k">class</span> <span class="nc">ConventionalFLRG</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">):</span>
|
||||
<span class="sd">"""First Order Conventional Fuzzy Logical Relationship Group"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">ConventionalFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="n">LHS</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span>
|
||||
|
||||
<div class="viewcode-block" id="ConventionalFLRG.get_key"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.chen.ConventionalFLRG.get_key">[docs]</a> <span class="k">def</span> <span class="nf">get_key</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span><span class="o">.</span><span class="n">name</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ConventionalFLRG.append_rhs"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.chen.ConventionalFLRG.append_rhs">[docs]</a> <span class="k">def</span> <span class="nf">append_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">c</span><span class="p">)</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">+</span> <span class="s2">" -> "</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">s</span><span class="p">:</span> <span class="n">s</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">tmp2</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="n">tmp2</span> <span class="o">+</span> <span class="s2">","</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="n">tmp2</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">c</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">tmp</span> <span class="o">+</span> <span class="n">tmp2</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ConventionalFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.chen.ConventionalFTS">[docs]</a><span class="k">class</span> <span class="nc">ConventionalFTS</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
|
||||
<span class="sd">"""Conventional Fuzzy Time Series"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">ConventionalFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Conventional FTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">"Chen"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">"CFTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<div class="viewcode-block" id="ConventionalFTS.generate_flrg"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.chen.ConventionalFTS.generate_flrg">[docs]</a> <span class="k">def</span> <span class="nf">generate_flrg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrs</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">flr</span> <span class="ow">in</span> <span class="n">flrs</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">flr</span><span class="o">.</span><span class="n">LHS</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span> <span class="o">=</span> <span class="n">ConventionalFLRG</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ConventionalFTS.train"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.chen.ConventionalFTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">tmpdata</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">fuzzyfy_series</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s1">'maximum'</span><span class="p">)</span>
|
||||
<span class="n">flrs</span> <span class="o">=</span> <span class="n">FLR</span><span class="o">.</span><span class="n">generate_non_recurrent_flrs</span><span class="p">(</span><span class="n">tmpdata</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">generate_flrg</span><span class="p">(</span><span class="n">flrs</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ConventionalFTS.forecast"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.chen.ConventionalFTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
|
||||
<span class="n">mv</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">fuzzyfy_instance</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
|
||||
<span class="n">actual</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">get_maximum_membership_fuzzyset</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span> <span class="c1">#self.sets[np.argwhere(mv == max(mv))[0, 0]]</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">actual</span><span class="o">.</span><span class="n">name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">actual</span><span class="o">.</span><span class="n">centroid</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">_flrg</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">actual</span><span class="o">.</span><span class="n">name</span><span class="p">]</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_flrg</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
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|
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|
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|
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|
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|
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|
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|
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|
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|
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139
docs/_build/html/_modules/pyFTS/models/cheng.html
vendored
Normal file
139
docs/_build/html/_modules/pyFTS/models/cheng.html
vendored
Normal file
@ -0,0 +1,139 @@
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||||
|
||||
<h1>Source code for pyFTS.models.cheng</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">Trend Weighted Fuzzy Time Series by Cheng, Chen and Wu (2009)</span>
|
||||
|
||||
<span class="sd">C.-H. Cheng, Y.-S. Chen, and Y.-L. Wu, “Forecasting innovation diffusion of products using trend-weighted fuzzy time-series model,” </span>
|
||||
<span class="sd">Expert Syst. Appl., vol. 36, no. 2, pp. 1826–1832, 2009.</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">yu</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="TrendWeightedFLRG"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.cheng.TrendWeightedFLRG">[docs]</a><span class="k">class</span> <span class="nc">TrendWeightedFLRG</span><span class="p">(</span><span class="n">yu</span><span class="o">.</span><span class="n">WeightedFLRG</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> First Order Trend Weighted Fuzzy Logical Relationship Group</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">TrendWeightedFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
|
||||
<div class="viewcode-block" id="TrendWeightedFLRG.weights"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.cheng.TrendWeightedFLRG.weights">[docs]</a> <span class="k">def</span> <span class="nf">weights</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">count_nochange</span> <span class="o">=</span> <span class="mf">0.0</span>
|
||||
<span class="n">count_up</span> <span class="o">=</span> <span class="mf">0.0</span>
|
||||
<span class="n">count_down</span> <span class="o">=</span> <span class="mf">0.0</span>
|
||||
<span class="n">weights</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">if</span> <span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span> <span class="o">==</span> <span class="n">sets</span><span class="p">[</span><span class="n">c</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span><span class="p">:</span>
|
||||
<span class="n">count_nochange</span> <span class="o">+=</span> <span class="mf">1.0</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">count_nochange</span>
|
||||
<span class="k">elif</span> <span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span> <span class="o">></span> <span class="n">sets</span><span class="p">[</span><span class="n">c</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span><span class="p">:</span>
|
||||
<span class="n">count_down</span> <span class="o">+=</span> <span class="mf">1.0</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">count_down</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">count_up</span> <span class="o">+=</span> <span class="mf">1.0</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">count_up</span>
|
||||
<span class="n">weights</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
|
||||
<span class="n">tot</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">weights</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">k</span> <span class="o">/</span> <span class="n">tot</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">weights</span><span class="p">])</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">w</span></div></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="TrendWeightedFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.cheng.TrendWeightedFTS">[docs]</a><span class="k">class</span> <span class="nc">TrendWeightedFTS</span><span class="p">(</span><span class="n">yu</span><span class="o">.</span><span class="n">WeightedFTS</span><span class="p">):</span>
|
||||
<span class="sd">"""First Order Trend Weighted Fuzzy Time Series"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">TrendWeightedFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">"TWFTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Trend Weighted FTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">"Cheng"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
|
||||
<div class="viewcode-block" id="TrendWeightedFTS.generate_FLRG"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.cheng.TrendWeightedFTS.generate_FLRG">[docs]</a> <span class="k">def</span> <span class="nf">generate_FLRG</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrs</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">flr</span> <span class="ow">in</span> <span class="n">flrs</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">flr</span><span class="o">.</span><span class="n">LHS</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span> <span class="o">=</span> <span class="n">TrendWeightedFLRG</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
|
||||
<div class="sphinxsidebarwrapper"><div class="relations">
|
||||
<h3>Related Topics</h3>
|
||||
<ul>
|
||||
<li><a href="../../../index.html">Documentation overview</a><ul>
|
||||
<li><a href="../../index.html">Module code</a><ul>
|
||||
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|
||||
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|
||||
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|
||||
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|
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<div id="searchbox" style="display: none" role="search">
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<h3>Quick search</h3>
|
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<div class="searchformwrapper">
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©2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
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380
docs/_build/html/_modules/pyFTS/models/ensemble/ensemble.html
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380
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<title>pyFTS.models.ensemble.ensemble — pyFTS 1.2.3 documentation</title>
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|
||||
<h1>Source code for pyFTS.models.ensemble.ensemble</h1><div class="highlight"><pre>
|
||||
<span></span><span class="ch">#!/usr/bin/python</span>
|
||||
<span class="c1"># -*- coding: utf8 -*-</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">SortedCollection</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">tree</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">chen</span><span class="p">,</span> <span class="n">cheng</span><span class="p">,</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">hwang</span><span class="p">,</span> <span class="n">ismailefendi</span><span class="p">,</span> <span class="n">sadaei</span><span class="p">,</span> <span class="n">song</span><span class="p">,</span> <span class="n">yu</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">ProbabilityDistribution</span>
|
||||
<span class="kn">import</span> <span class="nn">scipy.stats</span> <span class="k">as</span> <span class="nn">st</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="sampler"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.sampler">[docs]</a><span class="k">def</span> <span class="nf">sampler</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">quantiles</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">qt</span> <span class="ow">in</span> <span class="n">quantiles</span><span class="p">:</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">nanpercentile</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">q</span><span class="o">=</span><span class="n">qt</span> <span class="o">*</span> <span class="mi">100</span><span class="p">))</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="EnsembleFTS"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS">[docs]</a><span class="k">class</span> <span class="nc">EnsembleFTS</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Ensemble FTS</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">EnsembleFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">"Ensemble FTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Ensemble FTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_point_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_interval_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_probability_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">models</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="sd">"""A list of FTS models, the ensemble components"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">parameters</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="sd">"""A list with the parameters for each component model"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">alpha</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"alpha"</span><span class="p">,</span> <span class="mf">0.05</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">point_method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'point_method'</span><span class="p">,</span> <span class="s1">'mean'</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">interval_method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'interval_method'</span><span class="p">,</span> <span class="s1">'quantile'</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
|
||||
<div class="viewcode-block" id="EnsembleFTS.append_model"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS.append_model">[docs]</a> <span class="k">def</span> <span class="nf">append_model</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">model</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Append a new model to the ensemble</span>
|
||||
|
||||
<span class="sd"> :param model: FTS model</span>
|
||||
|
||||
<span class="sd"> """</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">models</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">model</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">model</span><span class="o">.</span><span class="n">order</span> <span class="o">></span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">order</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">model</span><span class="o">.</span><span class="n">is_multivariate</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_multivariate</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">model</span><span class="o">.</span><span class="n">has_seasonality</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_seasonality</span> <span class="o">=</span> <span class="kc">True</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="EnsembleFTS.train"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">pass</span></div>
|
||||
|
||||
<div class="viewcode-block" id="EnsembleFTS.get_models_forecasts"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS.get_models_forecasts">[docs]</a> <span class="k">def</span> <span class="nf">get_models_forecasts</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">data</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">model</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">models</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">model</span><span class="o">.</span><span class="n">is_multivariate</span> <span class="ow">or</span> <span class="n">model</span><span class="o">.</span><span class="n">has_seasonality</span><span class="p">:</span>
|
||||
<span class="n">forecast</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">forecast</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">)</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">data</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_data</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="o">-</span><span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">:]</span>
|
||||
<span class="n">forecast</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">forecast</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">forecast</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">))</span> <span class="ow">and</span> <span class="nb">len</span><span class="p">(</span><span class="n">forecast</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">forecast</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">forecast</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">forecast</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">))</span> <span class="ow">and</span> <span class="nb">len</span><span class="p">(</span><span class="n">forecast</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">forecast</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">forecast</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">forecast</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">forecast</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">tmp</span></div>
|
||||
|
||||
<div class="viewcode-block" id="EnsembleFTS.get_point"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS.get_point">[docs]</a> <span class="k">def</span> <span class="nf">get_point</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">forecasts</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">point_method</span> <span class="o">==</span> <span class="s1">'mean'</span><span class="p">:</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmean</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">point_method</span> <span class="o">==</span> <span class="s1">'median'</span><span class="p">:</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nanpercentile</span><span class="p">(</span><span class="n">forecasts</span><span class="p">,</span> <span class="mi">50</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">point_method</span> <span class="o">==</span> <span class="s1">'quantile'</span><span class="p">:</span>
|
||||
<span class="n">alpha</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"alpha"</span><span class="p">,</span><span class="mf">0.05</span><span class="p">)</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">percentile</span><span class="p">(</span><span class="n">forecasts</span><span class="p">,</span> <span class="n">alpha</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="EnsembleFTS.get_interval"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS.get_interval">[docs]</a> <span class="k">def</span> <span class="nf">get_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">interval_method</span> <span class="o">==</span> <span class="s1">'extremum'</span><span class="p">:</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="nb">min</span><span class="p">(</span><span class="n">forecasts</span><span class="p">),</span> <span class="nb">max</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)])</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">interval_method</span> <span class="o">==</span> <span class="s1">'quantile'</span><span class="p">:</span>
|
||||
<span class="n">qt_lo</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nanpercentile</span><span class="p">(</span><span class="n">forecasts</span><span class="p">,</span> <span class="n">q</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">alpha</span> <span class="o">*</span> <span class="mi">100</span><span class="p">)</span>
|
||||
<span class="n">qt_up</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nanpercentile</span><span class="p">(</span><span class="n">forecasts</span><span class="p">,</span> <span class="n">q</span><span class="o">=</span><span class="p">(</span><span class="mi">1</span><span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">alpha</span><span class="p">)</span> <span class="o">*</span> <span class="mi">100</span><span class="p">)</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="n">qt_lo</span><span class="p">,</span> <span class="n">qt_up</span><span class="p">])</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">interval_method</span> <span class="o">==</span> <span class="s1">'normal'</span><span class="p">:</span>
|
||||
<span class="n">mu</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmean</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)</span>
|
||||
<span class="n">sigma</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">nanvar</span><span class="p">(</span><span class="n">forecasts</span><span class="p">))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mu</span> <span class="o">+</span> <span class="n">st</span><span class="o">.</span><span class="n">norm</span><span class="o">.</span><span class="n">ppf</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">alpha</span><span class="p">)</span> <span class="o">*</span> <span class="n">sigma</span><span class="p">)</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mu</span> <span class="o">+</span> <span class="n">st</span><span class="o">.</span><span class="n">norm</span><span class="o">.</span><span class="n">ppf</span><span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">alpha</span><span class="p">)</span> <span class="o">*</span> <span class="n">sigma</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="EnsembleFTS.get_distribution_interquantile"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS.get_distribution_interquantile">[docs]</a> <span class="k">def</span> <span class="nf">get_distribution_interquantile</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">forecasts</span><span class="p">,</span> <span class="n">alpha</span><span class="p">):</span>
|
||||
<span class="n">size</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)</span>
|
||||
<span class="n">qt_lower</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ceil</span><span class="p">(</span><span class="n">size</span> <span class="o">*</span> <span class="n">alpha</span><span class="p">))</span> <span class="o">-</span> <span class="mi">1</span>
|
||||
<span class="n">qt_upper</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ceil</span><span class="p">(</span><span class="n">size</span> <span class="o">*</span> <span class="p">(</span><span class="mi">1</span><span class="o">-</span> <span class="n">alpha</span><span class="p">)))</span> <span class="o">-</span> <span class="mi">1</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)[</span><span class="n">qt_lower</span> <span class="p">:</span> <span class="n">qt_upper</span><span class="p">]</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="EnsembleFTS.forecast"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="s2">"method"</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">point_method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'method'</span><span class="p">,</span><span class="s1">'mean'</span><span class="p">)</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">l</span><span class="o">+</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="p">:</span> <span class="n">k</span><span class="p">]</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_models_forecasts</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
<span class="n">point</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_point</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">point</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="EnsembleFTS.forecast_interval"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS.forecast_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="s2">"method"</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">interval_method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'method'</span><span class="p">,</span><span class="s1">'quantile'</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="s1">'alpha'</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">alpha</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'alpha'</span><span class="p">,</span><span class="mf">0.05</span><span class="p">)</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">l</span><span class="o">+</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="p">:</span> <span class="n">k</span><span class="p">]</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_models_forecasts</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
<span class="n">interval</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_interval</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">interval</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">interval</span> <span class="o">=</span> <span class="n">interval</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">interval</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="EnsembleFTS.forecast_ahead_interval"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS.forecast_ahead_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="s1">'method'</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">interval_method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'method'</span><span class="p">,</span><span class="s1">'quantile'</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="s1">'alpha'</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">alpha</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'alpha'</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">alpha</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">samples</span> <span class="o">=</span> <span class="p">[[</span><span class="n">k</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">data</span><span class="p">[</span><span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">:]]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">steps</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">):</span>
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">lags</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">):</span> <span class="n">lags</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">samples</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">+</span> <span class="n">i</span><span class="p">]</span>
|
||||
|
||||
<span class="c1"># Build the tree with all possible paths</span>
|
||||
|
||||
<span class="n">root</span> <span class="o">=</span> <span class="n">tree</span><span class="o">.</span><span class="n">FLRGTreeNode</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="n">tree</span><span class="o">.</span><span class="n">build_tree_without_order</span><span class="p">(</span><span class="n">root</span><span class="p">,</span> <span class="n">lags</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">root</span><span class="o">.</span><span class="n">paths</span><span class="p">():</span>
|
||||
<span class="n">path</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">reversed</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">filter</span><span class="p">(</span><span class="kc">None</span><span class="o">.</span><span class="fm">__ne__</span><span class="p">,</span> <span class="n">p</span><span class="p">))))</span>
|
||||
|
||||
<span class="n">forecasts</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">get_models_forecasts</span><span class="p">(</span><span class="n">path</span><span class="p">))</span>
|
||||
|
||||
<span class="n">samples</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">sampler</span><span class="p">(</span><span class="n">forecasts</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mf">0.1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mf">0.2</span><span class="p">)))</span>
|
||||
<span class="n">interval</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_interval</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">interval</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">interval</span> <span class="o">=</span> <span class="n">interval</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">interval</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="EnsembleFTS.forecast_distribution"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS.forecast_distribution">[docs]</a> <span class="k">def</span> <span class="nf">forecast_distribution</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">smooth</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"smooth"</span><span class="p">,</span> <span class="s2">"KDE"</span><span class="p">)</span>
|
||||
<span class="n">alpha</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"alpha"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="n">uod</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_UoD</span><span class="p">()</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)):</span>
|
||||
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span><span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="p">:</span> <span class="n">k</span><span class="p">]</span>
|
||||
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_models_forecasts</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">alpha</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_distribution_interquantile</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span> <span class="n">alpha</span><span class="p">)</span>
|
||||
|
||||
<span class="n">dist</span> <span class="o">=</span> <span class="n">ProbabilityDistribution</span><span class="o">.</span><span class="n">ProbabilityDistribution</span><span class="p">(</span><span class="n">smooth</span><span class="p">,</span> <span class="n">uod</span><span class="o">=</span><span class="n">uod</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">forecasts</span><span class="p">,</span>
|
||||
<span class="n">name</span><span class="o">=</span><span class="s2">""</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">dist</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="EnsembleFTS.forecast_ahead_distribution"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS.forecast_ahead_distribution">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead_distribution</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="s1">'method'</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">point_method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'method'</span><span class="p">,</span><span class="s1">'mean'</span><span class="p">)</span>
|
||||
|
||||
<span class="n">smooth</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"smooth"</span><span class="p">,</span> <span class="s2">"KDE"</span><span class="p">)</span>
|
||||
<span class="n">alpha</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"alpha"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">start</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'start'</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">)</span>
|
||||
|
||||
<span class="n">uod</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_UoD</span><span class="p">()</span>
|
||||
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">start</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">:</span> <span class="n">start</span><span class="p">]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">steps</span><span class="o">+</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">):</span>
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">lags</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">):</span> <span class="n">lags</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="o">=</span> <span class="n">sample</span><span class="p">[</span><span class="n">k</span><span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">]</span>
|
||||
|
||||
<span class="c1"># Build the tree with all possible paths</span>
|
||||
|
||||
<span class="n">root</span> <span class="o">=</span> <span class="n">tree</span><span class="o">.</span><span class="n">FLRGTreeNode</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="n">tree</span><span class="o">.</span><span class="n">build_tree_without_order</span><span class="p">(</span><span class="n">root</span><span class="p">,</span> <span class="n">lags</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">root</span><span class="o">.</span><span class="n">paths</span><span class="p">():</span>
|
||||
<span class="n">path</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">reversed</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">filter</span><span class="p">(</span><span class="kc">None</span><span class="o">.</span><span class="fm">__ne__</span><span class="p">,</span> <span class="n">p</span><span class="p">))))</span>
|
||||
|
||||
<span class="n">forecasts</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">get_models_forecasts</span><span class="p">(</span><span class="n">path</span><span class="p">))</span>
|
||||
|
||||
<span class="n">sample</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">sampler</span><span class="p">(</span><span class="n">forecasts</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mf">0.1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mf">0.1</span><span class="p">)))</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">alpha</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">forecasts</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_distribution_interquantile</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span> <span class="n">alpha</span><span class="p">)</span>
|
||||
|
||||
<span class="n">dist</span> <span class="o">=</span> <span class="n">ProbabilityDistribution</span><span class="o">.</span><span class="n">ProbabilityDistribution</span><span class="p">(</span><span class="n">smooth</span><span class="p">,</span> <span class="n">uod</span><span class="o">=</span><span class="n">uod</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">forecasts</span><span class="p">,</span>
|
||||
<span class="n">name</span><span class="o">=</span><span class="s2">""</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">dist</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="AllMethodEnsembleFTS"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS">[docs]</a><span class="k">class</span> <span class="nc">AllMethodEnsembleFTS</span><span class="p">(</span><span class="n">EnsembleFTS</span><span class="p">):</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">AllMethodEnsembleFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_order</span> <span class="o">=</span> <span class="mi">3</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span><span class="s2">"Ensemble FTS"</span>
|
||||
|
||||
<div class="viewcode-block" id="AllMethodEnsembleFTS.set_transformations"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS.set_transformations">[docs]</a> <span class="k">def</span> <span class="nf">set_transformations</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">model</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">transformations</span><span class="p">:</span>
|
||||
<span class="n">model</span><span class="o">.</span><span class="n">append_transformation</span><span class="p">(</span><span class="n">t</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="AllMethodEnsembleFTS.train"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.AllMethodEnsembleFTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">fo_methods</span> <span class="o">=</span> <span class="p">[</span><span class="n">song</span><span class="o">.</span><span class="n">ConventionalFTS</span><span class="p">,</span> <span class="n">chen</span><span class="o">.</span><span class="n">ConventionalFTS</span><span class="p">,</span> <span class="n">yu</span><span class="o">.</span><span class="n">WeightedFTS</span><span class="p">,</span> <span class="n">cheng</span><span class="o">.</span><span class="n">TrendWeightedFTS</span><span class="p">,</span>
|
||||
<span class="n">sadaei</span><span class="o">.</span><span class="n">ExponentialyWeightedFTS</span><span class="p">,</span> <span class="n">ismailefendi</span><span class="o">.</span><span class="n">ImprovedWeightedFTS</span><span class="p">]</span>
|
||||
|
||||
<span class="n">ho_methods</span> <span class="o">=</span> <span class="p">[</span><span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">,</span> <span class="n">hwang</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">method</span> <span class="ow">in</span> <span class="n">fo_methods</span><span class="p">:</span>
|
||||
<span class="n">model</span> <span class="o">=</span> <span class="n">method</span><span class="p">(</span><span class="n">partitioner</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">set_transformations</span><span class="p">(</span><span class="n">model</span><span class="p">)</span>
|
||||
<span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">append_model</span><span class="p">(</span><span class="n">model</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">method</span> <span class="ow">in</span> <span class="n">ho_methods</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="o">+</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="n">model</span> <span class="o">=</span> <span class="n">method</span><span class="p">(</span><span class="n">partitioner</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">model</span><span class="o">.</span><span class="n">min_order</span> <span class="o">>=</span> <span class="n">o</span><span class="p">:</span>
|
||||
<span class="n">model</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="n">o</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">set_transformations</span><span class="p">(</span><span class="n">model</span><span class="p">)</span>
|
||||
<span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">append_model</span><span class="p">(</span><span class="n">model</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
|
||||
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
||||
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|
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<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
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<h3>Related Topics</h3>
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<li><a href="../../../../index.html">Documentation overview</a><ul>
|
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|
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<h3>Quick search</h3>
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169
docs/_build/html/_modules/pyFTS/models/ensemble/multiseasonal.html
vendored
Normal file
169
docs/_build/html/_modules/pyFTS/models/ensemble/multiseasonal.html
vendored
Normal file
@ -0,0 +1,169 @@
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<title>pyFTS.models.ensemble.multiseasonal — pyFTS 1.2.3 documentation</title>
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<h1>Source code for pyFTS.models.ensemble.multiseasonal</h1><div class="highlight"><pre>
|
||||
<span></span><span class="ch">#!/usr/bin/python</span>
|
||||
<span class="c1"># -*- coding: utf8 -*-</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Util</span> <span class="k">as</span> <span class="n">cUtil</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models.ensemble</span> <span class="k">import</span> <span class="n">ensemble</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models.seasonal</span> <span class="k">import</span> <span class="n">cmsfts</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">ProbabilityDistribution</span>
|
||||
<span class="kn">from</span> <span class="nn">copy</span> <span class="k">import</span> <span class="n">deepcopy</span>
|
||||
<span class="kn">from</span> <span class="nn">joblib</span> <span class="k">import</span> <span class="n">Parallel</span><span class="p">,</span> <span class="n">delayed</span>
|
||||
<span class="kn">import</span> <span class="nn">multiprocessing</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="train_individual_model"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.multiseasonal.train_individual_model">[docs]</a><span class="k">def</span> <span class="nf">train_individual_model</span><span class="p">(</span><span class="n">partitioner</span><span class="p">,</span> <span class="n">train_data</span><span class="p">,</span> <span class="n">indexer</span><span class="p">):</span>
|
||||
<span class="n">pttr</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="vm">__module__</span><span class="p">)</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">'.'</span><span class="p">)[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
|
||||
<span class="n">diff</span> <span class="o">=</span> <span class="s2">"_diff"</span> <span class="k">if</span> <span class="n">partitioner</span><span class="o">.</span><span class="n">transformation</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="k">else</span> <span class="s2">""</span>
|
||||
<span class="n">_key</span> <span class="o">=</span> <span class="s2">"msfts_"</span> <span class="o">+</span> <span class="n">pttr</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="n">partitions</span><span class="p">)</span> <span class="o">+</span> <span class="n">diff</span> <span class="o">+</span> <span class="s2">"_"</span> <span class="o">+</span> <span class="n">indexer</span><span class="o">.</span><span class="n">name</span>
|
||||
|
||||
<span class="nb">print</span><span class="p">(</span><span class="n">_key</span><span class="p">)</span>
|
||||
|
||||
<span class="n">model</span> <span class="o">=</span> <span class="n">cmsfts</span><span class="o">.</span><span class="n">ContextualMultiSeasonalFTS</span><span class="p">(</span><span class="n">_key</span><span class="p">,</span> <span class="n">indexer</span><span class="o">=</span><span class="n">indexer</span><span class="p">)</span>
|
||||
<span class="n">model</span><span class="o">.</span><span class="n">append_transformation</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="n">transformation</span><span class="p">)</span>
|
||||
<span class="n">model</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="n">train_data</span><span class="p">,</span> <span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">order</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
|
||||
|
||||
<span class="n">cUtil</span><span class="o">.</span><span class="n">persist_obj</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="s2">"models/"</span><span class="o">+</span><span class="n">_key</span><span class="o">+</span><span class="s2">".pkl"</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">model</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="SeasonalEnsembleFTS"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS">[docs]</a><span class="k">class</span> <span class="nc">SeasonalEnsembleFTS</span><span class="p">(</span><span class="n">ensemble</span><span class="o">.</span><span class="n">EnsembleFTS</span><span class="p">):</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">SeasonalEnsembleFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Seasonal Ensemble FTS"</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_order</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">indexers</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">partitioners</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_multivariate</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_seasonality</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_probability_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
|
||||
<div class="viewcode-block" id="SeasonalEnsembleFTS.update_uod"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS.update_uod">[docs]</a> <span class="k">def</span> <span class="nf">update_uod</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">original_max</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_data</span><span class="p">(</span><span class="n">data</span><span class="p">))</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">original_min</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_data</span><span class="p">(</span><span class="n">data</span><span class="p">))</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SeasonalEnsembleFTS.train"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">original_max</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_data</span><span class="p">(</span><span class="n">data</span><span class="p">))</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">original_min</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_data</span><span class="p">(</span><span class="n">data</span><span class="p">))</span>
|
||||
|
||||
<span class="n">num_cores</span> <span class="o">=</span> <span class="n">multiprocessing</span><span class="o">.</span><span class="n">cpu_count</span><span class="p">()</span>
|
||||
|
||||
<span class="n">pool</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="n">count</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">ix</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexers</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">pt</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioners</span><span class="p">:</span>
|
||||
<span class="n">pool</span><span class="p">[</span><span class="n">count</span><span class="p">]</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'ix'</span><span class="p">:</span> <span class="n">ix</span><span class="p">,</span> <span class="s1">'pt'</span><span class="p">:</span> <span class="n">pt</span><span class="p">}</span>
|
||||
<span class="n">count</span> <span class="o">+=</span> <span class="mi">1</span>
|
||||
|
||||
<span class="n">results</span> <span class="o">=</span> <span class="n">Parallel</span><span class="p">(</span><span class="n">n_jobs</span><span class="o">=</span><span class="n">num_cores</span><span class="p">)(</span>
|
||||
<span class="n">delayed</span><span class="p">(</span><span class="n">train_individual_model</span><span class="p">)(</span><span class="n">deepcopy</span><span class="p">(</span><span class="n">pool</span><span class="p">[</span><span class="n">m</span><span class="p">][</span><span class="s1">'pt'</span><span class="p">]),</span> <span class="n">data</span><span class="p">,</span> <span class="n">deepcopy</span><span class="p">(</span><span class="n">pool</span><span class="p">[</span><span class="n">m</span><span class="p">][</span><span class="s1">'ix'</span><span class="p">]))</span>
|
||||
<span class="k">for</span> <span class="n">m</span> <span class="ow">in</span> <span class="n">pool</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">tmp</span> <span class="ow">in</span> <span class="n">results</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">append_model</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
|
||||
<span class="n">cUtil</span><span class="o">.</span><span class="n">persist_obj</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="s2">"models/"</span><span class="o">+</span><span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="o">+</span><span class="s2">".pkl"</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SeasonalEnsembleFTS.forecast_distribution"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.multiseasonal.SeasonalEnsembleFTS.forecast_distribution">[docs]</a> <span class="k">def</span> <span class="nf">forecast_distribution</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">smooth</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"smooth"</span><span class="p">,</span> <span class="s2">"KDE"</span><span class="p">)</span>
|
||||
<span class="n">alpha</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"alpha"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="n">uod</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_UoD</span><span class="p">()</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">data</span><span class="o">.</span><span class="n">index</span><span class="p">:</span>
|
||||
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_models_forecasts</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">ix</span><span class="p">[</span><span class="n">k</span><span class="p">])</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">alpha</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_distribution_interquantile</span><span class="p">(</span> <span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span><span class="o">.</span><span class="n">tolist</span><span class="p">(),</span> <span class="n">alpha</span><span class="p">)</span>
|
||||
|
||||
<span class="n">name</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_index</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">ix</span><span class="p">[</span><span class="n">k</span><span class="p">]))</span>
|
||||
|
||||
<span class="n">dist</span> <span class="o">=</span> <span class="n">ProbabilityDistribution</span><span class="o">.</span><span class="n">ProbabilityDistribution</span><span class="p">(</span><span class="n">smooth</span><span class="p">,</span> <span class="n">uod</span><span class="o">=</span><span class="n">uod</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">tmp</span><span class="p">,</span>
|
||||
<span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">dist</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
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|
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<li><a href="../../../../index.html">Documentation overview</a><ul>
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216
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vendored
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<h1>Source code for pyFTS.models.hofts</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">High Order FTS</span>
|
||||
|
||||
<span class="sd">Severiano, S. A. Jr; Silva, P. C. L.; Sadaei, H. J.; Guimarães, F. G. Very Short-term Solar Forecasting</span>
|
||||
<span class="sd">using Fuzzy Time Series. 2017 IEEE International Conference on Fuzzy Systems. DOI10.1109/FUZZ-IEEE.2017.8015732</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span><span class="p">,</span> <span class="n">tree</span>
|
||||
|
||||
<div class="viewcode-block" id="HighOrderFLRG"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.HighOrderFLRG">[docs]</a><span class="k">class</span> <span class="nc">HighOrderFLRG</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">):</span>
|
||||
<span class="sd">"""Conventional High Order Fuzzy Logical Relationship Group"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">HighOrderFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">strlhs</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
|
||||
<div class="viewcode-block" id="HighOrderFLRG.append_rhs"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.HighOrderFLRG.append_rhs">[docs]</a> <span class="k">def</span> <span class="nf">append_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">c</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="o">=</span> <span class="n">c</span></div>
|
||||
|
||||
<div class="viewcode-block" id="HighOrderFLRG.append_lhs"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.HighOrderFLRG.append_lhs">[docs]</a> <span class="k">def</span> <span class="nf">append_lhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">c</span><span class="p">)</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">tmp</span> <span class="o">+</span> <span class="s2">","</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">tmp</span> <span class="o">+</span> <span class="n">c</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="o">+</span> <span class="s2">" -> "</span> <span class="o">+</span> <span class="n">tmp</span>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="HighOrderFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.HighOrderFTS">[docs]</a><span class="k">class</span> <span class="nc">HighOrderFTS</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
|
||||
<span class="sd">"""Conventional High Order Fuzzy Time Series"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">HighOrderFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"High Order FTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">"HOFTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">"Severiano, Silva, Sadaei and Guimarães"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_order</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"order"</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">lags</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"lags"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">configure_lags</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="HighOrderFTS.configure_lags"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.HighOrderFTS.configure_lags">[docs]</a> <span class="k">def</span> <span class="nf">configure_lags</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="s2">"order"</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"order"</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="s2">"lags"</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">lags</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"lags"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">lags</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">lags</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">lags</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="HighOrderFTS.generate_lhs_flrg"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.HighOrderFTS.generate_lhs_flrg">[docs]</a> <span class="k">def</span> <span class="nf">generate_lhs_flrg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sample</span><span class="p">):</span>
|
||||
<span class="n">lags</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<span class="n">flrgs</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">o</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">lags</span><span class="p">):</span>
|
||||
<span class="n">lhs</span> <span class="o">=</span> <span class="p">[</span><span class="n">key</span> <span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">sample</span><span class="p">[</span><span class="n">o</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span> <span class="o">></span> <span class="bp">self</span><span class="o">.</span><span class="n">alpha_cut</span><span class="p">]</span>
|
||||
<span class="n">lags</span><span class="p">[</span><span class="n">ct</span><span class="p">]</span> <span class="o">=</span> <span class="n">lhs</span>
|
||||
|
||||
<span class="n">root</span> <span class="o">=</span> <span class="n">tree</span><span class="o">.</span><span class="n">FLRGTreeNode</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="n">tree</span><span class="o">.</span><span class="n">build_tree_without_order</span><span class="p">(</span><span class="n">root</span><span class="p">,</span> <span class="n">lags</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
|
||||
|
||||
<span class="c1"># Trace the possible paths</span>
|
||||
<span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">root</span><span class="o">.</span><span class="n">paths</span><span class="p">():</span>
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="n">HighOrderFLRG</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">)</span>
|
||||
<span class="n">path</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">reversed</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">filter</span><span class="p">(</span><span class="kc">None</span><span class="o">.</span><span class="fm">__ne__</span><span class="p">,</span> <span class="n">p</span><span class="p">))))</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">lhs</span> <span class="ow">in</span> <span class="n">path</span><span class="p">:</span>
|
||||
<span class="n">flrg</span><span class="o">.</span><span class="n">append_lhs</span><span class="p">(</span><span class="n">lhs</span><span class="p">)</span>
|
||||
|
||||
<span class="n">flrgs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">flrg</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">flrgs</span></div>
|
||||
|
||||
<div class="viewcode-block" id="HighOrderFTS.generate_flrg"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.HighOrderFTS.generate_flrg">[docs]</a> <span class="k">def</span> <span class="nf">generate_flrg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dump</span><span class="p">:</span> <span class="nb">print</span><span class="p">(</span><span class="s2">"FLR: "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">k</span><span class="p">))</span>
|
||||
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
|
||||
|
||||
<span class="n">rhs</span> <span class="o">=</span> <span class="p">[</span><span class="n">key</span> <span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">k</span><span class="p">])</span> <span class="o">></span> <span class="bp">self</span><span class="o">.</span><span class="n">alpha_cut</span><span class="p">]</span>
|
||||
|
||||
<span class="n">flrgs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrg</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">flrg</span> <span class="ow">in</span> <span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span> <span class="o">=</span> <span class="n">flrg</span><span class="p">;</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">st</span> <span class="ow">in</span> <span class="n">rhs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">st</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="HighOrderFTS.train"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.HighOrderFTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">configure_lags</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">generate_flrg</span><span class="p">(</span><span class="n">data</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="HighOrderFTS.forecast"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.HighOrderFTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">l</span> <span class="o"><=</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">ndata</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="n">l</span><span class="o">+</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="n">flrgs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrg</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">k</span><span class="p">])</span>
|
||||
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">flrg</span> <span class="ow">in</span> <span class="n">flrgs</span><span class="p">:</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]]</span><span class="o">.</span><span class="n">centroid</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">))</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">nanmean</span><span class="p">(</span><span class="n">tmp</span><span class="p">))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
||||
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|
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|
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143
docs/_build/html/_modules/pyFTS/models/hwang.html
vendored
Normal file
143
docs/_build/html/_modules/pyFTS/models/hwang.html
vendored
Normal file
@ -0,0 +1,143 @@
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
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<h1>Source code for pyFTS.models.hwang</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">High Order Fuzzy Time Series by Hwang, Chen and Lee (1998)</span>
|
||||
|
||||
<span class="sd">Jeng-Ren Hwang, Shyi-Ming Chen, and Chia-Hoang Lee, “Handling forecasting problems using fuzzy time series,” </span>
|
||||
<span class="sd">Fuzzy Sets Syst., no. 100, pp. 217–228, 1998.</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">Transformations</span><span class="p">,</span> <span class="n">fts</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="HighOrderFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hwang.HighOrderFTS">[docs]</a><span class="k">class</span> <span class="nc">HighOrderFTS</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">HighOrderFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_order</span> <span class="o">=</span> <span class="mi">2</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Hwang High Order FTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">"Hwang"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">"Hwang"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">configure_lags</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="HighOrderFTS.configure_lags"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hwang.HighOrderFTS.configure_lags">[docs]</a> <span class="k">def</span> <span class="nf">configure_lags</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="s2">"order"</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"order"</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span></div>
|
||||
|
||||
<div class="viewcode-block" id="HighOrderFTS.forecast"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hwang.HighOrderFTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
|
||||
<span class="n">cn</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mf">0.0</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">l</span><span class="p">)])</span>
|
||||
<span class="n">ow</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="mf">0.0</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">l</span><span class="p">)]</span> <span class="k">for</span> <span class="n">z</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)])</span>
|
||||
<span class="n">rn</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([[</span><span class="mf">0.0</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">l</span><span class="p">)]</span> <span class="k">for</span> <span class="n">z</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)])</span>
|
||||
<span class="n">ft</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mf">0.0</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">l</span><span class="p">)])</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="o">-</span><span class="mi">1</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)):</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">ix</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">l</span><span class="p">):</span>
|
||||
<span class="n">s</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
|
||||
<span class="n">cn</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">grant_bounds</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">t</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">))</span>
|
||||
<span class="k">for</span> <span class="n">w</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="o">-</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="n">ow</span><span class="p">[</span><span class="n">w</span><span class="p">,</span> <span class="n">ix</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">FuzzySet</span><span class="o">.</span><span class="n">grant_bounds</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">t</span> <span class="o">-</span> <span class="n">w</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">))</span>
|
||||
<span class="n">rn</span><span class="p">[</span><span class="n">w</span><span class="p">,</span> <span class="n">ix</span><span class="p">]</span> <span class="o">=</span> <span class="n">ow</span><span class="p">[</span><span class="n">w</span><span class="p">,</span> <span class="n">ix</span><span class="p">]</span> <span class="o">*</span> <span class="n">cn</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
|
||||
<span class="n">ft</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">ft</span><span class="p">[</span><span class="n">ix</span><span class="p">],</span> <span class="n">rn</span><span class="p">[</span><span class="n">w</span><span class="p">,</span> <span class="n">ix</span><span class="p">])</span>
|
||||
<span class="n">mft</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">ft</span><span class="p">)</span>
|
||||
<span class="n">out</span> <span class="o">=</span> <span class="mf">0.0</span>
|
||||
<span class="n">count</span> <span class="o">=</span> <span class="mf">0.0</span>
|
||||
<span class="k">for</span> <span class="n">ix</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">l</span><span class="p">):</span>
|
||||
<span class="n">s</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="n">ft</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span> <span class="o">==</span> <span class="n">mft</span><span class="p">:</span>
|
||||
<span class="n">out</span> <span class="o">=</span> <span class="n">out</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span>
|
||||
<span class="n">count</span> <span class="o">+=</span> <span class="mf">1.0</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">out</span> <span class="o">/</span> <span class="n">count</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="HighOrderFTS.train"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hwang.HighOrderFTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">==</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">configure_lags</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
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|
||||
<li><a href="../../../index.html">Documentation overview</a><ul>
|
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<li><a href="../../index.html">Module code</a><ul>
|
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|
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|
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|
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<h3>Quick search</h3>
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©2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
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167
docs/_build/html/_modules/pyFTS/models/ifts.html
vendored
Normal file
167
docs/_build/html/_modules/pyFTS/models/ifts.html
vendored
Normal file
@ -0,0 +1,167 @@
|
||||
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
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||||
<h1>Source code for pyFTS.models.ifts</h1><div class="highlight"><pre>
|
||||
<span></span><span class="ch">#!/usr/bin/python</span>
|
||||
<span class="c1"># -*- coding: utf8 -*-</span>
|
||||
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd">High Order Interval Fuzzy Time Series</span>
|
||||
|
||||
<span class="sd">SILVA, Petrônio CL; SADAEI, Hossein Javedani; GUIMARÃES, Frederico Gadelha. Interval Forecasting with Fuzzy Time Series.</span>
|
||||
<span class="sd">In: Computational Intelligence (SSCI), 2016 IEEE Symposium Series on. IEEE, 2016. p. 1-8.</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">tree</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="IntervalFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ifts.IntervalFTS">[docs]</a><span class="k">class</span> <span class="nc">IntervalFTS</span><span class="p">(</span><span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> High Order Interval Fuzzy Time Series</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">IntervalFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">"IFTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Interval FTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">"Silva, P.; Guimarães, F.; Sadaei, H. (2016)"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_point_forecasting</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_interval_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_order</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
|
||||
<div class="viewcode-block" id="IntervalFTS.get_upper"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ifts.IntervalFTS.get_upper">[docs]</a> <span class="k">def</span> <span class="nf">get_upper</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrg</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]]</span><span class="o">.</span><span class="n">upper</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="IntervalFTS.get_lower"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ifts.IntervalFTS.get_lower">[docs]</a> <span class="k">def</span> <span class="nf">get_lower</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrg</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]]</span><span class="o">.</span><span class="n">lower</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="IntervalFTS.get_sequence_membership"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ifts.IntervalFTS.get_sequence_membership">[docs]</a> <span class="k">def</span> <span class="nf">get_sequence_membership</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">fuzzySets</span><span class="p">):</span>
|
||||
<span class="n">mb</span> <span class="o">=</span> <span class="p">[</span><span class="n">fuzzySets</span><span class="p">[</span><span class="n">k</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">k</span><span class="p">])</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">))]</span>
|
||||
<span class="k">return</span> <span class="n">mb</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="IntervalFTS.forecast_interval"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ifts.IntervalFTS.forecast_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">l</span> <span class="o"><=</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">ndata</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="n">l</span><span class="o">+</span><span class="mi">1</span><span class="p">):</span>
|
||||
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">ndata</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
|
||||
|
||||
<span class="n">flrgs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrg</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
|
||||
<span class="n">up</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">lo</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">affected_flrgs_memberships</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">flrg</span> <span class="ow">in</span> <span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="c1"># achar o os bounds de cada FLRG, ponderados pela pertinência</span>
|
||||
<span class="n">mv</span> <span class="o">=</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_membership</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
<span class="n">up</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mv</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">flrg</span><span class="p">))</span>
|
||||
<span class="n">lo</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mv</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">flrg</span><span class="p">))</span>
|
||||
<span class="n">affected_flrgs_memberships</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mv</span><span class="p">)</span>
|
||||
|
||||
<span class="c1"># gerar o intervalo</span>
|
||||
<span class="n">norm</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">affected_flrgs_memberships</span><span class="p">)</span>
|
||||
<span class="n">lo_</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">lo</span><span class="p">)</span> <span class="o">/</span> <span class="n">norm</span>
|
||||
<span class="n">up_</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">up</span><span class="p">)</span> <span class="o">/</span> <span class="n">norm</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="n">lo_</span><span class="p">,</span> <span class="n">up_</span><span class="p">])</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
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|
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<li><a href="../../../index.html">Documentation overview</a><ul>
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172
docs/_build/html/_modules/pyFTS/models/ismailefendi.html
vendored
Normal file
172
docs/_build/html/_modules/pyFTS/models/ismailefendi.html
vendored
Normal file
@ -0,0 +1,172 @@
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
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<h1>Source code for pyFTS.models.ismailefendi</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">First Order Improved Weighted Fuzzy Time Series by Efendi, Ismail and Deris (2013)</span>
|
||||
|
||||
<span class="sd">R. Efendi, Z. Ismail, and M. M. Deris, “Improved weight Fuzzy Time Series as used in the exchange rates forecasting of </span>
|
||||
<span class="sd">US Dollar to Ringgit Malaysia,” Int. J. Comput. Intell. Appl., vol. 12, no. 1, p. 1350005, 2013.</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ImprovedWeightedFLRG"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ismailefendi.ImprovedWeightedFLRG">[docs]</a><span class="k">class</span> <span class="nc">ImprovedWeightedFLRG</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">):</span>
|
||||
<span class="sd">"""First Order Improved Weighted Fuzzy Logical Relationship Group"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">ImprovedWeightedFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="n">LHS</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">rhs_counts</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="o">=</span> <span class="mf">0.0</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
|
||||
<div class="viewcode-block" id="ImprovedWeightedFLRG.append_rhs"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ismailefendi.ImprovedWeightedFLRG.append_rhs">[docs]</a> <span class="k">def</span> <span class="nf">append_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">c</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="o">=</span> <span class="n">c</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">rhs_counts</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="o">=</span> <span class="mf">1.0</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">rhs_counts</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="o">+=</span> <span class="mf">1.0</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="o">+=</span> <span class="mf">1.0</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ImprovedWeightedFLRG.weights"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ismailefendi.ImprovedWeightedFLRG.weights">[docs]</a> <span class="k">def</span> <span class="nf">weights</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">rhs_counts</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()])</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">w</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">+</span> <span class="s2">" -> "</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()):</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">tmp2</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="n">tmp2</span> <span class="o">+</span> <span class="s2">","</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="n">tmp2</span> <span class="o">+</span> <span class="n">c</span> <span class="o">+</span> <span class="s2">"("</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">rhs_counts</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">count</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span> <span class="o">+</span> <span class="s2">")"</span>
|
||||
<span class="k">return</span> <span class="n">tmp</span> <span class="o">+</span> <span class="n">tmp2</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ImprovedWeightedFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ismailefendi.ImprovedWeightedFTS">[docs]</a><span class="k">class</span> <span class="nc">ImprovedWeightedFTS</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
|
||||
<span class="sd">"""First Order Improved Weighted Fuzzy Time Series"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">ImprovedWeightedFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">"IWFTS"</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Improved Weighted FTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">"Ismail & Efendi"</span>
|
||||
|
||||
<div class="viewcode-block" id="ImprovedWeightedFTS.generate_flrg"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ismailefendi.ImprovedWeightedFTS.generate_flrg">[docs]</a> <span class="k">def</span> <span class="nf">generate_flrg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrs</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">flr</span> <span class="ow">in</span> <span class="n">flrs</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">flr</span><span class="o">.</span><span class="n">LHS</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span> <span class="o">=</span> <span class="n">ImprovedWeightedFLRG</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">);</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ImprovedWeightedFTS.train"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ismailefendi.ImprovedWeightedFTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">tmpdata</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">fuzzyfy_series</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s1">'maximum'</span><span class="p">)</span>
|
||||
<span class="n">flrs</span> <span class="o">=</span> <span class="n">FLR</span><span class="o">.</span><span class="n">generate_recurrent_flrs</span><span class="p">(</span><span class="n">tmpdata</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">generate_flrg</span><span class="p">(</span><span class="n">flrs</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ImprovedWeightedFTS.forecast"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ismailefendi.ImprovedWeightedFTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">ordered_sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ordered_sets</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">set_ordered</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
|
||||
<span class="n">actual</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">get_maximum_membership_fuzzyset</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">actual</span><span class="o">.</span><span class="n">name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">actual</span><span class="o">.</span><span class="n">centroid</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">actual</span><span class="o">.</span><span class="n">name</span><span class="p">]</span>
|
||||
<span class="n">mp</span> <span class="o">=</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_midpoints</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mp</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">weights</span><span class="p">()))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
||||
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|
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|
||||
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|
||||
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|
||||
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|
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|
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|
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|
||||
<h3>Quick search</h3>
|
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|
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103
docs/_build/html/_modules/pyFTS/models/multivariate/FLR.html
vendored
Normal file
103
docs/_build/html/_modules/pyFTS/models/multivariate/FLR.html
vendored
Normal file
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|
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
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|
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||||
<h1>Source code for pyFTS.models.multivariate.FLR</h1><div class="highlight"><pre>
|
||||
<span></span>
|
||||
|
||||
<div class="viewcode-block" id="FLR"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.FLR.FLR">[docs]</a><span class="k">class</span> <span class="nc">FLR</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
|
||||
<span class="sd">"""Multivariate Fuzzy Logical Relationship"""</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Creates a Fuzzy Logical Relationship</span>
|
||||
<span class="sd"> :param LHS: Left Hand Side fuzzy set</span>
|
||||
<span class="sd"> :param RHS: Right Hand Side fuzzy set</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
|
||||
<div class="viewcode-block" id="FLR.set_lhs"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.FLR.FLR.set_lhs">[docs]</a> <span class="k">def</span> <span class="nf">set_lhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">var</span><span class="p">,</span> <span class="nb">set</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="n">var</span><span class="p">]</span> <span class="o">=</span> <span class="nb">set</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FLR.set_rhs"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.FLR.FLR.set_rhs">[docs]</a> <span class="k">def</span> <span class="nf">set_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="nb">set</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="nb">set</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">str</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()])</span> <span class="o">+</span> <span class="s2">" -> "</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span></div>
|
||||
|
||||
|
||||
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
||||
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|
||||
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|
||||
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|
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|
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|
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|
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|
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|
||||
89
docs/_build/html/_modules/pyFTS/models/multivariate/common.html
vendored
Normal file
89
docs/_build/html/_modules/pyFTS/models/multivariate/common.html
vendored
Normal file
@ -0,0 +1,89 @@
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|
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
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|
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|
||||
<h1>Source code for pyFTS.models.multivariate.common</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="fuzzyfy_instance"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.common.fuzzyfy_instance">[docs]</a><span class="k">def</span> <span class="nf">fuzzyfy_instance</span><span class="p">(</span><span class="n">data_point</span><span class="p">,</span> <span class="n">var</span><span class="p">):</span>
|
||||
<span class="n">mv</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">var</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">data_point</span><span class="p">)</span> <span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">var</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">])</span>
|
||||
<span class="n">ix</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">mv</span> <span class="o">></span> <span class="n">var</span><span class="o">.</span><span class="n">alpha_cut</span><span class="p">))</span>
|
||||
<span class="n">sets</span> <span class="o">=</span> <span class="p">[(</span><span class="n">var</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="n">var</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">ix</span><span class="p">]</span>
|
||||
<span class="k">return</span> <span class="n">sets</span></div>
|
||||
|
||||
|
||||
</pre></div>
|
||||
|
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|
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|
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121
docs/_build/html/_modules/pyFTS/models/multivariate/flrg.html
vendored
Normal file
121
docs/_build/html/_modules/pyFTS/models/multivariate/flrg.html
vendored
Normal file
@ -0,0 +1,121 @@
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|
||||
|
||||
<h1>Source code for pyFTS.models.multivariate.flrg</h1><div class="highlight"><pre>
|
||||
<span></span>
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">flrg</span> <span class="k">as</span> <span class="n">flg</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="FLRG"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.flrg.FLRG">[docs]</a><span class="k">class</span> <span class="nc">FLRG</span><span class="p">(</span><span class="n">flg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Multivariate Fuzzy Logical Rule Group</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">FLRG</span><span class="p">,</span><span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'order'</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'lhs'</span><span class="p">,</span> <span class="p">{})</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span>
|
||||
|
||||
<div class="viewcode-block" id="FLRG.set_lhs"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.flrg.FLRG.set_lhs">[docs]</a> <span class="k">def</span> <span class="nf">set_lhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">var</span><span class="p">,</span> <span class="n">fset</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="n">var</span><span class="p">]</span> <span class="o">=</span> <span class="n">fset</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">var</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="n">var</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="n">var</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">fset</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="FLRG.append_rhs"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.flrg.FLRG.append_rhs">[docs]</a> <span class="k">def</span> <span class="nf">append_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">fset</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">fset</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FLRG.get_membership"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.flrg.FLRG.get_membership">[docs]</a> <span class="k">def</span> <span class="nf">get_membership</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">variables</span><span class="p">):</span>
|
||||
<span class="n">mvs</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">var</span> <span class="ow">in</span> <span class="n">variables</span><span class="p">:</span>
|
||||
<span class="n">s</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="n">var</span><span class="o">.</span><span class="n">name</span><span class="p">]</span>
|
||||
<span class="n">mvs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">var</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">var</span><span class="o">.</span><span class="n">name</span><span class="p">]))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmin</span><span class="p">(</span><span class="n">mvs</span><span class="p">)</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">_str</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">:</span>
|
||||
<span class="n">_str</span> <span class="o">+=</span> <span class="s2">","</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">_str</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="s2">""</span>
|
||||
<span class="n">_str</span> <span class="o">+=</span> <span class="n">k</span>
|
||||
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="o">+</span> <span class="s2">" -> "</span> <span class="o">+</span> <span class="n">_str</span></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
||||
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|
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<li><a href="../../../../index.html">Documentation overview</a><ul>
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<li><a href="../../../index.html">Module code</a><ul>
|
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<h3>Quick search</h3>
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<h1>Source code for pyFTS.models.multivariate.mvfts</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">fts</span><span class="p">,</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">tree</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="k">import</span> <span class="n">FLR</span> <span class="k">as</span> <span class="n">MVFLR</span><span class="p">,</span> <span class="n">common</span><span class="p">,</span> <span class="n">flrg</span> <span class="k">as</span> <span class="n">mvflrg</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="MVFTS"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS">[docs]</a><span class="k">class</span> <span class="nc">MVFTS</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Multivariate extension of Chen's ConventionalFTS method</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">MVFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">explanatory_variables</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">target_variable</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_multivariate</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">"MVFTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Multivariate FTS"</span>
|
||||
|
||||
<div class="viewcode-block" id="MVFTS.append_variable"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.append_variable">[docs]</a> <span class="k">def</span> <span class="nf">append_variable</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">var</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Append a new endogenous variable to the model</span>
|
||||
|
||||
<span class="sd"> :param var: variable object</span>
|
||||
<span class="sd"> :return:</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">explanatory_variables</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">var</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="MVFTS.format_data"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.format_data">[docs]</a> <span class="k">def</span> <span class="nf">format_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="k">for</span> <span class="n">var</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">explanatory_variables</span><span class="p">:</span>
|
||||
<span class="n">ndata</span><span class="p">[</span><span class="n">var</span><span class="o">.</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">var</span><span class="o">.</span><span class="n">data_label</span><span class="p">]</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ndata</span></div>
|
||||
|
||||
<div class="viewcode-block" id="MVFTS.apply_transformations"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.apply_transformations">[docs]</a> <span class="k">def</span> <span class="nf">apply_transformations</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">params</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">updateUoD</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">copy</span><span class="p">(</span><span class="n">deep</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">var</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">explanatory_variables</span><span class="p">:</span>
|
||||
<span class="n">ndata</span><span class="p">[</span><span class="n">var</span><span class="o">.</span><span class="n">data_label</span><span class="p">]</span> <span class="o">=</span> <span class="n">var</span><span class="o">.</span><span class="n">apply_transformations</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">var</span><span class="o">.</span><span class="n">data_label</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ndata</span></div>
|
||||
|
||||
<div class="viewcode-block" id="MVFTS.generate_lhs_flrs"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_lhs_flrs">[docs]</a> <span class="k">def</span> <span class="nf">generate_lhs_flrs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="n">flrs</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">lags</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="k">for</span> <span class="n">vc</span><span class="p">,</span> <span class="n">var</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">explanatory_variables</span><span class="p">):</span>
|
||||
<span class="n">data_point</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">var</span><span class="o">.</span><span class="n">data_label</span><span class="p">]</span>
|
||||
<span class="n">lags</span><span class="p">[</span><span class="n">vc</span><span class="p">]</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">fuzzyfy_instance</span><span class="p">(</span><span class="n">data_point</span><span class="p">,</span> <span class="n">var</span><span class="p">)</span>
|
||||
|
||||
<span class="n">root</span> <span class="o">=</span> <span class="n">tree</span><span class="o">.</span><span class="n">FLRGTreeNode</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="n">tree</span><span class="o">.</span><span class="n">build_tree_without_order</span><span class="p">(</span><span class="n">root</span><span class="p">,</span> <span class="n">lags</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">root</span><span class="o">.</span><span class="n">paths</span><span class="p">():</span>
|
||||
<span class="n">path</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">reversed</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">filter</span><span class="p">(</span><span class="kc">None</span><span class="o">.</span><span class="fm">__ne__</span><span class="p">,</span> <span class="n">p</span><span class="p">))))</span>
|
||||
|
||||
<span class="n">flr</span> <span class="o">=</span> <span class="n">MVFLR</span><span class="o">.</span><span class="n">FLR</span><span class="p">()</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">v</span><span class="p">,</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">path</span><span class="p">:</span>
|
||||
<span class="n">flr</span><span class="o">.</span><span class="n">set_lhs</span><span class="p">(</span><span class="n">v</span><span class="p">,</span> <span class="n">s</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">explanatory_variables</span><span class="p">):</span>
|
||||
<span class="n">flrs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">flr</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">flrs</span></div>
|
||||
|
||||
<div class="viewcode-block" id="MVFTS.generate_flrs"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_flrs">[docs]</a> <span class="k">def</span> <span class="nf">generate_flrs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="n">flrs</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">ct</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">index</span><span class="p">)):</span>
|
||||
<span class="n">ix</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">index</span><span class="p">[</span><span class="n">ct</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
|
||||
<span class="n">data_point</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
|
||||
|
||||
<span class="n">tmp_flrs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrs</span><span class="p">(</span><span class="n">data_point</span><span class="p">)</span>
|
||||
|
||||
<span class="n">target_ix</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">index</span><span class="p">[</span><span class="n">ct</span><span class="p">]</span>
|
||||
<span class="n">target_point</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">target_variable</span><span class="o">.</span><span class="n">data_label</span><span class="p">][</span><span class="n">target_ix</span><span class="p">]</span>
|
||||
<span class="n">target</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">fuzzyfy_instance</span><span class="p">(</span><span class="n">target_point</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">target_variable</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">flr</span> <span class="ow">in</span> <span class="n">tmp_flrs</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">v</span><span class="p">,</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">target</span><span class="p">:</span>
|
||||
<span class="n">flr</span><span class="o">.</span><span class="n">set_rhs</span><span class="p">(</span><span class="n">s</span><span class="p">)</span>
|
||||
<span class="n">flrs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">flr</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">flrs</span></div>
|
||||
|
||||
<div class="viewcode-block" id="MVFTS.generate_flrg"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_flrg">[docs]</a> <span class="k">def</span> <span class="nf">generate_flrg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrs</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">flr</span> <span class="ow">in</span> <span class="n">flrs</span><span class="p">:</span>
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="n">mvflrg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">(</span><span class="n">lhs</span><span class="o">=</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span> <span class="o">=</span> <span class="n">flrg</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="MVFTS.train"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">apply_transformations</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="n">flrs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_flrs</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">generate_flrg</span><span class="p">(</span><span class="n">flrs</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="MVFTS.forecast"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">apply_transformations</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">ix</span> <span class="ow">in</span> <span class="n">ndata</span><span class="o">.</span><span class="n">index</span><span class="p">:</span>
|
||||
<span class="n">data_point</span> <span class="o">=</span> <span class="n">ndata</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
|
||||
<span class="n">flrs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrs</span><span class="p">(</span><span class="n">data_point</span><span class="p">)</span>
|
||||
<span class="n">mvs</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">mps</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">flr</span> <span class="ow">in</span> <span class="n">flrs</span><span class="p">:</span>
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="n">mvflrg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">(</span><span class="n">lhs</span><span class="o">=</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="c1">#print('hit')</span>
|
||||
<span class="n">mvs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mf">0.</span><span class="p">)</span>
|
||||
<span class="n">mps</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mf">0.</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">mvs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">get_membership</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">format_data</span><span class="p">(</span><span class="n">data_point</span><span class="p">),</span> <span class="bp">self</span><span class="o">.</span><span class="n">explanatory_variables</span><span class="p">))</span>
|
||||
<span class="n">mps</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">target_variable</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">))</span>
|
||||
|
||||
<span class="c1">#print('mv', mvs)</span>
|
||||
<span class="c1">#print('mp', mps)</span>
|
||||
<span class="n">mv</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">mvs</span><span class="p">)</span>
|
||||
<span class="n">mp</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">mps</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">mv</span><span class="p">,</span><span class="n">mp</span><span class="o">.</span><span class="n">T</span><span class="p">)</span><span class="o">/</span><span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">mv</span><span class="p">))</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">target_variable</span><span class="o">.</span><span class="n">apply_inverse_transformations</span><span class="p">(</span><span class="n">ret</span><span class="p">,</span>
|
||||
<span class="n">params</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">target_variable</span><span class="o">.</span><span class="n">data_label</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="MVFTS.clone_parameters"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.clone_parameters">[docs]</a> <span class="k">def</span> <span class="nf">clone_parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">model</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">MVFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">clone_parameters</span><span class="p">(</span><span class="n">model</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">explanatory_variables</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">explanatory_variables</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">target_variable</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">target_variable</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">_str</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">+</span> <span class="s2">":</span><span class="se">\n</span><span class="s2">"</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
|
||||
<span class="n">_str</span> <span class="o">+=</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">k</span><span class="p">])</span> <span class="o">+</span> <span class="s2">"</span><span class="se">\n</span><span class="s2">"</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">_str</span></div>
|
||||
|
||||
|
||||
</pre></div>
|
||||
|
||||
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|
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<h1>Source code for pyFTS.models.multivariate.variable</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">fts</span><span class="p">,</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">tree</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="k">import</span> <span class="n">FLR</span> <span class="k">as</span> <span class="n">MVFLR</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="Variable"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.variable.Variable">[docs]</a><span class="k">class</span> <span class="nc">Variable</span><span class="p">:</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> A variable of a fuzzy time series multivariate model. Each variable contains its own</span>
|
||||
<span class="sd"> transformations and partitioners.</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="sd"> :param name:</span>
|
||||
<span class="sd"> :param \**kwargs: See below</span>
|
||||
|
||||
<span class="sd"> :Keyword Arguments:</span>
|
||||
<span class="sd"> * *alias* -- Alternative name for the variable</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">name</span>
|
||||
<span class="sd">"""A string with the name of the variable"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">alias</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'alias'</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
|
||||
<span class="sd">"""A string with the alias of the variable"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">data_label</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'data_label'</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
|
||||
<span class="sd">"""A string with the column name on DataFrame"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'type'</span><span class="p">,</span> <span class="s1">'common'</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">transformation</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'transformation'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">transformation_params</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'transformation_params'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">alpha_cut</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'alpha_cut'</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'data'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">build</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="Variable.build"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.variable.Variable.build">[docs]</a> <span class="k">def</span> <span class="nf">build</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="sd"> :param kwargs:</span>
|
||||
<span class="sd"> :return:</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">fs</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'partitioner'</span><span class="p">,</span> <span class="n">Grid</span><span class="o">.</span><span class="n">GridPartitioner</span><span class="p">)</span>
|
||||
<span class="n">mf</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'func'</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">)</span>
|
||||
<span class="n">np</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'npart'</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
|
||||
<span class="n">data</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'data'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="n">kw</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'partitioner_specific'</span><span class="p">,</span> <span class="p">{})</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span> <span class="o">=</span> <span class="n">fs</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">data_label</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">,</span> <span class="n">npart</span><span class="o">=</span><span class="n">np</span><span class="p">,</span> <span class="n">func</span><span class="o">=</span><span class="n">mf</span><span class="p">,</span>
|
||||
<span class="n">transformation</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">transformation</span><span class="p">,</span> <span class="n">prefix</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">alias</span><span class="p">,</span>
|
||||
<span class="n">variable</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="o">**</span><span class="n">kw</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">+</span> <span class="s2">" "</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">name</span></div>
|
||||
|
||||
<div class="viewcode-block" id="Variable.apply_transformations"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.variable.Variable.apply_transformations">[docs]</a> <span class="k">def</span> <span class="nf">apply_transformations</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'params'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">transformation_params</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'params'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">transformation</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">transformation</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">transformation_params</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">data</span></div>
|
||||
|
||||
<div class="viewcode-block" id="Variable.apply_inverse_transformations"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.variable.Variable.apply_inverse_transformations">[docs]</a> <span class="k">def</span> <span class="nf">apply_inverse_transformations</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'params'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">transformation_params</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'params'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">transformation</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">transformation</span><span class="o">.</span><span class="n">inverse</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">transformation_params</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">data</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
||||
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|
||||
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||||
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|
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|
||||
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|
||||
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|
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|
||||
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<h3>Quick search</h3>
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||||
<h1>Source code for pyFTS.models.nonstationary.common</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">Non Stationary Fuzzy Sets</span>
|
||||
|
||||
<span class="sd">GARIBALDI, Jonathan M.; JAROSZEWSKI, Marcin; MUSIKASUWAN, Salang. Nonstationary fuzzy sets.</span>
|
||||
<span class="sd">IEEE Transactions on Fuzzy Systems, v. 16, n. 4, p. 1072-1086, 2008.</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="k">import</span> <span class="o">*</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span> <span class="k">as</span> <span class="n">FS</span><span class="p">,</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">FLR</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">partitioner</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="k">import</span> <span class="n">perturbation</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="FuzzySet"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.common.FuzzySet">[docs]</a><span class="k">class</span> <span class="nc">FuzzySet</span><span class="p">(</span><span class="n">FS</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Non Stationary Fuzzy Sets</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">mf</span><span class="p">,</span> <span class="n">parameters</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Constructor</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">FuzzySet</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="n">name</span><span class="p">,</span> <span class="n">mf</span><span class="o">=</span><span class="n">mf</span><span class="p">,</span> <span class="n">parameters</span><span class="o">=</span><span class="n">parameters</span><span class="p">,</span> <span class="n">centroid</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">location</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"location"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="sd">"""Pertubation function that affects the location of the membership function"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">location_params</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"location_params"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="sd">"""Parameters for location pertubation function"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">location_roots</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"location_roots"</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">width</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"width"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="sd">"""Pertubation function that affects the width of the membership function"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">width_params</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"width_params"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="sd">"""Parameters for width pertubation function"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">width_roots</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"width_roots"</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">noise</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"noise"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="sd">"""Pertubation function that adds noise on the membership function"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">noise_params</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"noise_params"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="sd">"""Parameters for noise pertubation function"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">perturbated_parameters</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">=</span> <span class="s1">'nonstationary'</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">location</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">location</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="nb">set</span><span class="p">)):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">location</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">location</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">location_params</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">location_params</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">location_roots</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">location_roots</span><span class="p">]</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">width</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">width</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="nb">set</span><span class="p">)):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">width</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">width</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">width_params</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">width_params</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">width_roots</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">width_roots</span><span class="p">]</span>
|
||||
|
||||
<div class="viewcode-block" id="FuzzySet.perform_location"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.common.FuzzySet.perform_location">[docs]</a> <span class="k">def</span> <span class="nf">perform_location</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">param</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">location</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">inc</span> <span class="o">=</span> <span class="n">t</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">location</span><span class="p">)</span>
|
||||
|
||||
<span class="n">inc</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">location</span><span class="p">[</span><span class="n">k</span><span class="p">](</span><span class="n">t</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">location_roots</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">location_params</span><span class="p">[</span><span class="n">k</span><span class="p">])</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">l</span><span class="p">)])</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">gaussmf</span><span class="p">:</span>
|
||||
<span class="c1"># changes only the mean parameter</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">inc</span><span class="p">,</span> <span class="n">param</span><span class="p">[</span><span class="mi">1</span><span class="p">]]</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">sigmf</span><span class="p">:</span>
|
||||
<span class="c1"># changes only the midpoint parameter</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">param</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="n">inc</span><span class="p">]</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">bellmf</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">param</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">param</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="o">+</span> <span class="n">inc</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="c1"># translate all parameters</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="n">k</span> <span class="o">+</span> <span class="n">inc</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">param</span><span class="p">]</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FuzzySet.perform_width"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.common.FuzzySet.perform_width">[docs]</a> <span class="k">def</span> <span class="nf">perform_width</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">param</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">width</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">inc</span> <span class="o">=</span> <span class="n">t</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">width</span><span class="p">)</span>
|
||||
|
||||
<span class="n">inc</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">width</span><span class="p">[</span><span class="n">k</span><span class="p">](</span><span class="n">t</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">width_roots</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">width_params</span><span class="p">[</span><span class="n">k</span><span class="p">])</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">l</span><span class="p">)])</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">gaussmf</span><span class="p">:</span>
|
||||
<span class="c1"># changes only the variance parameter</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">param</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="n">inc</span><span class="p">]</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">sigmf</span><span class="p">:</span>
|
||||
<span class="c1"># changes only the smooth parameter</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">inc</span><span class="p">,</span> <span class="n">param</span><span class="p">[</span><span class="mi">1</span><span class="p">]]</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">inc</span> <span class="o">/</span> <span class="mi">2</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">-</span> <span class="n">tmp</span><span class="p">,</span> <span class="n">param</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">param</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="o">+</span> <span class="n">tmp</span><span class="p">]</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span><span class="p">:</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="p">(</span><span class="n">param</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span> <span class="o">-</span> <span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
|
||||
<span class="n">rab</span> <span class="o">=</span> <span class="p">(</span><span class="n">param</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="o">/</span> <span class="n">l</span>
|
||||
<span class="n">rcd</span> <span class="o">=</span> <span class="p">(</span><span class="n">param</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span> <span class="o">-</span> <span class="n">param</span><span class="p">[</span><span class="mi">2</span><span class="p">])</span> <span class="o">/</span> <span class="n">l</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">-</span> <span class="n">inc</span><span class="p">,</span> <span class="n">param</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">inc</span> <span class="o">*</span> <span class="n">rab</span><span class="p">,</span> <span class="n">param</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="o">+</span> <span class="n">inc</span> <span class="o">*</span> <span class="n">rcd</span><span class="p">,</span> <span class="n">param</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span> <span class="o">+</span> <span class="n">inc</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">param</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FuzzySet.membership"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.common.FuzzySet.membership">[docs]</a> <span class="k">def</span> <span class="nf">membership</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="n">t</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Calculate the membership value of a given input</span>
|
||||
|
||||
<span class="sd"> :param x: input value</span>
|
||||
<span class="sd"> :param t: time displacement or perturbation parameters</span>
|
||||
<span class="sd"> :return: membership value of x at this fuzzy set</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">perturbate_parameters</span><span class="p">(</span><span class="n">t</span><span class="p">)</span>
|
||||
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">perturbated_parameters</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">t</span><span class="p">)])</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">noise</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">noise</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">noise_params</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">tmp</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FuzzySet.perturbate_parameters"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.common.FuzzySet.perturbate_parameters">[docs]</a> <span class="k">def</span> <span class="nf">perturbate_parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">t</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">str</span><span class="p">(</span><span class="n">t</span><span class="p">)</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">perturbated_parameters</span><span class="p">:</span>
|
||||
<span class="n">param</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">parameters</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="nb">set</span><span class="p">)):</span>
|
||||
<span class="n">param</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">perform_location</span><span class="p">(</span><span class="n">t</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">param</span><span class="p">)</span>
|
||||
<span class="n">param</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">perform_width</span><span class="p">(</span><span class="n">t</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">param</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">param</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">perform_location</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="n">param</span><span class="p">)</span>
|
||||
<span class="n">param</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">perform_width</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="n">param</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">perturbated_parameters</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">t</span><span class="p">)]</span> <span class="o">=</span> <span class="n">param</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FuzzySet.get_midpoint"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.common.FuzzySet.get_midpoint">[docs]</a> <span class="k">def</span> <span class="nf">get_midpoint</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">t</span><span class="p">):</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">perturbate_parameters</span><span class="p">(</span><span class="n">t</span><span class="p">)</span>
|
||||
<span class="n">param</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">perturbated_parameters</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">t</span><span class="p">)]</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">gaussmf</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">sigmf</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">param</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">param</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="p">(</span><span class="n">param</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="o">-</span> <span class="n">param</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span> <span class="o">/</span> <span class="mi">2</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">param</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FuzzySet.get_lower"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.common.FuzzySet.get_lower">[docs]</a> <span class="k">def</span> <span class="nf">get_lower</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">t</span><span class="p">):</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">perturbate_parameters</span><span class="p">(</span><span class="n">t</span><span class="p">)</span>
|
||||
<span class="n">param</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">perturbated_parameters</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">t</span><span class="p">)]</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">gaussmf</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">-</span> <span class="mi">3</span><span class="o">*</span><span class="n">param</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">sigmf</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">-</span> <span class="n">param</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">param</span></div>
|
||||
|
||||
<div class="viewcode-block" id="FuzzySet.get_upper"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.common.FuzzySet.get_upper">[docs]</a> <span class="k">def</span> <span class="nf">get_upper</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">t</span><span class="p">):</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">perturbate_parameters</span><span class="p">(</span><span class="n">t</span><span class="p">)</span>
|
||||
<span class="n">param</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">perturbated_parameters</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">t</span><span class="p">)]</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">gaussmf</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="mi">3</span><span class="o">*</span><span class="n">param</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">sigmf</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">param</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">param</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">param</span><span class="p">[</span><span class="mi">3</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">param</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">location</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">+=</span> <span class="s2">"Location: "</span>
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">f</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">location</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">+=</span> <span class="nb">str</span><span class="p">(</span><span class="n">f</span><span class="o">.</span><span class="vm">__name__</span><span class="p">)</span> <span class="o">+</span> <span class="s2">"("</span> <span class="o">+</span> <span class="nb">str</span><span class="p">([</span><span class="s2">"</span><span class="si">{0:.2f}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">p</span><span class="p">)</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">location_params</span><span class="p">[</span><span class="n">ct</span><span class="p">]])</span> <span class="o">+</span> <span class="s2">") "</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">width</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">+=</span> <span class="s2">"Width: "</span>
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">f</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">width</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">+=</span> <span class="nb">str</span><span class="p">(</span><span class="n">f</span><span class="o">.</span><span class="vm">__name__</span><span class="p">)</span> <span class="o">+</span> <span class="s2">"("</span> <span class="o">+</span> <span class="nb">str</span><span class="p">([</span><span class="s2">"</span><span class="si">{0:.2f}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">p</span><span class="p">)</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">width_params</span><span class="p">[</span><span class="n">ct</span><span class="p">]])</span> <span class="o">+</span> <span class="s2">") "</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="s2">"("</span> <span class="o">+</span> <span class="nb">str</span><span class="p">([</span><span class="s2">"</span><span class="si">{0:.2f}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">p</span><span class="p">)</span> <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">parameters</span><span class="p">])</span> <span class="o">+</span> <span class="s2">") "</span> <span class="o">+</span> <span class="n">tmp</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">+</span> <span class="s2">": "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">mf</span><span class="o">.</span><span class="vm">__name__</span><span class="p">)</span> <span class="o">+</span> <span class="n">tmp</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="fuzzify"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.common.fuzzify">[docs]</a><span class="k">def</span> <span class="nf">fuzzify</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">fuzzySets</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Calculate the membership values for a data point given nonstationary fuzzy sets</span>
|
||||
|
||||
<span class="sd"> :param inst: data points</span>
|
||||
<span class="sd"> :param t: time displacement of the instance</span>
|
||||
<span class="sd"> :param fuzzySets: list of fuzzy sets</span>
|
||||
<span class="sd"> :return: array of membership values</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="n">inst</span> <span class="o">=</span> <span class="p">[</span><span class="n">inst</span><span class="p">]</span>
|
||||
<span class="k">for</span> <span class="n">t</span><span class="p">,</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">inst</span><span class="p">):</span>
|
||||
<span class="n">mv</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">fs</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">t</span><span class="p">)</span> <span class="k">for</span> <span class="n">fs</span> <span class="ow">in</span> <span class="n">fuzzySets</span><span class="p">])</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mv</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="fuzzySeries"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.common.fuzzySeries">[docs]</a><span class="k">def</span> <span class="nf">fuzzySeries</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">fuzzySets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="p">,</span> <span class="n">window_size</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s1">'fuzzy'</span><span class="p">,</span> <span class="n">const_t</span><span class="o">=</span> <span class="kc">None</span><span class="p">):</span>
|
||||
<span class="n">fts</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">t</span><span class="p">,</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">data</span><span class="p">):</span>
|
||||
<span class="n">tdisp</span> <span class="o">=</span> <span class="n">window_index</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="n">window_size</span><span class="p">)</span> <span class="k">if</span> <span class="n">const_t</span> <span class="ow">is</span> <span class="kc">None</span> <span class="k">else</span> <span class="n">const_t</span>
|
||||
<span class="n">mv</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">fuzzySets</span><span class="p">[</span><span class="n">fs</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">tdisp</span><span class="p">)</span> <span class="k">for</span> <span class="n">fs</span> <span class="ow">in</span> <span class="n">ordered_sets</span><span class="p">])</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">mv</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">sets</span> <span class="o">=</span> <span class="p">[</span><span class="n">check_bounds</span><span class="p">(</span><span class="n">i</span><span class="p">,</span> <span class="n">fuzzySets</span><span class="p">,</span> <span class="n">tdisp</span><span class="p">)]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">method</span> <span class="o">==</span> <span class="s1">'fuzzy'</span><span class="p">:</span>
|
||||
<span class="n">ix</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">mv</span> <span class="o">></span> <span class="mf">0.0</span><span class="p">))</span>
|
||||
<span class="k">elif</span> <span class="n">method</span> <span class="o">==</span> <span class="s1">'maximum'</span><span class="p">:</span>
|
||||
<span class="n">mx</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">mv</span><span class="p">)</span>
|
||||
<span class="n">ix</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">mv</span> <span class="o">==</span> <span class="n">mx</span><span class="p">))</span>
|
||||
<span class="n">sets</span> <span class="o">=</span> <span class="p">[</span><span class="n">fuzzySets</span><span class="p">[</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">i</span><span class="p">]]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">ix</span><span class="p">]</span>
|
||||
<span class="n">fts</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">sets</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">fts</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="window_index"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.common.window_index">[docs]</a><span class="k">def</span> <span class="nf">window_index</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="n">window_size</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="nb">set</span><span class="p">)):</span>
|
||||
<span class="k">return</span> <span class="n">t</span>
|
||||
<span class="k">return</span> <span class="n">t</span> <span class="o">-</span> <span class="p">(</span><span class="n">t</span> <span class="o">%</span> <span class="n">window_size</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="check_bounds"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.common.check_bounds">[docs]</a><span class="k">def</span> <span class="nf">check_bounds</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">partitioner</span><span class="p">,</span> <span class="n">t</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">data</span> <span class="o"><</span> <span class="n">partitioner</span><span class="o">.</span><span class="n">lower_set</span><span class="p">()</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">t</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">partitioner</span><span class="o">.</span><span class="n">lower_set</span><span class="p">()</span>
|
||||
<span class="k">elif</span> <span class="n">data</span> <span class="o">></span> <span class="n">partitioner</span><span class="o">.</span><span class="n">upper_set</span><span class="p">()</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">t</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">partitioner</span><span class="o">.</span><span class="n">upper_set</span><span class="p">()</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="check_bounds_index"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.common.check_bounds_index">[docs]</a><span class="k">def</span> <span class="nf">check_bounds_index</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">partitioner</span><span class="p">,</span> <span class="n">t</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">data</span> <span class="o"><</span> <span class="n">partitioner</span><span class="o">.</span><span class="n">lower_set</span><span class="p">()</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">t</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="mi">0</span>
|
||||
<span class="k">elif</span> <span class="n">data</span> <span class="o">></span> <span class="n">partitioner</span><span class="o">.</span><span class="n">upper_set</span><span class="p">()</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">t</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span> <span class="o">-</span><span class="mi">1</span></div>
|
||||
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349
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<h1>Source code for pyFTS.models.nonstationary.cvfts</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="k">import</span> <span class="n">common</span><span class="p">,</span><span class="n">nsfts</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">flrg</span><span class="p">,</span> <span class="n">tree</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="HighOrderNonstationaryFLRG"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.HighOrderNonstationaryFLRG">[docs]</a><span class="k">class</span> <span class="nc">HighOrderNonstationaryFLRG</span><span class="p">(</span><span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">):</span>
|
||||
<span class="sd">"""Conventional High Order Fuzzy Logical Relationship Group"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">HighOrderNonstationaryFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">strlhs</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
|
||||
<div class="viewcode-block" id="HighOrderNonstationaryFLRG.append_rhs"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.HighOrderNonstationaryFLRG.append_rhs">[docs]</a> <span class="k">def</span> <span class="nf">append_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">c</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="o">=</span> <span class="n">c</span></div>
|
||||
|
||||
<div class="viewcode-block" id="HighOrderNonstationaryFLRG.append_lhs"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.HighOrderNonstationaryFLRG.append_lhs">[docs]</a> <span class="k">def</span> <span class="nf">append_lhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">c</span><span class="p">)</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">tmp</span> <span class="o">+</span> <span class="s2">","</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">tmp</span> <span class="o">+</span> <span class="n">c</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="o">+</span> <span class="s2">" -> "</span> <span class="o">+</span> <span class="n">tmp</span>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ConditionalVarianceFTS"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS">[docs]</a><span class="k">class</span> <span class="nc">ConditionalVarianceFTS</span><span class="p">(</span><span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">):</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">ConditionalVarianceFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Conditional Variance FTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">"CVFTS "</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">append_transformation</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">transformation</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_stack</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">max_stack</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">uod_clip</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_order</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">inputs</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">forecasts</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">residuals</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">variance_residual</span> <span class="o">=</span> <span class="mf">0.</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">mean_residual</span> <span class="o">=</span> <span class="mf">0.</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">memory_window</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"memory_window"</span><span class="p">,</span><span class="mi">5</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="ConditionalVarianceFTS.train"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">tmpdata</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">fuzzySeries</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">,</span>
|
||||
<span class="n">method</span><span class="o">=</span><span class="s1">'fuzzy'</span><span class="p">,</span> <span class="n">const_t</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
|
||||
<span class="n">flrs</span> <span class="o">=</span> <span class="n">FLR</span><span class="o">.</span><span class="n">generate_non_recurrent_flrs</span><span class="p">(</span><span class="n">tmpdata</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">generate_flrg</span><span class="p">(</span><span class="n">flrs</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">forecasts</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="n">no_update</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">residuals</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="mi">1</span><span class="p">:])</span> <span class="o">-</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">forecasts</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">variance_residual</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">var</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">residuals</span><span class="p">)</span> <span class="c1"># np.max(self.residuals</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">mean_residual</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">residuals</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">residuals</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">residuals</span><span class="p">[</span><span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">memory_window</span><span class="p">:]</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">forecasts</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecasts</span><span class="p">[</span><span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">memory_window</span><span class="p">:]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">inputs</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">memory_window</span><span class="p">:])</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ConditionalVarianceFTS.generate_flrg"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS.generate_flrg">[docs]</a> <span class="k">def</span> <span class="nf">generate_flrg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrs</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">flr</span> <span class="ow">in</span> <span class="n">flrs</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">name</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">nsfts</span><span class="o">.</span><span class="n">ConventionalNonStationaryFLRG</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">name</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">_smooth</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">a</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="o">.</span><span class="mi">1</span> <span class="o">*</span> <span class="n">a</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="o">.</span><span class="mi">3</span> <span class="o">*</span> <span class="n">a</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="o">.</span><span class="mi">6</span> <span class="o">*</span> <span class="n">a</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span>
|
||||
|
||||
<div class="viewcode-block" id="ConditionalVarianceFTS.perturbation_factors"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS.perturbation_factors">[docs]</a> <span class="k">def</span> <span class="nf">perturbation_factors</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">npart</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
<span class="n">_max</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="n">_min</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">if</span> <span class="n">data</span> <span class="o"><</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_min</span><span class="p">:</span>
|
||||
<span class="n">_min</span> <span class="o">=</span> <span class="n">data</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_min</span> <span class="k">if</span> <span class="n">data</span> <span class="o"><</span> <span class="mi">0</span> <span class="k">else</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_min</span> <span class="o">-</span> <span class="n">data</span>
|
||||
<span class="k">elif</span> <span class="n">data</span> <span class="o">></span> <span class="bp">self</span><span class="o">.</span><span class="n">original_max</span><span class="p">:</span>
|
||||
<span class="n">_max</span> <span class="o">=</span> <span class="n">data</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_max</span> <span class="k">if</span> <span class="n">data</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_max</span> <span class="o">-</span> <span class="n">data</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_stack</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_stack</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">_min</span><span class="p">)</span>
|
||||
<span class="n">_min</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">min_stack</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">max_stack</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">max_stack</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">_max</span><span class="p">)</span>
|
||||
<span class="n">_max</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_stack</span><span class="p">)</span>
|
||||
|
||||
<span class="n">_range</span> <span class="o">=</span> <span class="p">(</span><span class="n">_max</span> <span class="o">-</span> <span class="n">_min</span><span class="p">)</span><span class="o">/</span><span class="mi">2</span>
|
||||
|
||||
<span class="n">translate</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="n">_min</span><span class="p">,</span> <span class="n">_max</span><span class="p">,</span> <span class="n">npart</span><span class="p">)</span>
|
||||
|
||||
<span class="n">var</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">residuals</span><span class="p">)</span>
|
||||
|
||||
<span class="n">var</span> <span class="o">=</span> <span class="mi">0</span> <span class="k">if</span> <span class="n">var</span> <span class="o"><</span> <span class="mi">1</span> <span class="k">else</span> <span class="n">var</span>
|
||||
|
||||
<span class="n">loc</span> <span class="o">=</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">mean_residual</span> <span class="o">+</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">residuals</span><span class="p">))</span>
|
||||
|
||||
<span class="n">location</span> <span class="o">=</span> <span class="p">[</span><span class="n">_range</span> <span class="o">+</span> <span class="n">w</span> <span class="o">+</span> <span class="n">loc</span> <span class="o">+</span> <span class="n">k</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="o">-</span><span class="n">var</span><span class="p">,</span><span class="n">var</span><span class="p">,</span> <span class="n">npart</span><span class="p">)</span> <span class="k">for</span> <span class="n">w</span> <span class="ow">in</span> <span class="n">translate</span><span class="p">]</span>
|
||||
|
||||
<span class="n">scale</span> <span class="o">=</span> <span class="p">[</span><span class="nb">abs</span><span class="p">(</span><span class="n">location</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">-</span> <span class="n">location</span><span class="p">[</span><span class="mi">2</span><span class="p">])]</span>
|
||||
<span class="n">scale</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="nb">abs</span><span class="p">(</span><span class="n">location</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">location</span><span class="p">[</span><span class="n">k</span> <span class="o">+</span> <span class="mi">1</span><span class="p">])</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">npart</span><span class="p">)])</span>
|
||||
<span class="n">scale</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">abs</span><span class="p">(</span><span class="n">location</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">location</span><span class="p">[</span><span class="o">-</span><span class="mi">3</span><span class="p">]))</span>
|
||||
|
||||
<span class="n">perturb</span> <span class="o">=</span> <span class="p">[[</span><span class="n">location</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="n">scale</span><span class="p">[</span><span class="n">k</span><span class="p">]]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">npart</span><span class="p">)]</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">perturb</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ConditionalVarianceFTS.perturbation_factors__old"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS.perturbation_factors__old">[docs]</a> <span class="k">def</span> <span class="nf">perturbation_factors__old</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="n">npart</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
<span class="n">_max</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="n">_min</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">if</span> <span class="n">data</span> <span class="o"><</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_min</span><span class="p">:</span>
|
||||
<span class="n">_min</span> <span class="o">=</span> <span class="n">data</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_min</span> <span class="k">if</span> <span class="n">data</span> <span class="o"><</span> <span class="mi">0</span> <span class="k">else</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_min</span> <span class="o">-</span> <span class="n">data</span>
|
||||
<span class="k">elif</span> <span class="n">data</span> <span class="o">></span> <span class="bp">self</span><span class="o">.</span><span class="n">original_max</span><span class="p">:</span>
|
||||
<span class="n">_max</span> <span class="o">=</span> <span class="n">data</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_max</span> <span class="k">if</span> <span class="n">data</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_max</span> <span class="o">-</span> <span class="n">data</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_stack</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_stack</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="n">_min</span><span class="p">)</span>
|
||||
<span class="n">_min</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">min_stack</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">max_stack</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">max_stack</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">_max</span><span class="p">)</span>
|
||||
<span class="n">_max</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_stack</span><span class="p">)</span>
|
||||
|
||||
<span class="n">location</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="n">_min</span><span class="p">,</span> <span class="n">_max</span><span class="p">,</span> <span class="n">npart</span><span class="p">)</span>
|
||||
<span class="n">scale</span> <span class="o">=</span> <span class="p">[</span><span class="nb">abs</span><span class="p">(</span><span class="n">location</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">-</span> <span class="n">location</span><span class="p">[</span><span class="mi">2</span><span class="p">])]</span>
|
||||
<span class="n">scale</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="nb">abs</span><span class="p">(</span><span class="n">location</span><span class="p">[</span><span class="n">k</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">location</span><span class="p">[</span><span class="n">k</span><span class="o">+</span><span class="mi">1</span><span class="p">])</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">npart</span><span class="p">)])</span>
|
||||
<span class="n">scale</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">abs</span><span class="p">(</span><span class="n">location</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">location</span><span class="p">[</span><span class="o">-</span><span class="mi">3</span><span class="p">]))</span>
|
||||
|
||||
<span class="n">perturb</span> <span class="o">=</span> <span class="p">[[</span><span class="n">location</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="n">scale</span><span class="p">[</span><span class="n">k</span><span class="p">]]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">npart</span><span class="p">)]</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">perturb</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">_fsset_key</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ix</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">_affected_sets</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sample</span><span class="p">,</span> <span class="n">perturb</span><span class="p">):</span>
|
||||
|
||||
<span class="n">affected_sets</span> <span class="o">=</span> <span class="p">[[</span><span class="n">ct</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">_fsset_key</span><span class="p">(</span><span class="n">ct</span><span class="p">)]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="n">perturb</span><span class="p">[</span><span class="n">ct</span><span class="p">])]</span>
|
||||
<span class="k">for</span> <span class="n">ct</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">))</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">_fsset_key</span><span class="p">(</span><span class="n">ct</span><span class="p">)]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="n">perturb</span><span class="p">[</span><span class="n">ct</span><span class="p">])</span> <span class="o">></span> <span class="mf">0.0</span><span class="p">]</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">affected_sets</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">sample</span> <span class="o"><</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">lower_set</span><span class="p">()</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">perturb</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
|
||||
<span class="n">affected_sets</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span>
|
||||
<span class="k">elif</span> <span class="n">sample</span> <span class="o">></span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">upper_set</span><span class="p">()</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">perturb</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]):</span>
|
||||
<span class="n">affected_sets</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">affected_sets</span>
|
||||
|
||||
<div class="viewcode-block" id="ConditionalVarianceFTS.forecast"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">no_update</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"no_update"</span><span class="p">,</span><span class="kc">False</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">ndata</span><span class="p">[</span><span class="n">k</span><span class="p">]</span>
|
||||
|
||||
<span class="k">if</span> <span class="ow">not</span> <span class="n">no_update</span><span class="p">:</span>
|
||||
<span class="n">perturb</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">perturbation_factors</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">perturb</span> <span class="o">=</span> <span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">))]</span>
|
||||
|
||||
<span class="n">affected_sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_affected_sets</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="n">perturb</span><span class="p">)</span>
|
||||
|
||||
<span class="n">numerator</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">denominator</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">affected_sets</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">ix</span> <span class="o">=</span> <span class="n">affected_sets</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="n">aset</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="n">aset</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">numerator</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">aset</span><span class="p">]</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">perturb</span><span class="p">[</span><span class="n">ix</span><span class="p">]))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">fuzzy_set</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">aset</span><span class="p">]</span>
|
||||
<span class="n">numerator</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">fuzzy_set</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="n">perturb</span><span class="p">[</span><span class="n">ix</span><span class="p">]))</span>
|
||||
<span class="n">denominator</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">aset</span> <span class="ow">in</span> <span class="n">affected_sets</span><span class="p">:</span>
|
||||
<span class="n">ix</span> <span class="o">=</span> <span class="n">aset</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="n">fs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
|
||||
<span class="n">tdisp</span> <span class="o">=</span> <span class="n">perturb</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="n">fs</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">numerator</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">fs</span><span class="p">]</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">tdisp</span><span class="p">)</span> <span class="o">*</span> <span class="n">aset</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">fuzzy_set</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">fs</span><span class="p">]</span>
|
||||
<span class="n">numerator</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">fuzzy_set</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="n">tdisp</span><span class="p">)</span> <span class="o">*</span> <span class="n">aset</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="n">denominator</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">aset</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">sum</span><span class="p">(</span><span class="n">denominator</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">pto</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">numerator</span><span class="p">)</span> <span class="o">/</span><span class="nb">sum</span><span class="p">(</span><span class="n">denominator</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">pto</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">numerator</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">pto</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="ow">not</span> <span class="n">no_update</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">forecasts</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">pto</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">residuals</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">inputs</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecasts</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">inputs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">inputs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">forecasts</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">residuals</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ConditionalVarianceFTS.forecast_interval"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS.forecast_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">ndata</span><span class="p">[</span><span class="n">k</span><span class="p">]</span>
|
||||
|
||||
<span class="n">perturb</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">perturbation_factors</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
|
||||
<span class="n">affected_sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_affected_sets</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="n">perturb</span><span class="p">)</span>
|
||||
|
||||
<span class="n">upper</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">lower</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">affected_sets</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">ix</span> <span class="o">=</span> <span class="n">affected_sets</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="n">aset</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="n">aset</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">lower</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">aset</span><span class="p">]</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">perturb</span><span class="p">[</span><span class="n">ix</span><span class="p">]))</span>
|
||||
<span class="n">upper</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">aset</span><span class="p">]</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">perturb</span><span class="p">[</span><span class="n">ix</span><span class="p">]))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">fuzzy_set</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">aset</span><span class="p">]</span>
|
||||
<span class="n">lower</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">fuzzy_set</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">perturb</span><span class="p">[</span><span class="n">ix</span><span class="p">]))</span>
|
||||
<span class="n">upper</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">fuzzy_set</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">perturb</span><span class="p">[</span><span class="n">ix</span><span class="p">]))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">aset</span> <span class="ow">in</span> <span class="n">affected_sets</span><span class="p">:</span>
|
||||
<span class="n">ix</span> <span class="o">=</span> <span class="n">aset</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="n">fs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
|
||||
<span class="n">tdisp</span> <span class="o">=</span> <span class="n">perturb</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="n">fs</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">lower</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">fs</span><span class="p">]</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">tdisp</span><span class="p">)</span> <span class="o">*</span> <span class="n">aset</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="n">upper</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">fs</span><span class="p">]</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">tdisp</span><span class="p">)</span> <span class="o">*</span> <span class="n">aset</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">fuzzy_set</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">fs</span><span class="p">]</span>
|
||||
<span class="n">lower</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">fuzzy_set</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">tdisp</span><span class="p">)</span> <span class="o">*</span> <span class="n">aset</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="n">upper</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">fuzzy_set</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">tdisp</span><span class="p">)</span> <span class="o">*</span> <span class="n">aset</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
|
||||
|
||||
<span class="n">itvl</span> <span class="o">=</span> <span class="p">[</span><span class="nb">sum</span><span class="p">(</span><span class="n">lower</span><span class="p">),</span> <span class="nb">sum</span><span class="p">(</span><span class="n">upper</span><span class="p">)]</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">itvl</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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<h1>Source code for pyFTS.models.nonstationary.flrg</h1><div class="highlight"><pre>
|
||||
<span></span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">flrg</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="k">import</span> <span class="n">common</span>
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="NonStationaryFLRG"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.flrg.NonStationaryFLRG">[docs]</a><span class="k">class</span> <span class="nc">NonStationaryFLRG</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">):</span>
|
||||
<div class="viewcode-block" id="NonStationaryFLRG.unpack_args"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.flrg.NonStationaryFLRG.unpack_args">[docs]</a> <span class="k">def</span> <span class="nf">unpack_args</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">):</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">args</span><span class="p">)</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">args</span>
|
||||
<span class="n">sets</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">w</span> <span class="o">=</span> <span class="kc">None</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">1</span>
|
||||
<span class="k">if</span> <span class="n">l</span> <span class="o">></span> <span class="mi">0</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="nb">dict</span><span class="p">):</span>
|
||||
<span class="n">sets</span> <span class="o">=</span> <span class="n">tmp</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="n">l</span> <span class="o">></span> <span class="mi">1</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="p">(</span><span class="nb">int</span><span class="p">,</span> <span class="nb">list</span><span class="p">,</span> <span class="nb">tuple</span><span class="p">)):</span>
|
||||
<span class="n">t</span> <span class="o">=</span> <span class="n">tmp</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="n">l</span> <span class="o">></span> <span class="mi">2</span> <span class="ow">and</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="mi">2</span><span class="p">],</span> <span class="nb">int</span><span class="p">):</span>
|
||||
<span class="n">w</span> <span class="o">=</span> <span class="n">tmp</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span>
|
||||
|
||||
<span class="k">return</span> <span class="p">(</span><span class="n">sets</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">w</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">NonStationaryFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="n">LHS</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span>
|
||||
|
||||
<div class="viewcode-block" id="NonStationaryFLRG.get_key"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.flrg.NonStationaryFLRG.get_key">[docs]</a> <span class="k">def</span> <span class="nf">get_key</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">str</span><span class="p">([</span><span class="n">k</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">])</span>
|
||||
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span></div>
|
||||
|
||||
<div class="viewcode-block" id="NonStationaryFLRG.get_membership"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.flrg.NonStationaryFLRG.get_membership">[docs]</a> <span class="k">def</span> <span class="nf">get_membership</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">):</span>
|
||||
<span class="n">sets</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">window_size</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">unpack_args</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">)</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="mf">0.0</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="nb">set</span><span class="p">)):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="nb">min</span><span class="p">([</span><span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="n">ct</span><span class="p">]]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">dat</span><span class="p">,</span> <span class="n">common</span><span class="o">.</span><span class="n">window_index</span><span class="p">(</span><span class="n">t</span> <span class="o">-</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">-</span> <span class="n">ct</span><span class="p">),</span> <span class="n">window_size</span><span class="p">))</span>
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">dat</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">data</span><span class="p">)])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">common</span><span class="o">.</span><span class="n">window_index</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="n">window_size</span><span class="p">))</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="NonStationaryFLRG.get_midpoint"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.flrg.NonStationaryFLRG.get_midpoint">[docs]</a> <span class="k">def</span> <span class="nf">get_midpoint</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">):</span>
|
||||
<span class="n">sets</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">window_size</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">unpack_args</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="nb">set</span><span class="p">)):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[</span><span class="n">sets</span><span class="p">[</span><span class="n">r</span><span class="p">]</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="n">common</span><span class="o">.</span><span class="n">window_index</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="n">window_size</span><span class="p">))</span> <span class="k">for</span> <span class="n">r</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">]</span>
|
||||
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[</span><span class="n">sets</span><span class="p">[</span><span class="n">r</span><span class="p">]</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="n">common</span><span class="o">.</span><span class="n">window_index</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="n">window_size</span><span class="p">))</span> <span class="k">for</span> <span class="n">r</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()]</span>
|
||||
<span class="k">return</span> <span class="nb">sum</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span> <span class="o">/</span> <span class="nb">len</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]]</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="n">common</span><span class="o">.</span><span class="n">window_index</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="n">window_size</span><span class="p">))</span></div>
|
||||
|
||||
<div class="viewcode-block" id="NonStationaryFLRG.get_lower"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.flrg.NonStationaryFLRG.get_lower">[docs]</a> <span class="k">def</span> <span class="nf">get_lower</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">):</span>
|
||||
<span class="n">sets</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">window_size</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">unpack_args</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="nb">set</span><span class="p">)):</span>
|
||||
<span class="k">return</span> <span class="nb">min</span><span class="p">([</span><span class="n">sets</span><span class="p">[</span><span class="n">r</span><span class="p">]</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">common</span><span class="o">.</span><span class="n">window_index</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="n">window_size</span><span class="p">))</span> <span class="k">for</span> <span class="n">r</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">])</span>
|
||||
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">min</span><span class="p">([</span><span class="n">sets</span><span class="p">[</span><span class="n">r</span><span class="p">]</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">common</span><span class="o">.</span><span class="n">window_index</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="n">window_size</span><span class="p">))</span> <span class="k">for</span> <span class="n">r</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]]</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">common</span><span class="o">.</span><span class="n">window_index</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="n">window_size</span><span class="p">))</span></div>
|
||||
|
||||
<div class="viewcode-block" id="NonStationaryFLRG.get_upper"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.flrg.NonStationaryFLRG.get_upper">[docs]</a> <span class="k">def</span> <span class="nf">get_upper</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">*</span><span class="n">args</span><span class="p">):</span>
|
||||
<span class="n">sets</span><span class="p">,</span> <span class="n">t</span><span class="p">,</span> <span class="n">window_size</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">unpack_args</span><span class="p">(</span><span class="o">*</span><span class="n">args</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="nb">set</span><span class="p">)):</span>
|
||||
<span class="k">return</span> <span class="nb">max</span><span class="p">([</span><span class="n">sets</span><span class="p">[</span><span class="n">r</span><span class="p">]</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">common</span><span class="o">.</span><span class="n">window_index</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="n">window_size</span><span class="p">))</span> <span class="k">for</span> <span class="n">r</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">])</span>
|
||||
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">,</span> <span class="nb">dict</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">max</span><span class="p">([</span><span class="n">sets</span><span class="p">[</span><span class="n">r</span><span class="p">]</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">common</span><span class="o">.</span><span class="n">window_index</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="n">window_size</span><span class="p">))</span> <span class="k">for</span> <span class="n">r</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]]</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">common</span><span class="o">.</span><span class="n">window_index</span><span class="p">(</span><span class="n">t</span><span class="p">,</span> <span class="n">window_size</span><span class="p">))</span></div></div>
|
||||
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<h1>Source code for pyFTS.models.nonstationary.honsfts</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">tree</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="k">import</span> <span class="n">common</span><span class="p">,</span> <span class="n">flrg</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="HighOrderNonStationaryFLRG"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.honsfts.HighOrderNonStationaryFLRG">[docs]</a><span class="k">class</span> <span class="nc">HighOrderNonStationaryFLRG</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">NonStationaryFLRG</span><span class="p">):</span>
|
||||
<span class="sd">"""First Order NonStationary Fuzzy Logical Relationship Group"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">HighOrderNonStationaryFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<div class="viewcode-block" id="HighOrderNonStationaryFLRG.append_rhs"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.honsfts.HighOrderNonStationaryFLRG.append_rhs">[docs]</a> <span class="k">def</span> <span class="nf">append_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">c</span><span class="o">.</span><span class="n">name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">c</span><span class="o">.</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">c</span></div>
|
||||
|
||||
<div class="viewcode-block" id="HighOrderNonStationaryFLRG.append_lhs"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.honsfts.HighOrderNonStationaryFLRG.append_lhs">[docs]</a> <span class="k">def</span> <span class="nf">append_lhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">c</span><span class="p">)</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">tmp</span> <span class="o">+</span> <span class="s2">","</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">tmp</span> <span class="o">+</span> <span class="n">c</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="o">+</span> <span class="s2">" -> "</span> <span class="o">+</span> <span class="n">tmp</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="HighOrderNonStationaryFTS"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.honsfts.HighOrderNonStationaryFTS">[docs]</a><span class="k">class</span> <span class="nc">HighOrderNonStationaryFTS</span><span class="p">(</span><span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">):</span>
|
||||
<span class="sd">"""NonStationaryFTS Fuzzy Time Series"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">HighOrderNonStationaryFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="s2">"HONSFTS "</span> <span class="o">+</span> <span class="n">name</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"High Order Non Stationary FTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<div class="viewcode-block" id="HighOrderNonStationaryFTS.generate_flrg"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.honsfts.HighOrderNonStationaryFTS.generate_flrg">[docs]</a> <span class="k">def</span> <span class="nf">generate_flrg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">window_size</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"window_size"</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dump</span><span class="p">:</span> <span class="nb">print</span><span class="p">(</span><span class="s2">"FLR: "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">k</span><span class="p">))</span>
|
||||
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
|
||||
|
||||
<span class="n">disp</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">window_index</span><span class="p">(</span><span class="n">k</span><span class="p">,</span> <span class="n">window_size</span><span class="p">)</span>
|
||||
|
||||
<span class="n">rhs</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span> <span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="n">disp</span><span class="p">)</span> <span class="o">></span> <span class="mf">0.0</span><span class="p">]</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">rhs</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">rhs</span> <span class="o">=</span> <span class="p">[</span><span class="n">common</span><span class="o">.</span><span class="n">check_bounds</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="p">,</span> <span class="n">disp</span><span class="p">)]</span>
|
||||
|
||||
<span class="n">lags</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">o</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">):</span>
|
||||
<span class="n">tdisp</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">window_index</span><span class="p">(</span><span class="n">k</span> <span class="o">-</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">-</span> <span class="n">o</span><span class="p">),</span> <span class="n">window_size</span><span class="p">)</span>
|
||||
<span class="n">lhs</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span> <span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">sample</span><span class="p">[</span><span class="n">o</span><span class="p">],</span> <span class="n">tdisp</span><span class="p">)</span> <span class="o">></span> <span class="mf">0.0</span><span class="p">]</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">lhs</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">lhs</span> <span class="o">=</span> <span class="p">[</span><span class="n">common</span><span class="o">.</span><span class="n">check_bounds</span><span class="p">(</span><span class="n">sample</span><span class="p">[</span><span class="n">o</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="p">,</span> <span class="n">tdisp</span><span class="p">)]</span>
|
||||
|
||||
<span class="n">lags</span><span class="p">[</span><span class="n">o</span><span class="p">]</span> <span class="o">=</span> <span class="n">lhs</span>
|
||||
|
||||
<span class="n">root</span> <span class="o">=</span> <span class="n">tree</span><span class="o">.</span><span class="n">FLRGTreeNode</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="n">tree</span><span class="o">.</span><span class="n">build_tree_without_order</span><span class="p">(</span><span class="n">root</span><span class="p">,</span> <span class="n">lags</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
|
||||
|
||||
<span class="c1"># Trace the possible paths</span>
|
||||
<span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">root</span><span class="o">.</span><span class="n">paths</span><span class="p">():</span>
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="n">HighOrderNonStationaryFLRG</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">)</span>
|
||||
<span class="n">path</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">reversed</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">filter</span><span class="p">(</span><span class="kc">None</span><span class="o">.</span><span class="fm">__ne__</span><span class="p">,</span> <span class="n">p</span><span class="p">))))</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">c</span><span class="p">,</span> <span class="n">e</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
|
||||
<span class="n">flrg</span><span class="o">.</span><span class="n">append_lhs</span><span class="p">(</span><span class="n">e</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span> <span class="o">=</span> <span class="n">flrg</span><span class="p">;</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">st</span> <span class="ow">in</span> <span class="n">rhs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">st</span><span class="p">)</span></div>
|
||||
|
||||
<span class="c1"># flrgs = sorted(flrgs, key=lambda flrg: flrg.get_midpoint(0, window_size=1))</span>
|
||||
|
||||
<div class="viewcode-block" id="HighOrderNonStationaryFTS.train"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.honsfts.HighOrderNonStationaryFTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'order'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'order'</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'sets'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'sets'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="n">window_size</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'parameters'</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">generate_flrg</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">window_size</span><span class="o">=</span><span class="n">window_size</span><span class="p">)</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">_affected_flrgs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sample</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span> <span class="n">time_displacement</span><span class="p">,</span> <span class="n">window_size</span><span class="p">):</span>
|
||||
<span class="c1"># print("input: " + str(ndata[k]))</span>
|
||||
|
||||
<span class="n">affected_flrgs</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">affected_flrgs_memberships</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">lags</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">dat</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">sample</span><span class="p">):</span>
|
||||
<span class="n">tdisp</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">window_index</span><span class="p">((</span><span class="n">k</span> <span class="o">+</span> <span class="n">time_displacement</span><span class="p">)</span> <span class="o">-</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">-</span> <span class="n">ct</span><span class="p">),</span> <span class="n">window_size</span><span class="p">)</span>
|
||||
|
||||
<span class="n">sel</span> <span class="o">=</span> <span class="p">[</span><span class="n">ct</span> <span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">key</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">dat</span><span class="p">,</span> <span class="n">tdisp</span><span class="p">)</span> <span class="o">></span> <span class="mf">0.0</span><span class="p">]</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">sel</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">sel</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">common</span><span class="o">.</span><span class="n">check_bounds_index</span><span class="p">(</span><span class="n">dat</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="p">,</span> <span class="n">tdisp</span><span class="p">))</span>
|
||||
|
||||
<span class="n">lags</span><span class="p">[</span><span class="n">ct</span><span class="p">]</span> <span class="o">=</span> <span class="n">sel</span>
|
||||
|
||||
<span class="c1"># Build the tree with all possible paths</span>
|
||||
|
||||
<span class="n">root</span> <span class="o">=</span> <span class="n">tree</span><span class="o">.</span><span class="n">FLRGTreeNode</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="n">tree</span><span class="o">.</span><span class="n">build_tree_without_order</span><span class="p">(</span><span class="n">root</span><span class="p">,</span> <span class="n">lags</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
|
||||
|
||||
<span class="c1"># Trace the possible paths and build the PFLRG's</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">root</span><span class="o">.</span><span class="n">paths</span><span class="p">():</span>
|
||||
<span class="n">path</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">reversed</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">filter</span><span class="p">(</span><span class="kc">None</span><span class="o">.</span><span class="fm">__ne__</span><span class="p">,</span> <span class="n">p</span><span class="p">))))</span>
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="n">HighOrderNonStationaryFLRG</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="n">path</span><span class="p">:</span>
|
||||
<span class="n">flrg</span><span class="o">.</span><span class="n">append_lhs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">kk</span><span class="p">]])</span>
|
||||
|
||||
<span class="n">affected_flrgs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">flrg</span><span class="p">)</span>
|
||||
<span class="c1"># affected_flrgs_memberships.append_rhs(flrg.get_membership(sample, disp))</span>
|
||||
|
||||
<span class="c1"># print(flrg.get_key())</span>
|
||||
|
||||
<span class="c1"># the FLRG is here because of the bounds verification</span>
|
||||
<span class="n">mv</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">dat</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">sample</span><span class="p">):</span>
|
||||
<span class="n">td</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">window_index</span><span class="p">((</span><span class="n">k</span> <span class="o">+</span> <span class="n">time_displacement</span><span class="p">)</span> <span class="o">-</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">-</span> <span class="n">ct</span><span class="p">),</span> <span class="n">window_size</span><span class="p">)</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="n">ct</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">dat</span><span class="p">,</span> <span class="n">td</span><span class="p">)</span>
|
||||
|
||||
|
||||
<span class="n">mv</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="c1"># print(mv)</span>
|
||||
|
||||
<span class="n">affected_flrgs_memberships</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">prod</span><span class="p">(</span><span class="n">mv</span><span class="p">))</span>
|
||||
|
||||
<span class="k">return</span> <span class="p">[</span><span class="n">affected_flrgs</span><span class="p">,</span> <span class="n">affected_flrgs_memberships</span><span class="p">]</span>
|
||||
|
||||
<div class="viewcode-block" id="HighOrderNonStationaryFTS.forecast"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.honsfts.HighOrderNonStationaryFTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">time_displacement</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"time_displacement"</span><span class="p">,</span><span class="mi">0</span><span class="p">)</span>
|
||||
|
||||
<span class="n">window_size</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"window_size"</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">l</span><span class="o">+</span><span class="mi">1</span><span class="p">):</span>
|
||||
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">ndata</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
|
||||
|
||||
<span class="n">affected_flrgs</span><span class="p">,</span> <span class="n">affected_flrgs_memberships</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_affected_flrgs</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span>
|
||||
<span class="n">time_displacement</span><span class="p">,</span> <span class="n">window_size</span><span class="p">)</span>
|
||||
|
||||
<span class="c1">#print([str(k) for k in affected_flrgs])</span>
|
||||
<span class="c1">#print(affected_flrgs_memberships)</span>
|
||||
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">tdisp</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">window_index</span><span class="p">(</span><span class="n">k</span> <span class="o">+</span> <span class="n">time_displacement</span><span class="p">,</span> <span class="n">window_size</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">affected_flrgs</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">common</span><span class="o">.</span><span class="n">check_bounds</span><span class="p">(</span><span class="n">sample</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">tdisp</span><span class="p">))</span>
|
||||
<span class="k">elif</span> <span class="nb">len</span><span class="p">(</span><span class="n">affected_flrgs</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="n">affected_flrgs</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="n">tdisp</span><span class="p">))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="n">tdisp</span><span class="p">))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">aset</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">affected_flrgs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">aset</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">aset</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="n">tdisp</span><span class="p">)</span> <span class="o">*</span>
|
||||
<span class="n">affected_flrgs_memberships</span><span class="p">[</span><span class="n">ct</span><span class="p">])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">aset</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="n">tdisp</span><span class="p">)</span><span class="o">*</span>
|
||||
<span class="n">affected_flrgs_memberships</span><span class="p">[</span><span class="n">ct</span><span class="p">])</span>
|
||||
<span class="n">pto</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
|
||||
<span class="c1">#print(pto)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">pto</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="HighOrderNonStationaryFTS.forecast_interval"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.honsfts.HighOrderNonStationaryFTS.forecast_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">time_displacement</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"time_displacement"</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
|
||||
|
||||
<span class="n">window_size</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"window_size"</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">l</span> <span class="o">+</span> <span class="mi">1</span><span class="p">):</span>
|
||||
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">ndata</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
|
||||
|
||||
<span class="n">affected_flrgs</span><span class="p">,</span> <span class="n">affected_flrgs_memberships</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_affected_flrgs</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="n">k</span><span class="p">,</span>
|
||||
<span class="n">time_displacement</span><span class="p">,</span> <span class="n">window_size</span><span class="p">)</span>
|
||||
|
||||
<span class="c1"># print([str(k) for k in affected_flrgs])</span>
|
||||
<span class="c1"># print(affected_flrgs_memberships)</span>
|
||||
|
||||
<span class="n">upper</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">lower</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">tdisp</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">window_index</span><span class="p">(</span><span class="n">k</span> <span class="o">+</span> <span class="n">time_displacement</span><span class="p">,</span> <span class="n">window_size</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">affected_flrgs</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">aset</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">check_bounds</span><span class="p">(</span><span class="n">sample</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">tdisp</span><span class="p">)</span>
|
||||
<span class="n">lower</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">aset</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">tdisp</span><span class="p">))</span>
|
||||
<span class="n">upper</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">aset</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">tdisp</span><span class="p">))</span>
|
||||
<span class="k">elif</span> <span class="nb">len</span><span class="p">(</span><span class="n">affected_flrgs</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">_flrg</span> <span class="o">=</span> <span class="n">affected_flrgs</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="n">_flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">lower</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">_flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">tdisp</span><span class="p">))</span>
|
||||
<span class="n">upper</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">_flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">tdisp</span><span class="p">))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">lower</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">tdisp</span><span class="p">))</span>
|
||||
<span class="n">upper</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">tdisp</span><span class="p">))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">aset</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">affected_flrgs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">aset</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">lower</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">aset</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">tdisp</span><span class="p">)</span> <span class="o">*</span>
|
||||
<span class="n">affected_flrgs_memberships</span><span class="p">[</span><span class="n">ct</span><span class="p">])</span>
|
||||
<span class="n">upper</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">aset</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">tdisp</span><span class="p">)</span> <span class="o">*</span>
|
||||
<span class="n">affected_flrgs_memberships</span><span class="p">[</span><span class="n">ct</span><span class="p">])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">lower</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">aset</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">tdisp</span><span class="p">)</span> <span class="o">*</span>
|
||||
<span class="n">affected_flrgs_memberships</span><span class="p">[</span><span class="n">ct</span><span class="p">])</span>
|
||||
<span class="n">upper</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">aset</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">tdisp</span><span class="p">)</span> <span class="o">*</span>
|
||||
<span class="n">affected_flrgs_memberships</span><span class="p">[</span><span class="n">ct</span><span class="p">])</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="nb">sum</span><span class="p">(</span><span class="n">lower</span><span class="p">),</span> <span class="nb">sum</span><span class="p">(</span><span class="n">upper</span><span class="p">)])</span>
|
||||
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
|
||||
<div class="sphinxsidebarwrapper"><div class="relations">
|
||||
<h3>Related Topics</h3>
|
||||
<ul>
|
||||
<li><a href="../../../../index.html">Documentation overview</a><ul>
|
||||
<li><a href="../../../index.html">Module code</a><ul>
|
||||
</ul></li>
|
||||
</ul></li>
|
||||
</ul>
|
||||
</div>
|
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<div id="searchbox" style="display: none" role="search">
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<h3>Quick search</h3>
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<div class="searchformwrapper">
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<form class="search" action="../../../../search.html" method="get">
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<input type="text" name="q" />
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<input type="submit" value="Go" />
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<div class="footer">
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352
docs/_build/html/_modules/pyFTS/models/nonstationary/nsfts.html
vendored
Normal file
352
docs/_build/html/_modules/pyFTS/models/nonstationary/nsfts.html
vendored
Normal file
@ -0,0 +1,352 @@
|
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
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<title>pyFTS.models.nonstationary.nsfts — pyFTS 1.2.3 documentation</title>
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<link rel="stylesheet" href="../../../../_static/alabaster.css" type="text/css" />
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<meta name="viewport" content="width=device-width, initial-scale=0.9, maximum-scale=0.9" />
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<div class="documentwrapper">
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<div class="bodywrapper">
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<div class="body" role="main">
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|
||||
<h1>Source code for pyFTS.models.nonstationary.nsfts</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="k">import</span> <span class="n">common</span><span class="p">,</span> <span class="n">flrg</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ConventionalNonStationaryFLRG"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.nsfts.ConventionalNonStationaryFLRG">[docs]</a><span class="k">class</span> <span class="nc">ConventionalNonStationaryFLRG</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">NonStationaryFLRG</span><span class="p">):</span>
|
||||
<span class="sd">"""First Order NonStationary Fuzzy Logical Relationship Group"""</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">ConventionalNonStationaryFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="n">LHS</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="nb">set</span><span class="p">()</span>
|
||||
|
||||
<div class="viewcode-block" id="ConventionalNonStationaryFLRG.get_key"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.nsfts.ConventionalNonStationaryFLRG.get_key">[docs]</a> <span class="k">def</span> <span class="nf">get_key</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ConventionalNonStationaryFLRG.append_rhs"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.nsfts.ConventionalNonStationaryFLRG.append_rhs">[docs]</a> <span class="k">def</span> <span class="nf">append_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">c</span><span class="p">)</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">+</span> <span class="s2">" -> "</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">tmp2</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="n">tmp2</span> <span class="o">+</span> <span class="s2">","</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="n">tmp2</span> <span class="o">+</span> <span class="n">c</span>
|
||||
<span class="k">return</span> <span class="n">tmp</span> <span class="o">+</span> <span class="n">tmp2</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="NonStationaryFTS"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.nsfts.NonStationaryFTS">[docs]</a><span class="k">class</span> <span class="nc">NonStationaryFTS</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
|
||||
<span class="sd">"""NonStationaryFTS Fuzzy Time Series"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">NonStationaryFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Non Stationary FTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">"NSFTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'method'</span><span class="p">,</span><span class="s1">'conditional'</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">append_transformation</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">transformation</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">method</span> <span class="o">==</span> <span class="s1">'conditional'</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_stack</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">max_stack</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">uod_clip</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_order</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">inputs</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">forecasts</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">residuals</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">variance_residual</span> <span class="o">=</span> <span class="mf">0.</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">mean_residual</span> <span class="o">=</span> <span class="mf">0.</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">memory_window</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"memory_window"</span><span class="p">,</span> <span class="mi">5</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="NonStationaryFTS.generate_flrg"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.nsfts.NonStationaryFTS.generate_flrg">[docs]</a> <span class="k">def</span> <span class="nf">generate_flrg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrs</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">flr</span> <span class="ow">in</span> <span class="n">flrs</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">name</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">ConventionalNonStationaryFLRG</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">name</span><span class="p">)</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">_smooth</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">a</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="o">.</span><span class="mi">1</span> <span class="o">*</span> <span class="n">a</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="o">.</span><span class="mi">3</span> <span class="o">*</span> <span class="n">a</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="o">.</span><span class="mi">6</span> <span class="o">*</span> <span class="n">a</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span>
|
||||
|
||||
<div class="viewcode-block" id="NonStationaryFTS.train"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.nsfts.NonStationaryFTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">method</span> <span class="o">==</span> <span class="s1">'unconditional'</span><span class="p">:</span>
|
||||
<span class="n">window_size</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'parameters'</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
|
||||
<span class="n">tmpdata</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">fuzzySeries</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">,</span>
|
||||
<span class="n">window_size</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s1">'fuzzy'</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">tmpdata</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">fuzzySeries</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">,</span>
|
||||
<span class="n">method</span><span class="o">=</span><span class="s1">'fuzzy'</span><span class="p">,</span> <span class="n">const_t</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
|
||||
|
||||
<span class="n">flrs</span> <span class="o">=</span> <span class="n">FLR</span><span class="o">.</span><span class="n">generate_non_recurrent_flrs</span><span class="p">(</span><span class="n">tmpdata</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">generate_flrg</span><span class="p">(</span><span class="n">flrs</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">method</span> <span class="o">==</span> <span class="s1">'conditional'</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">forecasts</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">no_update</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">residuals</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="mi">1</span><span class="p">:])</span> <span class="o">-</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">forecasts</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">variance_residual</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">var</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">residuals</span><span class="p">)</span> <span class="c1"># np.max(self.residuals</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">mean_residual</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">residuals</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">residuals</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">residuals</span><span class="p">[</span><span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">memory_window</span><span class="p">:]</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">forecasts</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecasts</span><span class="p">[</span><span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">memory_window</span><span class="p">:]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">inputs</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">memory_window</span><span class="p">:])</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span></div>
|
||||
|
||||
<div class="viewcode-block" id="NonStationaryFTS.conditional_perturbation_factors"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.nsfts.NonStationaryFTS.conditional_perturbation_factors">[docs]</a> <span class="k">def</span> <span class="nf">conditional_perturbation_factors</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">npart</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
<span class="n">_max</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="n">_min</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">if</span> <span class="n">data</span> <span class="o"><</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_min</span><span class="p">:</span>
|
||||
<span class="n">_min</span> <span class="o">=</span> <span class="n">data</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_min</span> <span class="k">if</span> <span class="n">data</span> <span class="o"><</span> <span class="mi">0</span> <span class="k">else</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_min</span> <span class="o">-</span> <span class="n">data</span>
|
||||
<span class="k">elif</span> <span class="n">data</span> <span class="o">></span> <span class="bp">self</span><span class="o">.</span><span class="n">original_max</span><span class="p">:</span>
|
||||
<span class="n">_max</span> <span class="o">=</span> <span class="n">data</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_max</span> <span class="k">if</span> <span class="n">data</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_max</span> <span class="o">-</span> <span class="n">data</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_stack</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_stack</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">_min</span><span class="p">)</span>
|
||||
<span class="n">_min</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">min_stack</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">max_stack</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="mi">2</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">max_stack</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">_max</span><span class="p">)</span>
|
||||
<span class="n">_max</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_stack</span><span class="p">)</span>
|
||||
|
||||
<span class="n">_range</span> <span class="o">=</span> <span class="p">(</span><span class="n">_max</span> <span class="o">-</span> <span class="n">_min</span><span class="p">)</span><span class="o">/</span><span class="mi">2</span>
|
||||
|
||||
<span class="n">translate</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="n">_min</span><span class="p">,</span> <span class="n">_max</span><span class="p">,</span> <span class="n">npart</span><span class="p">)</span>
|
||||
|
||||
<span class="n">var</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">residuals</span><span class="p">)</span>
|
||||
|
||||
<span class="n">var</span> <span class="o">=</span> <span class="mi">0</span> <span class="k">if</span> <span class="n">var</span> <span class="o"><</span> <span class="mi">1</span> <span class="k">else</span> <span class="n">var</span>
|
||||
|
||||
<span class="n">loc</span> <span class="o">=</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">mean_residual</span> <span class="o">+</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">residuals</span><span class="p">))</span>
|
||||
|
||||
<span class="n">location</span> <span class="o">=</span> <span class="p">[</span><span class="n">_range</span> <span class="o">+</span> <span class="n">w</span> <span class="o">+</span> <span class="n">loc</span> <span class="o">+</span> <span class="n">k</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="o">-</span><span class="n">var</span><span class="p">,</span><span class="n">var</span><span class="p">,</span> <span class="n">npart</span><span class="p">)</span> <span class="k">for</span> <span class="n">w</span> <span class="ow">in</span> <span class="n">translate</span><span class="p">]</span>
|
||||
|
||||
<span class="n">scale</span> <span class="o">=</span> <span class="p">[</span><span class="nb">abs</span><span class="p">(</span><span class="n">location</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">-</span> <span class="n">location</span><span class="p">[</span><span class="mi">2</span><span class="p">])]</span>
|
||||
<span class="n">scale</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="nb">abs</span><span class="p">(</span><span class="n">location</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">location</span><span class="p">[</span><span class="n">k</span> <span class="o">+</span> <span class="mi">1</span><span class="p">])</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="n">npart</span><span class="p">)])</span>
|
||||
<span class="n">scale</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">abs</span><span class="p">(</span><span class="n">location</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">location</span><span class="p">[</span><span class="o">-</span><span class="mi">3</span><span class="p">]))</span>
|
||||
|
||||
<span class="n">perturb</span> <span class="o">=</span> <span class="p">[[</span><span class="n">location</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="n">scale</span><span class="p">[</span><span class="n">k</span><span class="p">]]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">npart</span><span class="p">)]</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">perturb</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">_fsset_key</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ix</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">_affected_sets</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sample</span><span class="p">,</span> <span class="n">perturb</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">method</span> <span class="o">==</span> <span class="s1">'conditional'</span><span class="p">:</span>
|
||||
|
||||
<span class="n">affected_sets</span> <span class="o">=</span> <span class="p">[[</span><span class="n">ct</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">_fsset_key</span><span class="p">(</span><span class="n">ct</span><span class="p">)]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="n">perturb</span><span class="p">[</span><span class="n">ct</span><span class="p">])]</span>
|
||||
<span class="k">for</span> <span class="n">ct</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">))</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">_fsset_key</span><span class="p">(</span><span class="n">ct</span><span class="p">)]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="n">perturb</span><span class="p">[</span><span class="n">ct</span><span class="p">])</span> <span class="o">></span> <span class="mf">0.0</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">affected_sets</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">sample</span> <span class="o"><</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">lower_set</span><span class="p">()</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">perturb</span><span class="p">[</span><span class="mi">0</span><span class="p">]):</span>
|
||||
<span class="n">affected_sets</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span>
|
||||
<span class="k">elif</span> <span class="n">sample</span> <span class="o">></span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">upper_set</span><span class="p">()</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">perturb</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]):</span>
|
||||
<span class="n">affected_sets</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span>
|
||||
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">affected_sets</span> <span class="o">=</span> <span class="p">[[</span><span class="n">ct</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">_fsset_key</span><span class="p">(</span><span class="n">ct</span><span class="p">)]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="n">perturb</span><span class="p">)]</span>
|
||||
<span class="k">for</span> <span class="n">ct</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">))</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">_fsset_key</span><span class="p">(</span><span class="n">ct</span><span class="p">)]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="n">perturb</span><span class="p">)</span> <span class="o">></span> <span class="mf">0.0</span><span class="p">]</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">affected_sets</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">sample</span> <span class="o"><</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">lower_set</span><span class="p">()</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">perturb</span><span class="p">):</span>
|
||||
<span class="n">affected_sets</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span>
|
||||
<span class="k">elif</span> <span class="n">sample</span> <span class="o">></span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">upper_set</span><span class="p">()</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">perturb</span><span class="p">):</span>
|
||||
<span class="n">affected_sets</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">affected_sets</span>
|
||||
|
||||
<div class="viewcode-block" id="NonStationaryFTS.forecast"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.nsfts.NonStationaryFTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">time_displacement</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"time_displacement"</span><span class="p">,</span><span class="mi">0</span><span class="p">)</span>
|
||||
|
||||
<span class="n">window_size</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"window_size"</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
|
||||
|
||||
<span class="n">no_update</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"no_update"</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">ndata</span><span class="p">[</span><span class="n">k</span><span class="p">]</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">method</span> <span class="o">==</span> <span class="s1">'unconditional'</span><span class="p">:</span>
|
||||
<span class="n">perturb</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">window_index</span><span class="p">(</span><span class="n">k</span> <span class="o">+</span> <span class="n">time_displacement</span><span class="p">,</span> <span class="n">window_size</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">method</span> <span class="o">==</span> <span class="s1">'conditional'</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="ow">not</span> <span class="n">no_update</span><span class="p">:</span>
|
||||
<span class="n">perturb</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">conditional_perturbation_factors</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">perturb</span> <span class="o">=</span> <span class="p">[[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">))]</span>
|
||||
|
||||
<span class="n">affected_sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_affected_sets</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="n">perturb</span><span class="p">)</span>
|
||||
|
||||
<span class="n">numerator</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">denominator</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">affected_sets</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">ix</span> <span class="o">=</span> <span class="n">affected_sets</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="n">aset</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="n">aset</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">numerator</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">aset</span><span class="p">]</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">perturb</span><span class="p">[</span><span class="n">ix</span><span class="p">]))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">fuzzy_set</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">aset</span><span class="p">]</span>
|
||||
<span class="n">numerator</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">fuzzy_set</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="n">perturb</span><span class="p">[</span><span class="n">ix</span><span class="p">]))</span>
|
||||
<span class="n">denominator</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">aset</span> <span class="ow">in</span> <span class="n">affected_sets</span><span class="p">:</span>
|
||||
<span class="n">ix</span> <span class="o">=</span> <span class="n">aset</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="n">fs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
|
||||
<span class="n">tdisp</span> <span class="o">=</span> <span class="n">perturb</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="n">fs</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">numerator</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">fs</span><span class="p">]</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">tdisp</span><span class="p">)</span> <span class="o">*</span> <span class="n">aset</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">fuzzy_set</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">fs</span><span class="p">]</span>
|
||||
<span class="n">numerator</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">fuzzy_set</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="n">tdisp</span><span class="p">)</span> <span class="o">*</span> <span class="n">aset</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="n">denominator</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">aset</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">sum</span><span class="p">(</span><span class="n">denominator</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">pto</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">numerator</span><span class="p">)</span> <span class="o">/</span> <span class="nb">sum</span><span class="p">(</span><span class="n">denominator</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">pto</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">numerator</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">pto</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">method</span> <span class="o">==</span> <span class="s1">'conditional'</span> <span class="ow">and</span> <span class="ow">not</span> <span class="n">no_update</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">forecasts</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">pto</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">residuals</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">inputs</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecasts</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">inputs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">inputs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">forecasts</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">residuals</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="NonStationaryFTS.forecast_interval"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.nsfts.NonStationaryFTS.forecast_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">time_displacement</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"time_displacement"</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
|
||||
|
||||
<span class="n">window_size</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"window_size"</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
|
||||
<span class="c1"># print("input: " + str(ndata[k]))</span>
|
||||
|
||||
<span class="n">tdisp</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">window_index</span><span class="p">(</span><span class="n">k</span> <span class="o">+</span> <span class="n">time_displacement</span><span class="p">,</span> <span class="n">window_size</span><span class="p">)</span>
|
||||
|
||||
<span class="n">affected_sets</span> <span class="o">=</span> <span class="p">[[</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="n">tdisp</span><span class="p">)]</span>
|
||||
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="n">tdisp</span><span class="p">)</span> <span class="o">></span> <span class="mf">0.0</span><span class="p">]</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">affected_sets</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">affected_sets</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="n">common</span><span class="o">.</span><span class="n">check_bounds</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="p">,</span> <span class="n">tdisp</span><span class="p">),</span> <span class="mf">1.0</span><span class="p">])</span>
|
||||
|
||||
<span class="n">upper</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">lower</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">affected_sets</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">aset</span> <span class="o">=</span> <span class="n">affected_sets</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="n">aset</span><span class="o">.</span><span class="n">name</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">lower</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">aset</span><span class="o">.</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">tdisp</span><span class="p">))</span>
|
||||
<span class="n">upper</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">aset</span><span class="o">.</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">tdisp</span><span class="p">))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">lower</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">aset</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">tdisp</span><span class="p">))</span>
|
||||
<span class="n">upper</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">aset</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">tdisp</span><span class="p">))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">aset</span> <span class="ow">in</span> <span class="n">affected_sets</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">aset</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">name</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">lower</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">aset</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">tdisp</span><span class="p">)</span> <span class="o">*</span> <span class="n">aset</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="n">upper</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">aset</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">name</span><span class="p">]</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">tdisp</span><span class="p">)</span> <span class="o">*</span> <span class="n">aset</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">lower</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">aset</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">tdisp</span><span class="p">)</span> <span class="o">*</span> <span class="n">aset</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="n">upper</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">aset</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">tdisp</span><span class="p">)</span> <span class="o">*</span> <span class="n">aset</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
|
||||
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="nb">sum</span><span class="p">(</span><span class="n">lower</span><span class="p">),</span> <span class="nb">sum</span><span class="p">(</span><span class="n">upper</span><span class="p">)])</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
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|
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<h1>Source code for pyFTS.models.nonstationary.partitioners</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">partitioner</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="k">import</span> <span class="n">common</span><span class="p">,</span> <span class="n">perturbation</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span> <span class="k">as</span> <span class="n">stationary_fs</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="PolynomialNonStationaryPartitioner"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.partitioners.PolynomialNonStationaryPartitioner">[docs]</a><span class="k">class</span> <span class="nc">PolynomialNonStationaryPartitioner</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="n">Partitioner</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Non Stationary Universe of Discourse Partitioner</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">part</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">""""""</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">PolynomialNonStationaryPartitioner</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">,</span> <span class="n">npart</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">partitions</span><span class="p">,</span>
|
||||
<span class="n">func</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">membership_function</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">setnames</span><span class="p">,</span>
|
||||
<span class="n">prefix</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">prefix</span><span class="p">,</span> <span class="n">transformation</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">transformation</span><span class="p">,</span>
|
||||
<span class="n">indexer</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">indexer</span><span class="p">,</span> <span class="n">preprocess</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<span class="n">loc_params</span><span class="p">,</span> <span class="n">wid_params</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_polynomial_perturbations</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">setnames</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span> <span class="o">=</span> <span class="n">part</span><span class="o">.</span><span class="n">setnames</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span> <span class="o">=</span> <span class="n">stationary_fs</span><span class="o">.</span><span class="n">set_ordered</span><span class="p">(</span><span class="n">part</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">key</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">):</span>
|
||||
<span class="nb">set</span> <span class="o">=</span> <span class="n">part</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span>
|
||||
<span class="n">loc_roots</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">roots</span><span class="p">(</span><span class="n">loc_params</span><span class="p">[</span><span class="n">ct</span><span class="p">])[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="n">wid_roots</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">roots</span><span class="p">(</span><span class="n">wid_params</span><span class="p">[</span><span class="n">ct</span><span class="p">])[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">(</span><span class="nb">set</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="nb">set</span><span class="o">.</span><span class="n">mf</span><span class="p">,</span> <span class="nb">set</span><span class="o">.</span><span class="n">parameters</span><span class="p">,</span>
|
||||
<span class="n">location</span><span class="o">=</span><span class="n">perturbation</span><span class="o">.</span><span class="n">polynomial</span><span class="p">,</span>
|
||||
<span class="n">location_params</span><span class="o">=</span><span class="n">loc_params</span><span class="p">[</span><span class="n">ct</span><span class="p">],</span>
|
||||
<span class="n">location_roots</span><span class="o">=</span><span class="n">loc_roots</span><span class="p">,</span> <span class="c1">#**kwargs)</span>
|
||||
<span class="n">width</span><span class="o">=</span><span class="n">perturbation</span><span class="o">.</span><span class="n">polynomial</span><span class="p">,</span>
|
||||
<span class="n">width_params</span><span class="o">=</span><span class="n">wid_params</span><span class="p">[</span><span class="n">ct</span><span class="p">],</span>
|
||||
<span class="n">width_roots</span><span class="o">=</span><span class="n">wid_roots</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="nb">set</span><span class="o">.</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">tmp</span>
|
||||
|
||||
<div class="viewcode-block" id="PolynomialNonStationaryPartitioner.poly_width"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.partitioners.PolynomialNonStationaryPartitioner.poly_width">[docs]</a> <span class="k">def</span> <span class="nf">poly_width</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">par1</span><span class="p">,</span> <span class="n">par2</span><span class="p">,</span> <span class="n">rng</span><span class="p">,</span> <span class="n">deg</span><span class="p">):</span>
|
||||
<span class="n">a</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">polyval</span><span class="p">(</span><span class="n">par1</span><span class="p">,</span> <span class="n">rng</span><span class="p">)</span>
|
||||
<span class="n">b</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">polyval</span><span class="p">(</span><span class="n">par2</span><span class="p">,</span> <span class="n">rng</span><span class="p">)</span>
|
||||
<span class="n">diff</span> <span class="o">=</span> <span class="p">[</span><span class="n">b</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">-</span> <span class="n">a</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">rng</span><span class="p">]</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">polyfit</span><span class="p">(</span><span class="n">rng</span><span class="p">,</span> <span class="n">diff</span><span class="p">,</span> <span class="n">deg</span><span class="o">=</span><span class="n">deg</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">tmp</span></div>
|
||||
|
||||
<div class="viewcode-block" id="PolynomialNonStationaryPartitioner.scale_up"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.partitioners.PolynomialNonStationaryPartitioner.scale_up">[docs]</a> <span class="k">def</span> <span class="nf">scale_up</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">x</span><span class="p">,</span><span class="n">pct</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">x</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span> <span class="k">return</span> <span class="n">x</span><span class="o">*</span><span class="p">(</span><span class="mi">1</span><span class="o">+</span><span class="n">pct</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span> <span class="k">return</span> <span class="n">x</span><span class="o">*</span><span class="n">pct</span></div>
|
||||
|
||||
<div class="viewcode-block" id="PolynomialNonStationaryPartitioner.scale_down"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.partitioners.PolynomialNonStationaryPartitioner.scale_down">[docs]</a> <span class="k">def</span> <span class="nf">scale_down</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">x</span><span class="p">,</span><span class="n">pct</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">x</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span> <span class="k">return</span> <span class="n">x</span><span class="o">*</span><span class="n">pct</span>
|
||||
<span class="k">else</span><span class="p">:</span> <span class="k">return</span> <span class="n">x</span><span class="o">*</span><span class="p">(</span><span class="mi">1</span><span class="o">+</span><span class="n">pct</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="PolynomialNonStationaryPartitioner.get_polynomial_perturbations"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.partitioners.PolynomialNonStationaryPartitioner.get_polynomial_perturbations">[docs]</a> <span class="k">def</span> <span class="nf">get_polynomial_perturbations</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">w</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"window_size"</span><span class="p">,</span> <span class="nb">int</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span> <span class="o">/</span> <span class="mi">5</span><span class="p">))</span>
|
||||
<span class="n">degree</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"degree"</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>
|
||||
<span class="n">xmax</span> <span class="o">=</span> <span class="p">[</span><span class="n">data</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span>
|
||||
<span class="n">tmax</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="n">xmin</span> <span class="o">=</span> <span class="p">[</span><span class="n">data</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span>
|
||||
<span class="n">tmin</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">l</span><span class="p">,</span> <span class="n">w</span><span class="p">):</span>
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">i</span><span class="p">:</span><span class="n">i</span> <span class="o">+</span> <span class="n">w</span><span class="p">]</span>
|
||||
<span class="n">tx</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
<span class="n">xmax</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tx</span><span class="p">)</span>
|
||||
<span class="n">tmax</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">data</span> <span class="o">==</span> <span class="n">tx</span><span class="p">))</span><span class="o">.</span><span class="n">tolist</span><span class="p">()[</span><span class="mi">0</span><span class="p">])</span>
|
||||
<span class="n">tn</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
<span class="n">xmin</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tn</span><span class="p">)</span>
|
||||
<span class="n">tmin</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">data</span> <span class="o">==</span> <span class="n">tn</span><span class="p">))</span><span class="o">.</span><span class="n">tolist</span><span class="p">()[</span><span class="mi">0</span><span class="p">])</span>
|
||||
|
||||
<span class="n">cmax</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">polyfit</span><span class="p">(</span><span class="n">tmax</span><span class="p">,</span> <span class="n">xmax</span><span class="p">,</span> <span class="n">deg</span><span class="o">=</span><span class="n">degree</span><span class="p">)</span>
|
||||
<span class="n">cmin</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">polyfit</span><span class="p">(</span><span class="n">tmin</span><span class="p">,</span> <span class="n">xmin</span><span class="p">,</span> <span class="n">deg</span><span class="o">=</span><span class="n">degree</span><span class="p">)</span>
|
||||
|
||||
<span class="n">cmed</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">degree</span> <span class="o">+</span> <span class="mi">1</span><span class="p">):</span>
|
||||
<span class="n">cmed</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="n">cmin</span><span class="p">[</span><span class="n">d</span><span class="p">],</span> <span class="n">cmax</span><span class="p">[</span><span class="n">d</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitions</span><span class="p">)[</span><span class="mi">1</span><span class="p">:</span><span class="bp">self</span><span class="o">.</span><span class="n">partitions</span> <span class="o">-</span> <span class="mi">1</span><span class="p">])</span>
|
||||
|
||||
<span class="n">loc_params</span> <span class="o">=</span> <span class="p">[</span><span class="n">cmin</span><span class="o">.</span><span class="n">tolist</span><span class="p">()]</span>
|
||||
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitions</span> <span class="o">-</span> <span class="mi">2</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[</span><span class="n">cmed</span><span class="p">[</span><span class="n">k</span><span class="p">][</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">degree</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)]</span>
|
||||
<span class="n">loc_params</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="n">loc_params</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">cmax</span><span class="o">.</span><span class="n">tolist</span><span class="p">())</span>
|
||||
|
||||
<span class="n">rng</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">l</span><span class="p">)</span>
|
||||
|
||||
<span class="n">clen</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitions</span><span class="o">-</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">poly_width</span><span class="p">(</span><span class="n">loc_params</span><span class="p">[</span><span class="n">i</span> <span class="o">-</span> <span class="mi">1</span><span class="p">],</span> <span class="n">loc_params</span><span class="p">[</span><span class="n">i</span> <span class="o">+</span> <span class="mi">1</span><span class="p">],</span> <span class="n">rng</span><span class="p">,</span> <span class="n">degree</span><span class="p">)</span>
|
||||
<span class="n">clen</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">poly_width</span><span class="p">(</span><span class="n">loc_params</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">loc_params</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">rng</span><span class="p">,</span> <span class="n">degree</span><span class="p">)</span>
|
||||
<span class="n">clen</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">tmp</span><span class="p">)</span>
|
||||
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">poly_width</span><span class="p">(</span><span class="n">loc_params</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">partitions</span><span class="o">-</span><span class="mi">2</span><span class="p">],</span> <span class="n">loc_params</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">partitions</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">rng</span><span class="p">,</span> <span class="n">degree</span><span class="p">)</span>
|
||||
<span class="n">clen</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">(</span><span class="n">loc_params</span><span class="p">,</span> <span class="n">clen</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">tmp</span></div>
|
||||
|
||||
<div class="viewcode-block" id="PolynomialNonStationaryPartitioner.build"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.partitioners.PolynomialNonStationaryPartitioner.build">[docs]</a> <span class="k">def</span> <span class="nf">build</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="k">pass</span></div></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="SimpleNonStationaryPartitioner"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.partitioners.SimpleNonStationaryPartitioner">[docs]</a><span class="k">class</span> <span class="nc">SimpleNonStationaryPartitioner</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="n">Partitioner</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Non Stationary Universe of Discourse Partitioner</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">part</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">""""""</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">SimpleNonStationaryPartitioner</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">,</span> <span class="n">npart</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">partitions</span><span class="p">,</span>
|
||||
<span class="n">func</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">membership_function</span><span class="p">,</span> <span class="n">names</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">setnames</span><span class="p">,</span>
|
||||
<span class="n">prefix</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">prefix</span><span class="p">,</span> <span class="n">transformation</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">transformation</span><span class="p">,</span>
|
||||
<span class="n">indexer</span><span class="o">=</span><span class="n">part</span><span class="o">.</span><span class="n">indexer</span><span class="p">)</span><span class="c1">#, preprocess=False)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">part</span><span class="o">.</span><span class="n">sets</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
|
||||
<span class="nb">set</span> <span class="o">=</span> <span class="n">part</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">(</span><span class="nb">set</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="nb">set</span><span class="o">.</span><span class="n">mf</span><span class="p">,</span> <span class="nb">set</span><span class="o">.</span><span class="n">parameters</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">centroid</span> <span class="o">=</span> <span class="nb">set</span><span class="o">.</span><span class="n">centroid</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span> <span class="o">=</span><span class="n">tmp</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span> <span class="o">=</span> <span class="n">stationary_fs</span><span class="o">.</span><span class="n">set_ordered</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="SimpleNonStationaryPartitioner.build"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.partitioners.SimpleNonStationaryPartitioner.build">[docs]</a> <span class="k">def</span> <span class="nf">build</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="p">{}</span></div></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="simplenonstationary_gridpartitioner_builder"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.partitioners.simplenonstationary_gridpartitioner_builder">[docs]</a><span class="k">def</span> <span class="nf">simplenonstationary_gridpartitioner_builder</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">npart</span><span class="p">,</span> <span class="n">transformation</span><span class="p">):</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models.nonstationary</span> <span class="k">import</span> <span class="n">perturbation</span><span class="p">,</span> <span class="n">partitioners</span>
|
||||
|
||||
<span class="n">tmp_fs</span> <span class="o">=</span> <span class="n">Grid</span><span class="o">.</span><span class="n">GridPartitioner</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">,</span> <span class="n">npart</span><span class="o">=</span><span class="n">npart</span><span class="p">,</span> <span class="n">transformation</span><span class="o">=</span><span class="n">transformation</span><span class="p">)</span>
|
||||
<span class="n">fs</span> <span class="o">=</span> <span class="n">partitioners</span><span class="o">.</span><span class="n">SimpleNonStationaryPartitioner</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">tmp_fs</span><span class="p">,</span>
|
||||
<span class="n">location</span><span class="o">=</span><span class="n">perturbation</span><span class="o">.</span><span class="n">polynomial</span><span class="p">,</span>
|
||||
<span class="n">location_params</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
|
||||
<span class="n">location_roots</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span>
|
||||
<span class="n">width</span><span class="o">=</span><span class="n">perturbation</span><span class="o">.</span><span class="n">polynomial</span><span class="p">,</span>
|
||||
<span class="n">width_params</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">],</span>
|
||||
<span class="n">width_roots</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">fs</span></div>
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
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|
||||
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<h1>Source code for pyFTS.models.nonstationary.perturbation</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">Pertubation functions for Non Stationary Fuzzy Sets</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="k">import</span> <span class="o">*</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">Membership</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="linear"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.perturbation.linear">[docs]</a><span class="k">def</span> <span class="nf">linear</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">parameters</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">polyval</span><span class="p">(</span><span class="n">parameters</span><span class="p">,</span> <span class="n">x</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="polynomial"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.perturbation.polynomial">[docs]</a><span class="k">def</span> <span class="nf">polynomial</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">parameters</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">polyval</span><span class="p">(</span><span class="n">parameters</span><span class="p">,</span> <span class="n">x</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="exponential"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.perturbation.exponential">[docs]</a><span class="k">def</span> <span class="nf">exponential</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">parameters</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="n">x</span><span class="o">*</span><span class="n">parameters</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="periodic"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.perturbation.periodic">[docs]</a><span class="k">def</span> <span class="nf">periodic</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">parameters</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">sin</span><span class="p">(</span><span class="n">x</span> <span class="o">*</span> <span class="n">parameters</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span></div>
|
||||
</pre></div>
|
||||
|
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|
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<h3>Related Topics</h3>
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172
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||||
<h1>Source code for pyFTS.models.nonstationary.util</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
<span class="kn">import</span> <span class="nn">matplotlib</span> <span class="k">as</span> <span class="nn">plt</span>
|
||||
<span class="kn">import</span> <span class="nn">matplotlib.colors</span> <span class="k">as</span> <span class="nn">pltcolors</span>
|
||||
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">Util</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="plot_sets"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.util.plot_sets">[docs]</a><span class="k">def</span> <span class="nf">plot_sets</span><span class="p">(</span><span class="n">partitioner</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">end</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">step</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">tam</span><span class="o">=</span><span class="p">[</span><span class="mi">5</span><span class="p">,</span> <span class="mi">5</span><span class="p">],</span> <span class="n">colors</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
|
||||
<span class="n">save</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">file</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">window_size</span> <span class="o">=</span> <span class="mi">1</span><span class="p">,</span> <span class="n">only_lines</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
|
||||
|
||||
<span class="nb">range</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">start</span><span class="p">,</span><span class="n">end</span><span class="p">,</span><span class="n">step</span><span class="p">)</span>
|
||||
<span class="n">ticks</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">if</span> <span class="n">axes</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">fig</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">nrows</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">ncols</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="n">tam</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">key</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">):</span>
|
||||
<span class="n">fset</span> <span class="o">=</span> <span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="ow">not</span> <span class="n">only_lines</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">:</span>
|
||||
<span class="n">tdisp</span> <span class="o">=</span> <span class="n">t</span> <span class="o">-</span> <span class="p">(</span><span class="n">t</span> <span class="o">%</span> <span class="n">window_size</span><span class="p">)</span>
|
||||
<span class="n">fset</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">tdisp</span><span class="p">)</span>
|
||||
<span class="n">param</span> <span class="o">=</span> <span class="n">fset</span><span class="o">.</span><span class="n">perturbated_parameters</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">tdisp</span><span class="p">)]</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">fset</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">t</span> <span class="o">==</span> <span class="n">start</span><span class="p">:</span>
|
||||
<span class="n">line</span> <span class="o">=</span> <span class="n">axes</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="n">t</span><span class="p">,</span> <span class="n">t</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span> <span class="n">t</span><span class="p">],</span> <span class="n">param</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">fset</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
|
||||
<span class="n">fset</span><span class="o">.</span><span class="n">metadata</span><span class="p">[</span><span class="s1">'color'</span><span class="p">]</span> <span class="o">=</span> <span class="n">line</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">get_color</span><span class="p">()</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">axes</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="n">t</span><span class="p">,</span> <span class="n">t</span> <span class="o">+</span> <span class="mi">1</span><span class="p">,</span> <span class="n">t</span><span class="p">],</span> <span class="n">param</span><span class="p">,</span><span class="n">c</span><span class="o">=</span><span class="n">fset</span><span class="o">.</span><span class="n">metadata</span><span class="p">[</span><span class="s1">'color'</span><span class="p">])</span>
|
||||
|
||||
<span class="n">ticks</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="s2">"t+"</span><span class="o">+</span><span class="nb">str</span><span class="p">(</span><span class="n">t</span><span class="p">),</span><span class="s2">""</span><span class="p">])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">:</span>
|
||||
<span class="n">tdisp</span> <span class="o">=</span> <span class="n">t</span> <span class="o">-</span> <span class="p">(</span><span class="n">t</span> <span class="o">%</span> <span class="n">window_size</span><span class="p">)</span>
|
||||
<span class="n">fset</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">tdisp</span><span class="p">)</span>
|
||||
<span class="n">param</span> <span class="o">=</span> <span class="n">fset</span><span class="o">.</span><span class="n">perturbated_parameters</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">tdisp</span><span class="p">)]</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">polyval</span><span class="p">(</span><span class="n">param</span><span class="p">,</span> <span class="n">tdisp</span><span class="p">))</span>
|
||||
<span class="n">axes</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="nb">range</span><span class="p">,</span> <span class="n">tmp</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="s2">"--"</span><span class="p">,</span> <span class="n">c</span><span class="o">=</span><span class="s2">"blue"</span><span class="p">)</span>
|
||||
|
||||
<span class="n">axes</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s2">"Universe of Discourse"</span><span class="p">)</span>
|
||||
<span class="n">axes</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s2">"Time"</span><span class="p">)</span>
|
||||
<span class="n">plt</span><span class="o">.</span><span class="n">xticks</span><span class="p">([</span><span class="n">k</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">],</span> <span class="n">ticks</span><span class="p">,</span> <span class="n">rotation</span><span class="o">=</span><span class="s1">'vertical'</span><span class="p">)</span>
|
||||
|
||||
<span class="n">handles0</span><span class="p">,</span> <span class="n">labels0</span> <span class="o">=</span> <span class="n">axes</span><span class="o">.</span><span class="n">get_legend_handles_labels</span><span class="p">()</span>
|
||||
<span class="n">lgd</span> <span class="o">=</span> <span class="n">axes</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">handles0</span><span class="p">,</span> <span class="n">labels0</span><span class="p">,</span> <span class="n">loc</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">bbox_to_anchor</span><span class="o">=</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">))</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">data</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">axes</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">start</span><span class="p">,</span> <span class="n">start</span> <span class="o">+</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">),</span> <span class="mi">1</span><span class="p">),</span> <span class="n">data</span><span class="p">,</span><span class="n">c</span><span class="o">=</span><span class="s2">"black"</span><span class="p">)</span>
|
||||
|
||||
<span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
|
||||
|
||||
<span class="n">Util</span><span class="o">.</span><span class="n">show_and_save_image</span><span class="p">(</span><span class="n">fig</span><span class="p">,</span> <span class="n">file</span><span class="p">,</span> <span class="n">save</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="plot_sets_conditional"><a class="viewcode-back" href="../../../../pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.util.plot_sets_conditional">[docs]</a><span class="k">def</span> <span class="nf">plot_sets_conditional</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">step</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">[</span><span class="mi">5</span><span class="p">,</span> <span class="mi">5</span><span class="p">],</span> <span class="n">colors</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
|
||||
<span class="n">save</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">file</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">axes</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="nb">range</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">),</span> <span class="n">step</span><span class="p">)</span>
|
||||
<span class="n">ticks</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">if</span> <span class="n">axes</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">fig</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">nrows</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">ncols</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">figsize</span><span class="o">=</span><span class="n">size</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">t</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">:</span>
|
||||
<span class="n">model</span><span class="o">.</span><span class="n">forecast</span><span class="p">([</span><span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">]])</span>
|
||||
<span class="n">perturb</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">conditional_perturbation_factors</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">])</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">key</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">):</span>
|
||||
<span class="nb">set</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span>
|
||||
<span class="nb">set</span><span class="o">.</span><span class="n">perturbate_parameters</span><span class="p">(</span><span class="n">perturb</span><span class="p">[</span><span class="n">ct</span><span class="p">])</span>
|
||||
<span class="n">param</span> <span class="o">=</span> <span class="nb">set</span><span class="o">.</span><span class="n">perturbated_parameters</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">perturb</span><span class="p">[</span><span class="n">ct</span><span class="p">])]</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">set</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">t</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">line</span> <span class="o">=</span> <span class="n">axes</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="n">t</span><span class="p">,</span> <span class="n">t</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span> <span class="n">t</span><span class="p">],</span> <span class="n">param</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="nb">set</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
|
||||
<span class="nb">set</span><span class="o">.</span><span class="n">metadata</span><span class="p">[</span><span class="s1">'color'</span><span class="p">]</span> <span class="o">=</span> <span class="n">line</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">get_color</span><span class="p">()</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">axes</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="n">t</span><span class="p">,</span> <span class="n">t</span> <span class="o">+</span> <span class="mi">1</span><span class="p">,</span> <span class="n">t</span><span class="p">],</span> <span class="n">param</span><span class="p">,</span><span class="n">c</span><span class="o">=</span><span class="nb">set</span><span class="o">.</span><span class="n">metadata</span><span class="p">[</span><span class="s1">'color'</span><span class="p">])</span>
|
||||
|
||||
<span class="n">ticks</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="s2">"t+"</span><span class="o">+</span><span class="nb">str</span><span class="p">(</span><span class="n">t</span><span class="p">),</span><span class="s2">""</span><span class="p">])</span>
|
||||
|
||||
<span class="n">axes</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s2">"Universe of Discourse"</span><span class="p">)</span>
|
||||
<span class="n">axes</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s2">"Time"</span><span class="p">)</span>
|
||||
<span class="n">plt</span><span class="o">.</span><span class="n">xticks</span><span class="p">([</span><span class="n">k</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">],</span> <span class="n">ticks</span><span class="p">,</span> <span class="n">rotation</span><span class="o">=</span><span class="s1">'vertical'</span><span class="p">)</span>
|
||||
|
||||
<span class="n">handles0</span><span class="p">,</span> <span class="n">labels0</span> <span class="o">=</span> <span class="n">axes</span><span class="o">.</span><span class="n">get_legend_handles_labels</span><span class="p">()</span>
|
||||
<span class="n">lgd</span> <span class="o">=</span> <span class="n">axes</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">handles0</span><span class="p">,</span> <span class="n">labels0</span><span class="p">,</span> <span class="n">loc</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">bbox_to_anchor</span><span class="o">=</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">))</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">data</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">axes</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">),</span> <span class="mi">1</span><span class="p">),</span> <span class="n">data</span><span class="p">,</span><span class="n">c</span><span class="o">=</span><span class="s2">"black"</span><span class="p">)</span>
|
||||
|
||||
<span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
|
||||
|
||||
<span class="n">Util</span><span class="o">.</span><span class="n">show_and_save_image</span><span class="p">(</span><span class="n">fig</span><span class="p">,</span> <span class="n">file</span><span class="p">,</span> <span class="n">save</span><span class="p">)</span></div>
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
|
||||
<div class="sphinxsidebarwrapper"><div class="relations">
|
||||
<h3>Related Topics</h3>
|
||||
<ul>
|
||||
<li><a href="../../../../index.html">Documentation overview</a><ul>
|
||||
<li><a href="../../../index.html">Module code</a><ul>
|
||||
</ul></li>
|
||||
</ul></li>
|
||||
</ul>
|
||||
</div>
|
||||
<div id="searchbox" style="display: none" role="search">
|
||||
<h3>Quick search</h3>
|
||||
<div class="searchformwrapper">
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<form class="search" action="../../../../search.html" method="get">
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<input type="text" name="q" />
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<input type="submit" value="Go" />
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©2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
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635
docs/_build/html/_modules/pyFTS/models/pwfts.html
vendored
Normal file
635
docs/_build/html/_modules/pyFTS/models/pwfts.html
vendored
Normal file
@ -0,0 +1,635 @@
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
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||||
<h1>Source code for pyFTS.models.pwfts</h1><div class="highlight"><pre>
|
||||
<span></span><span class="ch">#!/usr/bin/python</span>
|
||||
<span class="c1"># -*- coding: utf8 -*-</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
<span class="kn">import</span> <span class="nn">math</span>
|
||||
<span class="kn">from</span> <span class="nn">operator</span> <span class="k">import</span> <span class="n">itemgetter</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">tree</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">ifts</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">ProbabilityDistribution</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFLRG"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFLRG">[docs]</a><span class="k">class</span> <span class="nc">ProbabilisticWeightedFLRG</span><span class="p">(</span><span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFLRG</span><span class="p">):</span>
|
||||
<span class="sd">"""High Order Probabilistic Weighted Fuzzy Logical Relationship Group"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">ProbabilisticWeightedFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">rhs_count</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">frequency_count</span> <span class="o">=</span> <span class="mf">0.0</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">Z</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFLRG.get_membership"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_membership">[docs]</a> <span class="k">def</span> <span class="nf">get_membership</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="nb">list</span><span class="p">)):</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">nanprod</span><span class="p">([</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">count</span><span class="p">])</span>
|
||||
<span class="k">for</span> <span class="n">count</span><span class="p">,</span> <span class="n">key</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="mi">0</span><span class="p">)])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">data</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFLRG.append_rhs"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.append_rhs">[docs]</a> <span class="k">def</span> <span class="nf">append_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">mv</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'mv'</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">frequency_count</span> <span class="o">+=</span> <span class="n">mv</span>
|
||||
<span class="k">if</span> <span class="n">c</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">rhs_count</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="o">+=</span> <span class="n">mv</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="o">=</span> <span class="n">c</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">rhs_count</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="o">=</span> <span class="n">mv</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFLRG.lhs_conditional_probability"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.lhs_conditional_probability">[docs]</a> <span class="k">def</span> <span class="nf">lhs_conditional_probability</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="n">sets</span><span class="p">,</span> <span class="n">norm</span><span class="p">,</span> <span class="n">uod</span><span class="p">,</span> <span class="n">nbins</span><span class="p">):</span>
|
||||
<span class="n">pk</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">frequency_count</span> <span class="o">/</span> <span class="n">norm</span>
|
||||
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">pk</span> <span class="o">*</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">get_membership</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">sets</span><span class="p">)</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">partition_function</span><span class="p">(</span><span class="n">sets</span><span class="p">,</span> <span class="n">uod</span><span class="p">,</span> <span class="n">nbins</span><span class="o">=</span><span class="n">nbins</span><span class="p">))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">tmp</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFLRG.rhs_unconditional_probability"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.rhs_unconditional_probability">[docs]</a> <span class="k">def</span> <span class="nf">rhs_unconditional_probability</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">rhs_count</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">frequency_count</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFLRG.rhs_conditional_probability"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.rhs_conditional_probability">[docs]</a> <span class="k">def</span> <span class="nf">rhs_conditional_probability</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="n">sets</span><span class="p">,</span> <span class="n">uod</span><span class="p">,</span> <span class="n">nbins</span><span class="p">):</span>
|
||||
<span class="n">total</span> <span class="o">=</span> <span class="mf">0.0</span>
|
||||
<span class="k">for</span> <span class="n">rhs</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">:</span>
|
||||
<span class="nb">set</span> <span class="o">=</span> <span class="n">sets</span><span class="p">[</span><span class="n">rhs</span><span class="p">]</span>
|
||||
<span class="n">wi</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">rhs_unconditional_probability</span><span class="p">(</span><span class="n">rhs</span><span class="p">)</span>
|
||||
<span class="n">mv</span> <span class="o">=</span> <span class="nb">set</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">/</span> <span class="nb">set</span><span class="o">.</span><span class="n">partition_function</span><span class="p">(</span><span class="n">uod</span><span class="p">,</span> <span class="n">nbins</span><span class="o">=</span><span class="n">nbins</span><span class="p">)</span>
|
||||
<span class="n">total</span> <span class="o">+=</span> <span class="n">wi</span> <span class="o">*</span> <span class="n">mv</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">total</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFLRG.partition_function"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.partition_function">[docs]</a> <span class="k">def</span> <span class="nf">partition_function</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sets</span><span class="p">,</span> <span class="n">uod</span><span class="p">,</span> <span class="n">nbins</span><span class="o">=</span><span class="mi">100</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">Z</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">Z</span> <span class="o">=</span> <span class="mf">0.0</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="n">uod</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">uod</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">nbins</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">Z</span> <span class="o">+=</span> <span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">Z</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFLRG.get_midpoint"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_midpoint">[docs]</a> <span class="k">def</span> <span class="nf">get_midpoint</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
|
||||
<span class="sd">'''Return the expectation of the PWFLRG, the weighted sum'''</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">midpoint</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">midpoint</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">rhs_unconditional_probability</span><span class="p">(</span><span class="n">s</span><span class="p">)</span> <span class="o">*</span> <span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span>
|
||||
<span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">]))</span>
|
||||
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">midpoint</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFLRG.get_upper"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_upper">[docs]</a> <span class="k">def</span> <span class="nf">get_upper</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">upper</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">upper</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">rhs_unconditional_probability</span><span class="p">(</span><span class="n">s</span><span class="p">)</span> <span class="o">*</span> <span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">upper</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">]))</span>
|
||||
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">upper</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFLRG.get_lower"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFLRG.get_lower">[docs]</a> <span class="k">def</span> <span class="nf">get_lower</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">lower</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">lower</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">rhs_unconditional_probability</span><span class="p">(</span><span class="n">s</span><span class="p">)</span> <span class="o">*</span> <span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">lower</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">]))</span>
|
||||
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">lower</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">tmp2</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="n">tmp2</span> <span class="o">+</span> <span class="s2">", "</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="n">tmp2</span> <span class="o">+</span> <span class="s2">"("</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">rhs_count</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">frequency_count</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span> <span class="o">+</span> <span class="s2">")"</span> <span class="o">+</span> <span class="n">c</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="o">+</span> <span class="s2">" -> "</span> <span class="o">+</span> <span class="n">tmp2</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS">[docs]</a><span class="k">class</span> <span class="nc">ProbabilisticWeightedFTS</span><span class="p">(</span><span class="n">ifts</span><span class="o">.</span><span class="n">IntervalFTS</span><span class="p">):</span>
|
||||
<span class="sd">"""High Order Probabilistic Weighted Fuzzy Time Series"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">ProbabilisticWeightedFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">"PWFTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Probabilistic FTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">"Silva, P.; Guimarães, F.; Sadaei, H."</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">global_frequency_count</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_point_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_interval_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_probability_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min_order</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">auto_update</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'update'</span><span class="p">,</span><span class="kc">False</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">configure_lags</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.train"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">configure_lags</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="n">parameters</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'parameters'</span><span class="p">,</span><span class="s1">'fuzzy'</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">parameters</span> <span class="o">==</span> <span class="s1">'monotonic'</span><span class="p">:</span>
|
||||
<span class="n">tmpdata</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">fuzzyfy_series_old</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
<span class="n">flrs</span> <span class="o">=</span> <span class="n">FLR</span><span class="o">.</span><span class="n">generate_recurrent_flrs</span><span class="p">(</span><span class="n">tmpdata</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">generateFLRG</span><span class="p">(</span><span class="n">flrs</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">generate_flrg</span><span class="p">(</span><span class="n">data</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.generate_lhs_flrg"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_lhs_flrg">[docs]</a> <span class="k">def</span> <span class="nf">generate_lhs_flrg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sample</span><span class="p">):</span>
|
||||
<span class="n">lags</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<span class="n">flrgs</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">o</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">lags</span><span class="p">):</span>
|
||||
<span class="n">lhs</span> <span class="o">=</span> <span class="p">[</span><span class="n">key</span> <span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">sample</span><span class="p">[</span><span class="n">o</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span> <span class="o">></span> <span class="bp">self</span><span class="o">.</span><span class="n">alpha_cut</span><span class="p">]</span>
|
||||
<span class="n">lags</span><span class="p">[</span><span class="n">ct</span><span class="p">]</span> <span class="o">=</span> <span class="n">lhs</span>
|
||||
|
||||
<span class="n">root</span> <span class="o">=</span> <span class="n">tree</span><span class="o">.</span><span class="n">FLRGTreeNode</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="n">tree</span><span class="o">.</span><span class="n">build_tree_without_order</span><span class="p">(</span><span class="n">root</span><span class="p">,</span> <span class="n">lags</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
|
||||
|
||||
<span class="c1"># Trace the possible paths</span>
|
||||
<span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">root</span><span class="o">.</span><span class="n">paths</span><span class="p">():</span>
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="n">ProbabilisticWeightedFLRG</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">)</span>
|
||||
<span class="n">path</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">reversed</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">filter</span><span class="p">(</span><span class="kc">None</span><span class="o">.</span><span class="fm">__ne__</span><span class="p">,</span> <span class="n">p</span><span class="p">))))</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">lhs</span> <span class="ow">in</span> <span class="n">path</span><span class="p">:</span>
|
||||
<span class="n">flrg</span><span class="o">.</span><span class="n">append_lhs</span><span class="p">(</span><span class="n">lhs</span><span class="p">)</span>
|
||||
|
||||
<span class="n">flrgs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">flrg</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">flrgs</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.generate_flrg"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_flrg">[docs]</a> <span class="k">def</span> <span class="nf">generate_flrg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dump</span><span class="p">:</span> <span class="nb">print</span><span class="p">(</span><span class="s2">"FLR: "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">k</span><span class="p">))</span>
|
||||
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
|
||||
|
||||
<span class="n">flrgs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrg</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">flrg</span> <span class="ow">in</span> <span class="n">flrgs</span><span class="p">:</span>
|
||||
|
||||
<span class="n">lhs_mv</span> <span class="o">=</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_membership</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span> <span class="o">=</span> <span class="n">flrg</span><span class="p">;</span>
|
||||
|
||||
<span class="n">fuzzyfied</span> <span class="o">=</span> <span class="p">[(</span><span class="n">s</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">k</span><span class="p">]))</span>
|
||||
<span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="o">.</span><span class="n">keys</span><span class="p">()</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">k</span><span class="p">])</span> <span class="o">></span> <span class="bp">self</span><span class="o">.</span><span class="n">alpha_cut</span><span class="p">]</span>
|
||||
|
||||
<span class="n">mvs</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="nb">set</span><span class="p">,</span> <span class="n">mv</span> <span class="ow">in</span> <span class="n">fuzzyfied</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="nb">set</span><span class="p">,</span> <span class="n">mv</span><span class="o">=</span><span class="n">lhs_mv</span> <span class="o">*</span> <span class="n">mv</span><span class="p">)</span>
|
||||
<span class="n">mvs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mv</span><span class="p">)</span>
|
||||
|
||||
<span class="n">tmp_fq</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">([</span><span class="n">lhs_mv</span><span class="o">*</span><span class="n">kk</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="n">mvs</span> <span class="k">if</span> <span class="n">kk</span> <span class="o">></span> <span class="mi">0</span><span class="p">])</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">global_frequency_count</span> <span class="o">+=</span> <span class="n">tmp_fq</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.update_model"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.update_model">[docs]</a> <span class="k">def</span> <span class="nf">update_model</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">data</span><span class="p">):</span>
|
||||
<span class="k">pass</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.add_new_PWFLGR"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.add_new_PWFLGR">[docs]</a> <span class="k">def</span> <span class="nf">add_new_PWFLGR</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrg</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">ProbabilisticWeightedFLRG</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">fs</span> <span class="ow">in</span> <span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">:</span> <span class="n">tmp</span><span class="o">.</span><span class="n">append_lhs</span><span class="p">(</span><span class="n">fs</span><span class="p">)</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">tmp</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span> <span class="o">=</span> <span class="n">tmp</span><span class="p">;</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">global_frequency_count</span> <span class="o">+=</span> <span class="mi">1</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.flrg_lhs_unconditional_probability"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_lhs_unconditional_probability">[docs]</a> <span class="k">def</span> <span class="nf">flrg_lhs_unconditional_probability</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrg</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">frequency_count</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">global_frequency_count</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="mf">0.0</span></div>
|
||||
<span class="c1">#self.add_new_PWFLGR(flrg)</span>
|
||||
<span class="c1">#return self.flrg_lhs_unconditional_probability(flrg)</span>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.flrg_lhs_conditional_probability"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_lhs_conditional_probability">[docs]</a> <span class="k">def</span> <span class="nf">flrg_lhs_conditional_probability</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="n">flrg</span><span class="p">):</span>
|
||||
<span class="n">mv</span> <span class="o">=</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_membership</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
<span class="n">pb</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrg_lhs_unconditional_probability</span><span class="p">(</span><span class="n">flrg</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">mv</span> <span class="o">*</span> <span class="n">pb</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.get_midpoint"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_midpoint">[docs]</a> <span class="k">def</span> <span class="nf">get_midpoint</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrg</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span> <span class="c1">#sum(np.array([tmp.rhs_unconditional_probability(s) * self.setsDict[s].centroid for s in tmp.RHS]))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">pi</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">/</span> <span class="nb">len</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">pi</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">]))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.flrg_rhs_conditional_probability"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.flrg_rhs_conditional_probability">[docs]</a> <span class="k">def</span> <span class="nf">flrg_rhs_conditional_probability</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="n">flrg</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">_flrg</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span>
|
||||
<span class="n">cond</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">_flrg</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
|
||||
<span class="n">_set</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">_flrg</span><span class="o">.</span><span class="n">rhs_unconditional_probability</span><span class="p">(</span><span class="n">s</span><span class="p">)</span> <span class="o">*</span> <span class="p">(</span><span class="n">_set</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">/</span> <span class="n">_set</span><span class="o">.</span><span class="n">partition_function</span><span class="p">(</span><span class="n">uod</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">get_UoD</span><span class="p">()))</span>
|
||||
<span class="n">cond</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">cond</span><span class="p">))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="c1">##########################################</span>
|
||||
<span class="c1"># this may be the problem! TEST IT!!!</span>
|
||||
<span class="c1">##########################################</span>
|
||||
<span class="n">pi</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">/</span> <span class="nb">len</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">pi</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">]))</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.get_upper"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_upper">[docs]</a> <span class="k">def</span> <span class="nf">get_upper</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrg</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.get_lower"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.get_lower">[docs]</a> <span class="k">def</span> <span class="nf">get_lower</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrg</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.forecast"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'method'</span><span class="p">,</span><span class="s1">'heuristic'</span><span class="p">)</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">-</span> <span class="mi">1</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">-</span> <span class="mi">1</span><span class="p">):</span> <span class="n">k</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">method</span> <span class="o">==</span> <span class="s1">'heuristic'</span><span class="p">:</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">point_heuristic</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">))</span>
|
||||
<span class="k">elif</span> <span class="n">method</span> <span class="o">==</span> <span class="s1">'expected_value'</span><span class="p">:</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">point_expected_value</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"Unknown point forecasting method!"</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">auto_update</span> <span class="ow">and</span> <span class="n">k</span> <span class="o">></span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="o">+</span><span class="mi">1</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">update_model</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">-</span> <span class="mi">1</span> <span class="p">:</span> <span class="n">k</span><span class="p">])</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.point_heuristic"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.point_heuristic">[docs]</a> <span class="k">def</span> <span class="nf">point_heuristic</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sample</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">flrgs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrg</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
|
||||
<span class="n">mp</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">norms</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">flrg</span> <span class="ow">in</span> <span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">norm</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrg_lhs_conditional_probability</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="n">flrg</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">norm</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">norm</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrg_lhs_unconditional_probability</span><span class="p">(</span><span class="n">flrg</span><span class="p">)</span>
|
||||
<span class="n">mp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">norm</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="n">flrg</span><span class="p">))</span>
|
||||
<span class="n">norms</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">norm</span><span class="p">)</span>
|
||||
|
||||
<span class="n">norm</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">norms</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">norm</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="mi">0</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="nb">sum</span><span class="p">(</span><span class="n">mp</span><span class="p">)</span> <span class="o">/</span> <span class="n">norm</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.point_expected_value"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.point_expected_value">[docs]</a> <span class="k">def</span> <span class="nf">point_expected_value</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sample</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast_distribution</span><span class="p">(</span><span class="n">sample</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">expected_value</span><span class="p">()</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.forecast_interval"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'method'</span><span class="p">,</span><span class="s1">'heuristic'</span><span class="p">)</span>
|
||||
<span class="n">alpha</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'alpha'</span><span class="p">,</span> <span class="mf">0.05</span><span class="p">)</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">-</span> <span class="mi">1</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">ndata</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">-</span> <span class="mi">1</span><span class="p">):</span> <span class="n">k</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">method</span> <span class="o">==</span> <span class="s1">'heuristic'</span><span class="p">:</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">interval_heuristic</span><span class="p">(</span><span class="n">sample</span><span class="p">))</span>
|
||||
<span class="k">elif</span> <span class="n">method</span> <span class="o">==</span> <span class="s1">'quantile'</span><span class="p">:</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">interval_quantile</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="n">alpha</span><span class="p">))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"Unknown interval forecasting method!"</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.interval_quantile"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.interval_quantile">[docs]</a> <span class="k">def</span> <span class="nf">interval_quantile</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="n">alpha</span><span class="p">):</span>
|
||||
<span class="n">dist</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast_distribution</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
<span class="n">itvl</span> <span class="o">=</span> <span class="n">dist</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">quantile</span><span class="p">([</span><span class="n">alpha</span><span class="p">,</span> <span class="mf">1.0</span> <span class="o">-</span> <span class="n">alpha</span><span class="p">])</span>
|
||||
<span class="k">return</span> <span class="n">itvl</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.interval_heuristic"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.interval_heuristic">[docs]</a> <span class="k">def</span> <span class="nf">interval_heuristic</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sample</span><span class="p">):</span>
|
||||
|
||||
<span class="n">flrgs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrg</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
|
||||
<span class="n">up</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">lo</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">norms</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">flrg</span> <span class="ow">in</span> <span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">norm</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrg_lhs_conditional_probability</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="n">flrg</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">norm</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">norm</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrg_lhs_unconditional_probability</span><span class="p">(</span><span class="n">flrg</span><span class="p">)</span>
|
||||
<span class="n">up</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">norm</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_upper</span><span class="p">(</span><span class="n">flrg</span><span class="p">))</span>
|
||||
<span class="n">lo</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">norm</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="n">flrg</span><span class="p">))</span>
|
||||
<span class="n">norms</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">norm</span><span class="p">)</span>
|
||||
|
||||
<span class="c1"># gerar o intervalo</span>
|
||||
<span class="n">norm</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">norms</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">norm</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">0</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">lo_</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">lo</span><span class="p">)</span> <span class="o">/</span> <span class="n">norm</span>
|
||||
<span class="n">up_</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">up</span><span class="p">)</span> <span class="o">/</span> <span class="n">norm</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="n">lo_</span><span class="p">,</span> <span class="n">up_</span><span class="p">]</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.forecast_distribution"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_distribution">[docs]</a> <span class="k">def</span> <span class="nf">forecast_distribution</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">smooth</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"smooth"</span><span class="p">,</span> <span class="s2">"none"</span><span class="p">)</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
<span class="n">uod</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_UoD</span><span class="p">()</span>
|
||||
|
||||
<span class="k">if</span> <span class="s1">'bins'</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
|
||||
<span class="n">_bins</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'bins'</span><span class="p">)</span>
|
||||
<span class="n">nbins</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">_bins</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">nbins</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"num_bins"</span><span class="p">,</span> <span class="mi">100</span><span class="p">)</span>
|
||||
<span class="n">_bins</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="n">uod</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">uod</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">nbins</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">-</span> <span class="mi">1</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">ndata</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">-</span> <span class="mi">1</span><span class="p">):</span> <span class="n">k</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]</span>
|
||||
|
||||
<span class="n">flrgs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrg</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="s1">'type'</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
|
||||
<span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'type'</span><span class="p">)</span>
|
||||
|
||||
<span class="n">dist</span> <span class="o">=</span> <span class="n">ProbabilityDistribution</span><span class="o">.</span><span class="n">ProbabilityDistribution</span><span class="p">(</span><span class="n">smooth</span><span class="p">,</span> <span class="n">uod</span><span class="o">=</span><span class="n">uod</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="n">_bins</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="nb">bin</span> <span class="ow">in</span> <span class="n">_bins</span><span class="p">:</span>
|
||||
<span class="n">num</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">den</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">s</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">s</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span>
|
||||
<span class="n">pk</span> <span class="o">=</span> <span class="n">flrg</span><span class="o">.</span><span class="n">lhs_conditional_probability</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">global_frequency_count</span><span class="p">,</span> <span class="n">uod</span><span class="p">,</span> <span class="n">nbins</span><span class="p">)</span>
|
||||
<span class="n">wi</span> <span class="o">=</span> <span class="n">flrg</span><span class="o">.</span><span class="n">rhs_conditional_probability</span><span class="p">(</span><span class="nb">bin</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">uod</span><span class="p">,</span> <span class="n">nbins</span><span class="p">)</span>
|
||||
<span class="n">num</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">wi</span> <span class="o">*</span> <span class="n">pk</span><span class="p">)</span>
|
||||
<span class="n">den</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">pk</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">num</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mf">0.0</span><span class="p">)</span>
|
||||
<span class="n">den</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mf">0.000000001</span><span class="p">)</span>
|
||||
<span class="n">pf</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">num</span><span class="p">)</span> <span class="o">/</span> <span class="nb">sum</span><span class="p">(</span><span class="n">den</span><span class="p">)</span>
|
||||
|
||||
<span class="n">dist</span><span class="o">.</span><span class="n">set</span><span class="p">(</span><span class="nb">bin</span><span class="p">,</span> <span class="n">pf</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">dist</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__check_point_bounds</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">point</span><span class="p">):</span>
|
||||
<span class="n">lower_set</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">lower_set</span><span class="p">()</span>
|
||||
<span class="n">upper_set</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">upper_set</span><span class="p">()</span>
|
||||
<span class="k">return</span> <span class="n">point</span> <span class="o"><=</span> <span class="n">lower_set</span><span class="o">.</span><span class="n">lower</span> <span class="ow">or</span> <span class="n">point</span> <span class="o">>=</span> <span class="n">upper_set</span><span class="o">.</span><span class="n">upper</span>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.forecast_ahead"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_ahead">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="n">start</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'start'</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">start</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">start</span><span class="p">]</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="n">steps</span><span class="o">+</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">__check_point_bounds</span><span class="p">(</span><span class="n">ret</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span> <span class="p">:</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">ret</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">mp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast</span><span class="p">(</span><span class="n">ret</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">k</span><span class="p">],</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mp</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:]</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__check_interval_bounds</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">interval</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">transformations</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">lower_set</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">lower_set</span><span class="p">()</span>
|
||||
<span class="n">upper_set</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">upper_set</span><span class="p">()</span>
|
||||
<span class="k">return</span> <span class="n">interval</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o"><=</span> <span class="n">lower_set</span><span class="o">.</span><span class="n">lower</span> <span class="ow">and</span> <span class="n">interval</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">>=</span> <span class="n">upper_set</span><span class="o">.</span><span class="n">upper</span>
|
||||
<span class="k">elif</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">transformations</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">interval</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o"><=</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_min</span> <span class="ow">and</span> <span class="n">interval</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">>=</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_max</span>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.forecast_ahead_interval"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_ahead_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="n">start</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'start'</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">)</span>
|
||||
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">start</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">start</span><span class="p">]</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[[</span><span class="n">k</span><span class="p">,</span> <span class="n">k</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">sample</span><span class="p">]</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">forecast_interval</span><span class="p">(</span><span class="n">sample</span><span class="p">)[</span><span class="mi">0</span><span class="p">])</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span> <span class="n">steps</span><span class="o">+</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">ret</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">__check_interval_bounds</span><span class="p">(</span><span class="n">ret</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]):</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">ret</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">lower</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast_interval</span><span class="p">([</span><span class="n">ret</span><span class="p">[</span><span class="n">x</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="n">k</span><span class="p">)],</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="n">upper</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast_interval</span><span class="p">([</span><span class="n">ret</span><span class="p">[</span><span class="n">x</span><span class="p">][</span><span class="mi">1</span><span class="p">]</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="n">k</span><span class="p">)],</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="n">np</span><span class="o">.</span><span class="n">min</span><span class="p">(</span><span class="n">lower</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">upper</span><span class="p">)])</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">:]</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilisticWeightedFTS.forecast_ahead_distribution"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_ahead_distribution">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead_distribution</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">smooth</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"smooth"</span><span class="p">,</span> <span class="s2">"none"</span><span class="p">)</span>
|
||||
|
||||
<span class="n">uod</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_UoD</span><span class="p">()</span>
|
||||
|
||||
<span class="k">if</span> <span class="s1">'bins'</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
|
||||
<span class="n">_bins</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'bins'</span><span class="p">)</span>
|
||||
<span class="n">nbins</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">_bins</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">nbins</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"num_bins"</span><span class="p">,</span> <span class="mi">100</span><span class="p">)</span>
|
||||
<span class="n">_bins</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="n">uod</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">uod</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">nbins</span><span class="p">)</span>
|
||||
|
||||
<span class="n">start</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'start'</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">)</span>
|
||||
|
||||
<span class="n">sample</span> <span class="o">=</span> <span class="n">ndata</span><span class="p">[</span><span class="n">start</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">start</span><span class="p">]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">dat</span> <span class="ow">in</span> <span class="n">sample</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="s1">'type'</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
|
||||
<span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'type'</span><span class="p">)</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">ProbabilityDistribution</span><span class="o">.</span><span class="n">ProbabilityDistribution</span><span class="p">(</span><span class="n">smooth</span><span class="p">,</span> <span class="n">uod</span><span class="o">=</span><span class="n">uod</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="n">_bins</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">set</span><span class="p">(</span><span class="n">dat</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">)</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
|
||||
<span class="n">dist</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast_distribution</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="n">_bins</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">dist</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="o">+</span><span class="mi">1</span><span class="p">,</span> <span class="n">steps</span><span class="o">+</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="o">+</span><span class="mi">1</span><span class="p">):</span>
|
||||
<span class="n">dist</span> <span class="o">=</span> <span class="n">ProbabilityDistribution</span><span class="o">.</span><span class="n">ProbabilityDistribution</span><span class="p">(</span><span class="n">smooth</span><span class="p">,</span> <span class="n">uod</span><span class="o">=</span><span class="n">uod</span><span class="p">,</span> <span class="n">bins</span><span class="o">=</span><span class="n">_bins</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="n">lags</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<span class="c1"># Find all bins of past distributions with probability greater than zero</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">d</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">lags</span><span class="p">):</span>
|
||||
<span class="n">dd</span> <span class="o">=</span> <span class="n">ret</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="n">d</span><span class="p">]</span>
|
||||
<span class="n">vals</span> <span class="o">=</span> <span class="p">[</span><span class="nb">float</span><span class="p">(</span><span class="n">v</span><span class="p">)</span> <span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">dd</span><span class="o">.</span><span class="n">bins</span> <span class="k">if</span> <span class="nb">round</span><span class="p">(</span><span class="n">dd</span><span class="o">.</span><span class="n">density</span><span class="p">(</span><span class="n">v</span><span class="p">),</span> <span class="mi">4</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">]</span>
|
||||
<span class="n">lags</span><span class="p">[</span><span class="n">ct</span><span class="p">]</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">vals</span><span class="p">)</span>
|
||||
|
||||
<span class="n">root</span> <span class="o">=</span> <span class="n">tree</span><span class="o">.</span><span class="n">FLRGTreeNode</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="n">tree</span><span class="o">.</span><span class="n">build_tree_without_order</span><span class="p">(</span><span class="n">root</span><span class="p">,</span> <span class="n">lags</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
|
||||
|
||||
<span class="c1"># Trace all possible combinations between the bins of past distributions</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">root</span><span class="o">.</span><span class="n">paths</span><span class="p">():</span>
|
||||
<span class="n">path</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">reversed</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">filter</span><span class="p">(</span><span class="kc">None</span><span class="o">.</span><span class="fm">__ne__</span><span class="p">,</span> <span class="n">p</span><span class="p">))))</span>
|
||||
|
||||
<span class="c1"># get the combined probabilities for this path</span>
|
||||
|
||||
<span class="n">pk</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">prod</span><span class="p">([</span><span class="n">ret</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">+</span> <span class="n">o</span><span class="p">]</span><span class="o">.</span><span class="n">density</span><span class="p">(</span><span class="n">path</span><span class="p">[</span><span class="n">ct</span><span class="p">])</span>
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">o</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">lags</span><span class="p">)])</span>
|
||||
|
||||
|
||||
<span class="n">d</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast_distribution</span><span class="p">(</span><span class="n">path</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
|
||||
|
||||
<span class="k">for</span> <span class="nb">bin</span> <span class="ow">in</span> <span class="n">_bins</span><span class="p">:</span>
|
||||
<span class="n">dist</span><span class="o">.</span><span class="n">set</span><span class="p">(</span><span class="nb">bin</span><span class="p">,</span> <span class="n">dist</span><span class="o">.</span><span class="n">density</span><span class="p">(</span><span class="nb">bin</span><span class="p">)</span> <span class="o">+</span> <span class="n">pk</span> <span class="o">*</span> <span class="n">d</span><span class="o">.</span><span class="n">density</span><span class="p">(</span><span class="nb">bin</span><span class="p">))</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">dist</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">:]</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">+</span> <span class="s2">":</span><span class="se">\n</span><span class="s2">"</span>
|
||||
<span class="k">for</span> <span class="n">r</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">):</span>
|
||||
<span class="n">p</span> <span class="o">=</span> <span class="nb">round</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">r</span><span class="p">]</span><span class="o">.</span><span class="n">frequency_count</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">global_frequency_count</span><span class="p">,</span> <span class="mi">3</span><span class="p">)</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">tmp</span> <span class="o">+</span> <span class="s2">"("</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">p</span><span class="p">)</span> <span class="o">+</span> <span class="s2">") "</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">r</span><span class="p">])</span> <span class="o">+</span> <span class="s2">"</span><span class="se">\n</span><span class="s2">"</span>
|
||||
<span class="k">return</span> <span class="n">tmp</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="visualize_distributions"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.pwfts.visualize_distributions">[docs]</a><span class="k">def</span> <span class="nf">visualize_distributions</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
|
||||
<span class="kn">from</span> <span class="nn">matplotlib</span> <span class="k">import</span> <span class="n">gridspec</span>
|
||||
<span class="kn">import</span> <span class="nn">seaborn</span> <span class="k">as</span> <span class="nn">sns</span>
|
||||
|
||||
<span class="n">ordered_sets</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span>
|
||||
<span class="n">ftpg_keys</span> <span class="o">=</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="o">.</span><span class="n">keys</span><span class="p">(),</span> <span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">x</span><span class="p">]</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">sets</span><span class="p">))</span>
|
||||
|
||||
<span class="n">lhs_probs</span> <span class="o">=</span> <span class="p">[</span><span class="n">model</span><span class="o">.</span><span class="n">flrg_lhs_unconditional_probability</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">k</span><span class="p">])</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">ftpg_keys</span><span class="p">]</span>
|
||||
|
||||
<span class="n">mat</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="nb">len</span><span class="p">(</span><span class="n">ftpg_keys</span><span class="p">),</span> <span class="nb">len</span><span class="p">(</span><span class="n">ordered_sets</span><span class="p">)))</span>
|
||||
<span class="k">for</span> <span class="n">row</span><span class="p">,</span> <span class="n">w</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">ftpg_keys</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">col</span><span class="p">,</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">ordered_sets</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">w</span><span class="p">]</span><span class="o">.</span><span class="n">RHS</span><span class="p">:</span>
|
||||
<span class="n">mat</span><span class="p">[</span><span class="n">row</span><span class="p">,</span> <span class="n">col</span><span class="p">]</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">w</span><span class="p">]</span><span class="o">.</span><span class="n">rhs_unconditional_probability</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
|
||||
|
||||
<span class="n">size</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'size'</span><span class="p">,</span> <span class="p">(</span><span class="mi">5</span><span class="p">,</span><span class="mi">10</span><span class="p">))</span>
|
||||
|
||||
<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="n">size</span><span class="p">)</span>
|
||||
|
||||
<span class="n">gs</span> <span class="o">=</span> <span class="n">gridspec</span><span class="o">.</span><span class="n">GridSpec</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="n">width_ratios</span><span class="o">=</span><span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">4</span><span class="p">])</span>
|
||||
<span class="n">ax1</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="n">gs</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
|
||||
<span class="n">sns</span><span class="o">.</span><span class="n">barplot</span><span class="p">(</span><span class="n">x</span><span class="o">=</span><span class="s1">'y'</span><span class="p">,</span> <span class="n">y</span><span class="o">=</span><span class="s1">'x'</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">'darkblue'</span><span class="p">,</span> <span class="n">data</span><span class="o">=</span><span class="p">{</span><span class="s1">'x'</span><span class="p">:</span> <span class="n">ftpg_keys</span><span class="p">,</span> <span class="s1">'y'</span><span class="p">:</span> <span class="n">lhs_probs</span><span class="p">},</span> <span class="n">ax</span><span class="o">=</span><span class="n">ax1</span><span class="p">)</span>
|
||||
<span class="n">ax1</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s2">"LHS Probabilities"</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ind_sets</span> <span class="o">=</span> <span class="nb">range</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">ordered_sets</span><span class="p">))</span>
|
||||
<span class="n">ax</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplot</span><span class="p">(</span><span class="n">gs</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>
|
||||
<span class="n">sns</span><span class="o">.</span><span class="n">heatmap</span><span class="p">(</span><span class="n">mat</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="s1">'Blues'</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">,</span> <span class="n">yticklabels</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="s2">"RHS probabilities"</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">set_xticks</span><span class="p">(</span><span class="n">ind_sets</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">set_xticklabels</span><span class="p">(</span><span class="n">ordered_sets</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">grid</span><span class="p">(</span><span class="kc">True</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">xaxis</span><span class="o">.</span><span class="n">set_tick_params</span><span class="p">(</span><span class="n">rotation</span><span class="o">=</span><span class="mi">90</span><span class="p">)</span></div>
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
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|
||||
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|
||||
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|
||||
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177
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<h1>Source code for pyFTS.models.sadaei</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">First Order Exponentialy Weighted Fuzzy Time Series by Sadaei et al. (2013)</span>
|
||||
|
||||
<span class="sd">H. J. Sadaei, R. Enayatifar, A. H. Abdullah, and A. Gani, “Short-term load forecasting using a hybrid model with a </span>
|
||||
<span class="sd">refined exponentially weighted fuzzy time series and an improved harmony search,” Int. J. Electr. Power Energy Syst., vol. 62, no. from 2005, pp. 118–129, 2014.</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span><span class="n">FLR</span><span class="p">,</span><span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span>
|
||||
|
||||
<span class="n">default_c</span> <span class="o">=</span> <span class="mf">1.1</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ExponentialyWeightedFLRG"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.sadaei.ExponentialyWeightedFLRG">[docs]</a><span class="k">class</span> <span class="nc">ExponentialyWeightedFLRG</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">):</span>
|
||||
<span class="sd">"""First Order Exponentialy Weighted Fuzzy Logical Relationship Group"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">ExponentialyWeightedFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="n">LHS</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="o">=</span> <span class="mf">0.0</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">c</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"c"</span><span class="p">,</span><span class="n">default_c</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
|
||||
<div class="viewcode-block" id="ExponentialyWeightedFLRG.append_rhs"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.sadaei.ExponentialyWeightedFLRG.append_rhs">[docs]</a> <span class="k">def</span> <span class="nf">append_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">c</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="o">+</span> <span class="mf">1.0</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ExponentialyWeightedFLRG.weights"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.sadaei.ExponentialyWeightedFLRG.weights">[docs]</a> <span class="k">def</span> <span class="nf">weights</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">wei</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">c</span> <span class="o">**</span> <span class="n">k</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">count</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">)]</span>
|
||||
<span class="n">tot</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">wei</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">k</span> <span class="o">/</span> <span class="n">tot</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">wei</span><span class="p">])</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">w</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">+</span> <span class="s2">" -> "</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
<span class="n">cc</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="n">wei</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">c</span> <span class="o">**</span> <span class="n">k</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mf">0.0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">count</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">)]</span>
|
||||
<span class="n">tot</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">wei</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">tmp2</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="n">tmp2</span> <span class="o">+</span> <span class="s2">","</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="n">tmp2</span> <span class="o">+</span> <span class="n">c</span> <span class="o">+</span> <span class="s2">"("</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">wei</span><span class="p">[</span><span class="n">cc</span><span class="p">]</span> <span class="o">/</span> <span class="n">tot</span><span class="p">)</span> <span class="o">+</span> <span class="s2">")"</span>
|
||||
<span class="n">cc</span> <span class="o">=</span> <span class="n">cc</span> <span class="o">+</span> <span class="mi">1</span>
|
||||
<span class="k">return</span> <span class="n">tmp</span> <span class="o">+</span> <span class="n">tmp2</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ExponentialyWeightedFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.sadaei.ExponentialyWeightedFTS">[docs]</a><span class="k">class</span> <span class="nc">ExponentialyWeightedFTS</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
|
||||
<span class="sd">"""First Order Exponentialy Weighted Fuzzy Time Series"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">ExponentialyWeightedFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">"EWFTS"</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Exponentialy Weighted FTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">"Sadaei"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">c</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'c'</span><span class="p">,</span> <span class="n">default_c</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="ExponentialyWeightedFTS.generate_flrg"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.sadaei.ExponentialyWeightedFTS.generate_flrg">[docs]</a> <span class="k">def</span> <span class="nf">generate_flrg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrs</span><span class="p">,</span> <span class="n">c</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">flr</span> <span class="ow">in</span> <span class="n">flrs</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">flr</span><span class="o">.</span><span class="n">LHS</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span> <span class="o">=</span> <span class="n">ExponentialyWeightedFLRG</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">,</span> <span class="n">c</span><span class="o">=</span><span class="n">c</span><span class="p">);</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ExponentialyWeightedFTS.train"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.sadaei.ExponentialyWeightedFTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">tmpdata</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">fuzzyfy_series</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s1">'maximum'</span><span class="p">)</span>
|
||||
<span class="n">flrs</span> <span class="o">=</span> <span class="n">FLR</span><span class="o">.</span><span class="n">generate_recurrent_flrs</span><span class="p">(</span><span class="n">tmpdata</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">generate_flrg</span><span class="p">(</span><span class="n">flrs</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">c</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ExponentialyWeightedFTS.forecast"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.sadaei.ExponentialyWeightedFTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">ordered_sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ordered_sets</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">set_ordered</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
|
||||
<span class="n">data</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
|
||||
<span class="n">actual</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">get_maximum_membership_fuzzyset</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">actual</span><span class="o">.</span><span class="n">name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">actual</span><span class="o">.</span><span class="n">centroid</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">actual</span><span class="o">.</span><span class="n">name</span><span class="p">]</span>
|
||||
<span class="n">mp</span> <span class="o">=</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_midpoints</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mp</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">weights</span><span class="p">()))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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<meta name="viewport" content="width=device-width, initial-scale=0.9, maximum-scale=0.9" />
|
||||
|
||||
</head><body>
|
||||
|
||||
|
||||
<div class="document">
|
||||
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|
||||
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|
||||
<div class="body" role="main">
|
||||
|
||||
<h1>Source code for pyFTS.models.seasonal.SeasonalIndexer</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models.seasonal</span> <span class="k">import</span> <span class="n">common</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="SeasonalIndexer"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.SeasonalIndexer">[docs]</a><span class="k">class</span> <span class="nc">SeasonalIndexer</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Seasonal Indexer. Responsible to find the seasonal index of a data point inside its data set</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">num_seasons</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">num_seasons</span> <span class="o">=</span> <span class="n">num_seasons</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"name"</span><span class="p">,</span><span class="s2">""</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="SeasonalIndexer.get_season_of_data"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.SeasonalIndexer.get_season_of_data">[docs]</a> <span class="k">def</span> <span class="nf">get_season_of_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">data</span><span class="p">):</span>
|
||||
<span class="k">pass</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SeasonalIndexer.get_season_by_index"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.SeasonalIndexer.get_season_by_index">[docs]</a> <span class="k">def</span> <span class="nf">get_season_by_index</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">inde</span><span class="p">):</span>
|
||||
<span class="k">pass</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SeasonalIndexer.get_data_by_season"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.SeasonalIndexer.get_data_by_season">[docs]</a> <span class="k">def</span> <span class="nf">get_data_by_season</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">indexes</span><span class="p">):</span>
|
||||
<span class="k">pass</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SeasonalIndexer.get_index_by_season"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.SeasonalIndexer.get_index_by_season">[docs]</a> <span class="k">def</span> <span class="nf">get_index_by_season</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">indexes</span><span class="p">):</span>
|
||||
<span class="k">pass</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SeasonalIndexer.get_data"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.SeasonalIndexer.get_data">[docs]</a> <span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="k">pass</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SeasonalIndexer.get_index"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.SeasonalIndexer.get_index">[docs]</a> <span class="k">def</span> <span class="nf">get_index</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="k">pass</span></div></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="LinearSeasonalIndexer"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.LinearSeasonalIndexer">[docs]</a><span class="k">class</span> <span class="nc">LinearSeasonalIndexer</span><span class="p">(</span><span class="n">SeasonalIndexer</span><span class="p">):</span>
|
||||
<span class="sd">"""Use the data array/list position to index the seasonality """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">seasons</span><span class="p">,</span> <span class="n">units</span><span class="p">,</span> <span class="n">ignore</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Indexer for array/list position</span>
|
||||
<span class="sd"> :param seasons: A list with the season group (i.e: 7 for week, 30 for month, etc)</span>
|
||||
<span class="sd"> :param units: A list with the units used for each season group, the default is 1 for each</span>
|
||||
<span class="sd"> :param ignore:</span>
|
||||
<span class="sd"> :param kwargs:</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">LinearSeasonalIndexer</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">seasons</span><span class="p">),</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">seasons</span> <span class="o">=</span> <span class="n">seasons</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">units</span> <span class="o">=</span> <span class="n">units</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">ignore</span> <span class="o">=</span> <span class="n">ignore</span>
|
||||
|
||||
<div class="viewcode-block" id="LinearSeasonalIndexer.get_season_of_data"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.LinearSeasonalIndexer.get_season_of_data">[docs]</a> <span class="k">def</span> <span class="nf">get_season_of_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">data</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_season_by_index</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">))</span><span class="o">.</span><span class="n">tolist</span><span class="p">())</span></div>
|
||||
|
||||
<div class="viewcode-block" id="LinearSeasonalIndexer.get_season_by_index"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.LinearSeasonalIndexer.get_season_by_index">[docs]</a> <span class="k">def</span> <span class="nf">get_season_by_index</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">index</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">index</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">num_seasons</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">season</span> <span class="o">=</span> <span class="p">(</span><span class="n">index</span> <span class="o">//</span> <span class="bp">self</span><span class="o">.</span><span class="n">units</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="o">%</span> <span class="bp">self</span><span class="o">.</span><span class="n">seasons</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">season</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">seasonality</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">seasons</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">(</span><span class="n">index</span> <span class="o">//</span> <span class="bp">self</span><span class="o">.</span><span class="n">units</span><span class="p">[</span><span class="n">ct</span><span class="p">])</span> <span class="o">%</span> <span class="bp">self</span><span class="o">.</span><span class="n">seasons</span><span class="p">[</span><span class="n">ct</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">ignore</span><span class="p">[</span><span class="n">ct</span><span class="p">]:</span>
|
||||
<span class="n">season</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">season</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">ix</span> <span class="ow">in</span> <span class="n">index</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">num_seasons</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">season</span> <span class="o">=</span> <span class="p">(</span><span class="n">ix</span> <span class="o">//</span> <span class="bp">self</span><span class="o">.</span><span class="n">units</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="o">%</span> <span class="bp">self</span><span class="o">.</span><span class="n">seasons</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">season</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">seasonality</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">seasons</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">(</span><span class="n">ix</span> <span class="o">//</span> <span class="bp">self</span><span class="o">.</span><span class="n">units</span><span class="p">[</span><span class="n">ct</span><span class="p">])</span> <span class="o">%</span> <span class="bp">self</span><span class="o">.</span><span class="n">seasons</span><span class="p">[</span><span class="n">ct</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="ow">not</span> <span class="bp">self</span><span class="o">.</span><span class="n">ignore</span><span class="p">[</span><span class="n">ct</span><span class="p">]:</span>
|
||||
<span class="n">season</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">season</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="LinearSeasonalIndexer.get_index_by_season"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.LinearSeasonalIndexer.get_index_by_season">[docs]</a> <span class="k">def</span> <span class="nf">get_index_by_season</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">indexes</span><span class="p">):</span>
|
||||
<span class="n">ix</span> <span class="o">=</span> <span class="mi">0</span><span class="p">;</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">count</span><span class="p">,</span><span class="n">season</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">seasons</span><span class="p">):</span>
|
||||
<span class="n">ix</span> <span class="o">+=</span> <span class="n">season</span><span class="o">*</span><span class="p">(</span><span class="n">indexes</span><span class="p">[</span><span class="n">count</span><span class="p">])</span>
|
||||
|
||||
<span class="c1">#ix += indexes[-1]</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ix</span></div>
|
||||
|
||||
<div class="viewcode-block" id="LinearSeasonalIndexer.get_data"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.LinearSeasonalIndexer.get_data">[docs]</a> <span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">data</span></div></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="DataFrameSeasonalIndexer"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.DataFrameSeasonalIndexer">[docs]</a><span class="k">class</span> <span class="nc">DataFrameSeasonalIndexer</span><span class="p">(</span><span class="n">SeasonalIndexer</span><span class="p">):</span>
|
||||
<span class="sd">"""Use the Pandas.DataFrame index position to index the seasonality """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">index_fields</span><span class="p">,</span><span class="n">index_seasons</span><span class="p">,</span> <span class="n">data_field</span><span class="p">,</span><span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="sd"> :param index_fields: DataFrame field to use as index</span>
|
||||
<span class="sd"> :param index_seasons: A list with the season group, i. e., multiples of positions that are considered a season (i.e: 7 for week, 30 for month, etc)</span>
|
||||
<span class="sd"> :param data_fields: DataFrame field to use as data</span>
|
||||
<span class="sd"> :param kwargs:</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">DataFrameSeasonalIndexer</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">index_seasons</span><span class="p">),</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">fields</span> <span class="o">=</span> <span class="n">index_fields</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">seasons</span> <span class="o">=</span> <span class="n">index_seasons</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">data_field</span> <span class="o">=</span> <span class="n">data_field</span>
|
||||
|
||||
<div class="viewcode-block" id="DataFrameSeasonalIndexer.get_season_of_data"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.DataFrameSeasonalIndexer.get_season_of_data">[docs]</a> <span class="k">def</span> <span class="nf">get_season_of_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">data</span><span class="p">):</span>
|
||||
<span class="c1">#data = data.copy()</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">ix</span> <span class="ow">in</span> <span class="n">data</span><span class="o">.</span><span class="n">index</span><span class="p">:</span>
|
||||
<span class="n">season</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">c</span><span class="p">,</span> <span class="n">f</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">fields</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">seasons</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">season</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">f</span><span class="p">][</span><span class="n">ix</span><span class="p">])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">a</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">f</span><span class="p">][</span><span class="n">ix</span><span class="p">]</span>
|
||||
<span class="n">season</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">a</span> <span class="o">//</span> <span class="bp">self</span><span class="o">.</span><span class="n">seasons</span><span class="p">[</span><span class="n">c</span><span class="p">])</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">season</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="DataFrameSeasonalIndexer.get_season_by_index"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.DataFrameSeasonalIndexer.get_season_by_index">[docs]</a> <span class="k">def</span> <span class="nf">get_season_by_index</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">index</span><span class="p">):</span>
|
||||
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">"Operation not available!"</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="DataFrameSeasonalIndexer.get_data_by_season"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.DataFrameSeasonalIndexer.get_data_by_season">[docs]</a> <span class="k">def</span> <span class="nf">get_data_by_season</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">indexes</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">season</span> <span class="ow">in</span> <span class="n">indexes</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">c</span><span class="p">,</span> <span class="n">f</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">fields</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">seasons</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">data</span><span class="p">[</span><span class="n">f</span><span class="p">]</span><span class="o">==</span> <span class="n">season</span><span class="p">[</span><span class="n">c</span><span class="p">]]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="p">[(</span><span class="n">data</span><span class="p">[</span><span class="n">f</span><span class="p">]</span> <span class="o">//</span> <span class="bp">self</span><span class="o">.</span><span class="n">seasons</span><span class="p">[</span><span class="n">c</span><span class="p">])</span> <span class="o">==</span> <span class="n">season</span><span class="p">[</span><span class="n">c</span><span class="p">]]</span>
|
||||
<span class="k">return</span> <span class="n">data</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">data_field</span><span class="p">]</span></div>
|
||||
|
||||
<div class="viewcode-block" id="DataFrameSeasonalIndexer.get_index_by_season"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.DataFrameSeasonalIndexer.get_index_by_season">[docs]</a> <span class="k">def</span> <span class="nf">get_index_by_season</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">indexes</span><span class="p">):</span>
|
||||
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">"Operation not available!"</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="DataFrameSeasonalIndexer.get_data"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.DataFrameSeasonalIndexer.get_data">[docs]</a> <span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">data</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">data_field</span><span class="p">]</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span></div>
|
||||
|
||||
<div class="viewcode-block" id="DataFrameSeasonalIndexer.set_data"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.DataFrameSeasonalIndexer.set_data">[docs]</a> <span class="k">def</span> <span class="nf">set_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span>
|
||||
<span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[:,</span><span class="bp">self</span><span class="o">.</span><span class="n">data_field</span><span class="p">]</span> <span class="o">=</span> <span class="n">value</span>
|
||||
<span class="k">return</span> <span class="n">data</span></div></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="DateTimeSeasonalIndexer"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.DateTimeSeasonalIndexer">[docs]</a><span class="k">class</span> <span class="nc">DateTimeSeasonalIndexer</span><span class="p">(</span><span class="n">SeasonalIndexer</span><span class="p">):</span>
|
||||
<span class="sd">"""Use a Pandas.DataFrame date field to index the seasonality """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">date_field</span><span class="p">,</span> <span class="n">index_fields</span><span class="p">,</span> <span class="n">index_seasons</span><span class="p">,</span> <span class="n">data_field</span><span class="p">,</span><span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="sd"> :param date_field: DataFrame field that contains the datetime field used on index</span>
|
||||
<span class="sd"> :param index_fields: List with commom.DataTime fields</span>
|
||||
<span class="sd"> :param index_seasons: Multiples of index_fields, the default is 1</span>
|
||||
<span class="sd"> :param data_field: DataFrame field with the time series data</span>
|
||||
<span class="sd"> :param kwargs:</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">DateTimeSeasonalIndexer</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">index_seasons</span><span class="p">),</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">fields</span> <span class="o">=</span> <span class="n">index_fields</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">seasons</span> <span class="o">=</span> <span class="n">index_seasons</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">data_field</span> <span class="o">=</span> <span class="n">data_field</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">date_field</span> <span class="o">=</span> <span class="n">date_field</span>
|
||||
|
||||
<div class="viewcode-block" id="DateTimeSeasonalIndexer.get_season_of_data"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.DateTimeSeasonalIndexer.get_season_of_data">[docs]</a> <span class="k">def</span> <span class="nf">get_season_of_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">ix</span> <span class="ow">in</span> <span class="n">data</span><span class="o">.</span><span class="n">index</span><span class="p">:</span>
|
||||
<span class="n">date</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">date_field</span><span class="p">][</span><span class="n">ix</span><span class="p">]</span>
|
||||
<span class="n">season</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">c</span><span class="p">,</span> <span class="n">f</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">fields</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">common</span><span class="o">.</span><span class="n">strip_datepart</span><span class="p">(</span><span class="n">date</span><span class="p">,</span> <span class="n">f</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">seasons</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">tmp</span> <span class="o">//</span> <span class="bp">self</span><span class="o">.</span><span class="n">seasons</span><span class="p">[</span><span class="n">c</span><span class="p">]</span>
|
||||
<span class="n">season</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">season</span><span class="p">)</span>
|
||||
|
||||
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">):</span>
|
||||
<span class="n">date</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">date_field</span><span class="p">]</span>
|
||||
<span class="n">season</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">c</span><span class="p">,</span> <span class="n">f</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">fields</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
|
||||
<span class="n">season</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">common</span><span class="o">.</span><span class="n">strip_datepart</span><span class="p">(</span><span class="n">date</span><span class="p">,</span> <span class="n">f</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">seasons</span><span class="p">[</span><span class="n">c</span><span class="p">]))</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">season</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="DateTimeSeasonalIndexer.get_season_by_index"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.DateTimeSeasonalIndexer.get_season_by_index">[docs]</a> <span class="k">def</span> <span class="nf">get_season_by_index</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">index</span><span class="p">):</span>
|
||||
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">"Operation not available!"</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="DateTimeSeasonalIndexer.get_data_by_season"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.DateTimeSeasonalIndexer.get_data_by_season">[docs]</a> <span class="k">def</span> <span class="nf">get_data_by_season</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">indexes</span><span class="p">):</span>
|
||||
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">"Operation not available!"</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="DateTimeSeasonalIndexer.get_index_by_season"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.DateTimeSeasonalIndexer.get_index_by_season">[docs]</a> <span class="k">def</span> <span class="nf">get_index_by_season</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">indexes</span><span class="p">):</span>
|
||||
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">"Operation not available!"</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="DateTimeSeasonalIndexer.get_data"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.DateTimeSeasonalIndexer.get_data">[docs]</a> <span class="k">def</span> <span class="nf">get_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">data</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">data_field</span><span class="p">]</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span></div>
|
||||
|
||||
<div class="viewcode-block" id="DateTimeSeasonalIndexer.get_index"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.DateTimeSeasonalIndexer.get_index">[docs]</a> <span class="k">def</span> <span class="nf">get_index</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">data</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">date_field</span><span class="p">]</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">)</span> <span class="k">else</span> <span class="n">data</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">date_field</span><span class="p">]</span></div>
|
||||
|
||||
<div class="viewcode-block" id="DateTimeSeasonalIndexer.set_data"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.DateTimeSeasonalIndexer.set_data">[docs]</a> <span class="k">def</span> <span class="nf">set_data</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span>
|
||||
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">"Operation not available!"</span><span class="p">)</span></div></div>
|
||||
|
||||
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
||||
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|
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<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
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<h3>Related Topics</h3>
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<li><a href="../../../../index.html">Documentation overview</a><ul>
|
||||
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|
||||
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|
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|
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<h3>Quick search</h3>
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188
docs/_build/html/_modules/pyFTS/models/seasonal/cmsfts.html
vendored
Normal file
188
docs/_build/html/_modules/pyFTS/models/seasonal/cmsfts.html
vendored
Normal file
@ -0,0 +1,188 @@
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
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|
||||
<h1>Source code for pyFTS.models.seasonal.cmsfts</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models.seasonal</span> <span class="k">import</span> <span class="n">sfts</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">chen</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ContextualSeasonalFLRG"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.cmsfts.ContextualSeasonalFLRG">[docs]</a><span class="k">class</span> <span class="nc">ContextualSeasonalFLRG</span><span class="p">(</span><span class="n">sfts</span><span class="o">.</span><span class="n">SeasonalFLRG</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Contextual Seasonal Fuzzy Logical Relationship Group</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">seasonality</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">ContextualSeasonalFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">seasonality</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<div class="viewcode-block" id="ContextualSeasonalFLRG.append_rhs"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.cmsfts.ContextualSeasonalFLRG.append_rhs">[docs]</a> <span class="k">def</span> <span class="nf">append_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flr</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">flr</span><span class="o">.</span><span class="n">LHS</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span> <span class="o">=</span> <span class="n">chen</span><span class="o">.</span><span class="n">ConventionalFLRG</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">+</span> <span class="s2">": </span><span class="se">\n</span><span class="s2"> "</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="s2">"</span><span class="se">\t</span><span class="s2">"</span>
|
||||
<span class="k">for</span> <span class="n">r</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">):</span>
|
||||
<span class="n">tmp2</span> <span class="o">+=</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">r</span><span class="p">])</span> <span class="o">+</span> <span class="s2">"</span><span class="se">\n\t</span><span class="s2">"</span>
|
||||
<span class="k">return</span> <span class="n">tmp</span> <span class="o">+</span> <span class="n">tmp2</span> <span class="o">+</span> <span class="s2">"</span><span class="se">\n</span><span class="s2">"</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ContextualMultiSeasonalFTS"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.cmsfts.ContextualMultiSeasonalFTS">[docs]</a><span class="k">class</span> <span class="nc">ContextualMultiSeasonalFTS</span><span class="p">(</span><span class="n">sfts</span><span class="o">.</span><span class="n">SeasonalFTS</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Contextual Multi-Seasonal Fuzzy Time Series</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">ContextualMultiSeasonalFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Contextual Multi Seasonal FTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">"CMSFTS "</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">seasonality</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_seasonality</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_point_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_multivariate</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<div class="viewcode-block" id="ContextualMultiSeasonalFTS.generate_flrg"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.cmsfts.ContextualMultiSeasonalFTS.generate_flrg">[docs]</a> <span class="k">def</span> <span class="nf">generate_flrg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrs</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">flr</span> <span class="ow">in</span> <span class="n">flrs</span><span class="p">:</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">str</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">index</span><span class="p">)</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">index</span><span class="p">)]</span> <span class="o">=</span> <span class="n">ContextualSeasonalFLRG</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">index</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">index</span><span class="p">)]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ContextualMultiSeasonalFTS.train"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.cmsfts.ContextualMultiSeasonalFTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'sets'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'sets'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'parameters'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">seasonality</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'parameters'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="n">flrs</span> <span class="o">=</span> <span class="n">FLR</span><span class="o">.</span><span class="n">generate_indexed_flrs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span>
|
||||
<span class="n">transformation</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">transformation</span><span class="p">,</span>
|
||||
<span class="n">alpha_cut</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">alpha_cut</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">generate_flrg</span><span class="p">(</span><span class="n">flrs</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ContextualMultiSeasonalFTS.get_midpoints"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.cmsfts.ContextualMultiSeasonalFTS.get_midpoints">[docs]</a> <span class="k">def</span> <span class="nf">get_midpoints</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrg</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">data</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">d</span> <span class="ow">in</span> <span class="n">flrg</span><span class="o">.</span><span class="n">RHS</span><span class="p">:</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">flrg</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">d</span><span class="p">]</span><span class="o">.</span><span class="n">RHS</span><span class="p">])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">d</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span><span class="p">])</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">ret</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ContextualMultiSeasonalFTS.forecast"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.cmsfts.ContextualMultiSeasonalFTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">ordered_sets</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">set_ordered</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">index</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_season_of_data</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_data</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)):</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">str</span><span class="p">(</span><span class="n">index</span><span class="p">[</span><span class="n">k</span><span class="p">])</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">index</span><span class="p">[</span><span class="n">k</span><span class="p">])]</span>
|
||||
|
||||
<span class="n">d</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">get_fuzzysets</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="p">,</span> <span class="n">alpha_cut</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">alpha_cut</span><span class="p">)</span>
|
||||
|
||||
<span class="n">mp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_midpoints</span><span class="p">(</span><span class="n">flrg</span><span class="p">,</span> <span class="n">d</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">sum</span><span class="p">(</span><span class="n">mp</span><span class="p">)</span> <span class="o">/</span> <span class="nb">len</span><span class="p">(</span><span class="n">mp</span><span class="p">))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ContextualMultiSeasonalFTS.forecast_ahead"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.cmsfts.ContextualMultiSeasonalFTS.forecast_ahead">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">steps</span><span class="p">:</span>
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span>
|
||||
|
||||
<span class="n">mp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_midpoints</span><span class="p">(</span><span class="n">flrg</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">sum</span><span class="p">(</span><span class="n">mp</span><span class="p">)</span> <span class="o">/</span> <span class="nb">len</span><span class="p">(</span><span class="n">mp</span><span class="p">))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div></div>
|
||||
|
||||
|
||||
</pre></div>
|
||||
|
||||
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|
||||
</html>
|
||||
175
docs/_build/html/_modules/pyFTS/models/seasonal/common.html
vendored
Normal file
175
docs/_build/html/_modules/pyFTS/models/seasonal/common.html
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Normal file
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<h1>Source code for pyFTS.models.seasonal.common</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
<span class="kn">from</span> <span class="nn">enum</span> <span class="k">import</span> <span class="n">Enum</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">Membership</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">partitioner</span><span class="p">,</span> <span class="n">Grid</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="DateTime"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.common.DateTime">[docs]</a><span class="k">class</span> <span class="nc">DateTime</span><span class="p">(</span><span class="n">Enum</span><span class="p">):</span>
|
||||
<span class="n">year</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="n">month</span> <span class="o">=</span> <span class="mi">12</span>
|
||||
<span class="n">day_of_month</span> <span class="o">=</span> <span class="mi">30</span>
|
||||
<span class="n">day_of_year</span> <span class="o">=</span> <span class="mi">364</span>
|
||||
<span class="n">day_of_week</span> <span class="o">=</span> <span class="mi">7</span>
|
||||
<span class="n">hour</span> <span class="o">=</span> <span class="mi">6</span>
|
||||
<span class="n">minute</span> <span class="o">=</span> <span class="mi">7</span>
|
||||
<span class="n">second</span> <span class="o">=</span> <span class="mi">8</span>
|
||||
<span class="n">hour_of_day</span> <span class="o">=</span> <span class="mi">24</span>
|
||||
<span class="n">hour_of_week</span> <span class="o">=</span> <span class="mi">168</span>
|
||||
<span class="n">hour_of_month</span> <span class="o">=</span> <span class="mi">744</span>
|
||||
<span class="n">hour_of_year</span> <span class="o">=</span> <span class="mi">8736</span>
|
||||
<span class="n">minute_of_hour</span> <span class="o">=</span> <span class="mi">60</span>
|
||||
<span class="n">minute_of_day</span> <span class="o">=</span> <span class="mi">1440</span>
|
||||
<span class="n">minute_of_week</span> <span class="o">=</span> <span class="mi">10080</span>
|
||||
<span class="n">minute_of_month</span> <span class="o">=</span> <span class="mi">44640</span>
|
||||
<span class="n">minute_of_year</span> <span class="o">=</span> <span class="mi">524160</span>
|
||||
<span class="n">second_of_minute</span> <span class="o">=</span> <span class="mf">60.00001</span>
|
||||
<span class="n">second_of_hour</span> <span class="o">=</span> <span class="mi">3600</span>
|
||||
<span class="n">second_of_day</span> <span class="o">=</span> <span class="mi">86400</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="strip_datepart"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.common.strip_datepart">[docs]</a><span class="k">def</span> <span class="nf">strip_datepart</span><span class="p">(</span><span class="n">date</span><span class="p">,</span> <span class="n">date_part</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">year</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">year</span>
|
||||
<span class="k">elif</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">month</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">month</span>
|
||||
<span class="k">elif</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">day_of_year</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">timetuple</span><span class="p">()</span><span class="o">.</span><span class="n">tm_yday</span>
|
||||
<span class="k">elif</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">day_of_month</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">day</span>
|
||||
<span class="k">elif</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">day_of_week</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">weekday</span><span class="p">()</span>
|
||||
<span class="k">elif</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">hour</span> <span class="ow">or</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">hour_of_day</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">hour</span>
|
||||
<span class="k">elif</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">hour_of_week</span><span class="p">:</span>
|
||||
<span class="n">wk</span> <span class="o">=</span> <span class="p">(</span><span class="n">date</span><span class="o">.</span><span class="n">weekday</span><span class="p">()</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="mi">24</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">hour</span> <span class="o">+</span> <span class="n">wk</span>
|
||||
<span class="k">elif</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">hour_of_month</span><span class="p">:</span>
|
||||
<span class="n">wk</span> <span class="o">=</span> <span class="p">(</span><span class="n">date</span><span class="o">.</span><span class="n">day</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="mi">24</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">hour</span> <span class="o">+</span> <span class="n">wk</span>
|
||||
<span class="k">elif</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">hour_of_year</span><span class="p">:</span>
|
||||
<span class="n">wk</span> <span class="o">=</span> <span class="p">(</span><span class="n">date</span><span class="o">.</span><span class="n">timetuple</span><span class="p">()</span><span class="o">.</span><span class="n">tm_yday</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="mi">24</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">hour</span> <span class="o">+</span> <span class="n">wk</span>
|
||||
<span class="k">elif</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">minute</span> <span class="ow">or</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">minute_of_hour</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">minute</span>
|
||||
<span class="k">elif</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">minute_of_day</span><span class="p">:</span>
|
||||
<span class="n">wk</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">hour</span> <span class="o">*</span> <span class="mi">60</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">minute</span> <span class="o">+</span> <span class="n">wk</span>
|
||||
<span class="k">elif</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">minute_of_week</span><span class="p">:</span>
|
||||
<span class="n">wk1</span> <span class="o">=</span> <span class="p">(</span><span class="n">date</span><span class="o">.</span><span class="n">weekday</span><span class="p">()</span><span class="o">-</span><span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="mi">1440</span> <span class="c1">#24 * 60</span>
|
||||
<span class="n">wk2</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">hour</span> <span class="o">*</span> <span class="mi">60</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">minute</span> <span class="o">+</span> <span class="n">wk1</span> <span class="o">+</span> <span class="n">wk2</span>
|
||||
<span class="k">elif</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">minute_of_month</span><span class="p">:</span>
|
||||
<span class="n">wk1</span> <span class="o">=</span> <span class="p">(</span><span class="n">date</span><span class="o">.</span><span class="n">day</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="mi">1440</span> <span class="c1">#24 * 60</span>
|
||||
<span class="n">wk2</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">hour</span> <span class="o">*</span> <span class="mi">60</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">minute</span> <span class="o">+</span> <span class="n">wk1</span> <span class="o">+</span> <span class="n">wk2</span>
|
||||
<span class="k">elif</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">minute_of_year</span><span class="p">:</span>
|
||||
<span class="n">wk1</span> <span class="o">=</span> <span class="p">(</span><span class="n">date</span><span class="o">.</span><span class="n">timetuple</span><span class="p">()</span><span class="o">.</span><span class="n">tm_yday</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="o">*</span> <span class="mi">1440</span> <span class="c1">#24 * 60</span>
|
||||
<span class="n">wk2</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">hour</span> <span class="o">*</span> <span class="mi">60</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">minute</span> <span class="o">+</span> <span class="n">wk1</span> <span class="o">+</span> <span class="n">wk2</span>
|
||||
<span class="k">elif</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">second</span> <span class="ow">or</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">second_of_minute</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">second</span>
|
||||
<span class="k">elif</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">second_of_hour</span><span class="p">:</span>
|
||||
<span class="n">wk1</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">minute</span> <span class="o">*</span> <span class="mi">60</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">second</span> <span class="o">+</span> <span class="n">wk1</span>
|
||||
<span class="k">elif</span> <span class="n">date_part</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">second_of_day</span><span class="p">:</span>
|
||||
<span class="n">wk1</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">hour</span> <span class="o">*</span> <span class="mi">3600</span> <span class="c1">#60 * 60</span>
|
||||
<span class="n">wk2</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">minute</span> <span class="o">*</span> <span class="mi">60</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">date</span><span class="o">.</span><span class="n">second</span> <span class="o">+</span> <span class="n">wk1</span> <span class="o">+</span> <span class="n">wk2</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s2">"Unknown DateTime value!"</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">tmp</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="FuzzySet"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.common.FuzzySet">[docs]</a><span class="k">class</span> <span class="nc">FuzzySet</span><span class="p">(</span><span class="n">FuzzySet</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Temporal/Seasonal Fuzzy Set</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">datepart</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">mf</span><span class="p">,</span> <span class="n">parameters</span><span class="p">,</span> <span class="n">centroid</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">FuzzySet</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="n">mf</span><span class="p">,</span> <span class="n">parameters</span><span class="p">,</span> <span class="n">centroid</span><span class="p">,</span> <span class="n">alpha</span><span class="p">,</span> <span class="nb">type</span> <span class="o">=</span> <span class="s1">'datetime'</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">datepart</span> <span class="o">=</span> <span class="n">datepart</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">=</span> <span class="s1">'seasonal'</span>
|
||||
|
||||
<div class="viewcode-block" id="FuzzySet.membership"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.common.FuzzySet.membership">[docs]</a> <span class="k">def</span> <span class="nf">membership</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
|
||||
<span class="n">dp</span> <span class="o">=</span> <span class="n">strip_datepart</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">datepart</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">mf</span><span class="p">(</span><span class="n">dp</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">parameters</span><span class="p">)</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">alpha</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
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|
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144
docs/_build/html/_modules/pyFTS/models/seasonal/msfts.html
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<h1>Source code for pyFTS.models.seasonal.msfts</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FLR</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models.seasonal</span> <span class="k">import</span> <span class="n">sfts</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="MultiSeasonalFTS"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.msfts.MultiSeasonalFTS">[docs]</a><span class="k">class</span> <span class="nc">MultiSeasonalFTS</span><span class="p">(</span><span class="n">sfts</span><span class="o">.</span><span class="n">SeasonalFTS</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Multi-Seasonal Fuzzy Time Series</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">indexer</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">MultiSeasonalFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="s2">"MSFTS"</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Multi Seasonal FTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">"MSFTS "</span> <span class="o">+</span> <span class="n">name</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">seasonality</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_seasonality</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_point_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_multivariate</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">indexer</span> <span class="o">=</span> <span class="n">indexer</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<div class="viewcode-block" id="MultiSeasonalFTS.generate_flrg"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.msfts.MultiSeasonalFTS.generate_flrg">[docs]</a> <span class="k">def</span> <span class="nf">generate_flrg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrs</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">flr</span> <span class="ow">in</span> <span class="n">flrs</span><span class="p">:</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">str</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">index</span><span class="p">)</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">index</span><span class="p">)]</span> <span class="o">=</span> <span class="n">sfts</span><span class="o">.</span><span class="n">SeasonalFLRG</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">index</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">index</span><span class="p">)]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="MultiSeasonalFTS.train"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.msfts.MultiSeasonalFTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'sets'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'sets'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'parameters'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">seasonality</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'parameters'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="c1">#ndata = self.indexer.set_data(data,self.doTransformations(self.indexer.get_data(data)))</span>
|
||||
<span class="n">flrs</span> <span class="o">=</span> <span class="n">FLR</span><span class="o">.</span><span class="n">generate_indexed_flrs</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="p">,</span> <span class="n">data</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">generate_flrg</span><span class="p">(</span><span class="n">flrs</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="MultiSeasonalFTS.forecast"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.msfts.MultiSeasonalFTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="n">index</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_season_of_data</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_data</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">index</span><span class="p">)):</span>
|
||||
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">index</span><span class="p">[</span><span class="n">k</span><span class="p">])]</span>
|
||||
|
||||
<span class="n">mp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">getMidpoints</span><span class="p">(</span><span class="n">flrg</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">sum</span><span class="p">(</span><span class="n">mp</span><span class="p">)</span> <span class="o">/</span> <span class="nb">len</span><span class="p">(</span><span class="n">mp</span><span class="p">))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="MultiSeasonalFTS.forecast_ahead"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.msfts.MultiSeasonalFTS.forecast_ahead">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">steps</span><span class="p">:</span>
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">i</span><span class="p">)]</span>
|
||||
|
||||
<span class="n">mp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">getMidpoints</span><span class="p">(</span><span class="n">flrg</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">sum</span><span class="p">(</span><span class="n">mp</span><span class="p">)</span> <span class="o">/</span> <span class="nb">len</span><span class="p">(</span><span class="n">mp</span><span class="p">))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
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|
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|
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|
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|
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|
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|
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|
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|
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197
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<h1>Source code for pyFTS.models.seasonal.partitioner</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">FuzzySet</span> <span class="k">as</span> <span class="n">FS</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common.Composite</span> <span class="k">import</span> <span class="n">FuzzySet</span> <span class="k">as</span> <span class="n">Composite</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">partitioner</span><span class="p">,</span> <span class="n">Grid</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models.seasonal.common</span> <span class="k">import</span> <span class="n">DateTime</span><span class="p">,</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">strip_datepart</span>
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">matplotlib.pylab</span> <span class="k">as</span> <span class="nn">plt</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="TimeGridPartitioner"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.partitioner.TimeGridPartitioner">[docs]</a><span class="k">class</span> <span class="nc">TimeGridPartitioner</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="n">Partitioner</span><span class="p">):</span>
|
||||
<span class="sd">"""Even Length DateTime Grid Partitioner"""</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Even Length Grid Partitioner</span>
|
||||
<span class="sd"> :param seasonality: Time granularity, from pyFTS.models.seasonal.common.DateTime</span>
|
||||
<span class="sd"> :param data: Training data of which the universe of discourse will be extracted. The universe of discourse is the open interval between the minimum and maximum values of the training data.</span>
|
||||
<span class="sd"> :param npart: The number of universe of discourse partitions, i.e., the number of fuzzy sets that will be created</span>
|
||||
<span class="sd"> :param func: Fuzzy membership function (pyFTS.common.Membership)</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">TimeGridPartitioner</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"TimeGrid"</span><span class="p">,</span> <span class="n">preprocess</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">season</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'seasonality'</span><span class="p">,</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">day_of_year</span><span class="p">)</span>
|
||||
<span class="n">data</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'data'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">season</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">year</span><span class="p">:</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="p">[</span><span class="n">strip_datepart</span><span class="p">(</span><span class="n">k</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="p">)</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">data</span><span class="p">]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">max</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="o">.</span><span class="n">value</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitions</span><span class="p">)</span> <span class="o">/</span> <span class="mi">2</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min</span> <span class="o">=</span> <span class="n">tmp</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">max</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="o">.</span><span class="n">value</span> <span class="o">+</span> <span class="n">tmp</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">build</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">setnames</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">setnames</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span> <span class="o">=</span> <span class="n">FS</span><span class="o">.</span><span class="n">set_ordered</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="TimeGridPartitioner.build"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.partitioner.TimeGridPartitioner.build">[docs]</a> <span class="k">def</span> <span class="nf">build</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="n">sets</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<span class="n">kwargs</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'variable'</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">variable</span><span class="p">}</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">season</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">year</span><span class="p">:</span>
|
||||
<span class="n">dlen</span> <span class="o">=</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">min</span><span class="p">)</span>
|
||||
<span class="n">partlen</span> <span class="o">=</span> <span class="n">dlen</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitions</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">partlen</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="o">.</span><span class="n">value</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitions</span>
|
||||
<span class="n">pl2</span> <span class="o">=</span> <span class="n">partlen</span> <span class="o">/</span> <span class="mi">2</span>
|
||||
|
||||
<span class="n">count</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">min</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">max</span><span class="p">,</span> <span class="n">partlen</span><span class="p">):</span>
|
||||
<span class="n">set_name</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_name</span><span class="p">(</span><span class="n">count</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">membership_function</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">c</span> <span class="o">==</span> <span class="bp">self</span><span class="o">.</span><span class="n">min</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">Composite</span><span class="p">(</span><span class="n">set_name</span><span class="p">,</span> <span class="n">superset</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append_set</span><span class="p">(</span><span class="n">FuzzySet</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="p">,</span> <span class="n">set_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">,</span>
|
||||
<span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="o">.</span><span class="n">value</span> <span class="o">-</span> <span class="n">pl2</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="o">.</span><span class="n">value</span><span class="p">,</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="o">.</span><span class="n">value</span> <span class="o">+</span> <span class="mf">0.0000001</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=.</span><span class="mi">5</span><span class="p">,</span>
|
||||
<span class="o">**</span><span class="n">kwargs</span><span class="p">))</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append_set</span><span class="p">(</span><span class="n">FuzzySet</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="p">,</span> <span class="n">set_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">,</span>
|
||||
<span class="p">[</span><span class="n">c</span> <span class="o">-</span> <span class="n">partlen</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="n">c</span> <span class="o">+</span> <span class="n">partlen</span><span class="p">],</span> <span class="n">c</span><span class="p">,</span>
|
||||
<span class="o">**</span><span class="n">kwargs</span><span class="p">))</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">centroid</span> <span class="o">=</span> <span class="n">c</span>
|
||||
<span class="n">sets</span><span class="p">[</span><span class="n">set_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">tmp</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">sets</span><span class="p">[</span><span class="n">set_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="p">,</span> <span class="n">set_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">,</span>
|
||||
<span class="p">[</span><span class="n">c</span> <span class="o">-</span> <span class="n">partlen</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="n">c</span> <span class="o">+</span> <span class="n">partlen</span><span class="p">],</span> <span class="n">c</span><span class="p">,</span>
|
||||
<span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">membership_function</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">gaussmf</span><span class="p">:</span>
|
||||
<span class="n">sets</span><span class="p">[</span><span class="n">set_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="p">,</span> <span class="n">set_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">gaussmf</span><span class="p">,</span> <span class="p">[</span><span class="n">c</span><span class="p">,</span> <span class="n">partlen</span> <span class="o">/</span> <span class="mi">3</span><span class="p">],</span> <span class="n">c</span><span class="p">,</span>
|
||||
<span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">membership_function</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span><span class="p">:</span>
|
||||
<span class="n">q</span> <span class="o">=</span> <span class="n">partlen</span> <span class="o">/</span> <span class="mi">4</span>
|
||||
<span class="k">if</span> <span class="n">c</span> <span class="o">==</span> <span class="bp">self</span><span class="o">.</span><span class="n">min</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">Composite</span><span class="p">(</span><span class="n">set_name</span><span class="p">,</span> <span class="n">superset</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append_set</span><span class="p">(</span><span class="n">FuzzySet</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="p">,</span> <span class="n">set_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">,</span>
|
||||
<span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="o">.</span><span class="n">value</span> <span class="o">-</span> <span class="n">pl2</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="o">.</span><span class="n">value</span><span class="p">,</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="o">.</span><span class="n">value</span> <span class="o">+</span> <span class="mf">0.0000001</span><span class="p">],</span> <span class="mi">0</span><span class="p">,</span>
|
||||
<span class="o">**</span><span class="n">kwargs</span><span class="p">))</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">append_set</span><span class="p">(</span><span class="n">FuzzySet</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="p">,</span> <span class="n">set_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span><span class="p">,</span>
|
||||
<span class="p">[</span><span class="n">c</span> <span class="o">-</span> <span class="n">partlen</span><span class="p">,</span> <span class="n">c</span> <span class="o">-</span> <span class="n">q</span><span class="p">,</span> <span class="n">c</span> <span class="o">+</span> <span class="n">q</span><span class="p">,</span> <span class="n">c</span> <span class="o">+</span> <span class="n">partlen</span><span class="p">],</span> <span class="n">c</span><span class="p">,</span>
|
||||
<span class="o">**</span><span class="n">kwargs</span><span class="p">))</span>
|
||||
<span class="n">tmp</span><span class="o">.</span><span class="n">centroid</span> <span class="o">=</span> <span class="n">c</span>
|
||||
<span class="n">sets</span><span class="p">[</span><span class="n">set_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">tmp</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">sets</span><span class="p">[</span><span class="n">set_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="p">,</span> <span class="n">set_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span><span class="p">,</span>
|
||||
<span class="p">[</span><span class="n">c</span> <span class="o">-</span> <span class="n">partlen</span><span class="p">,</span> <span class="n">c</span> <span class="o">-</span> <span class="n">q</span><span class="p">,</span> <span class="n">c</span> <span class="o">+</span> <span class="n">q</span><span class="p">,</span> <span class="n">c</span> <span class="o">+</span> <span class="n">partlen</span><span class="p">],</span> <span class="n">c</span><span class="p">,</span>
|
||||
<span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="n">count</span> <span class="o">+=</span> <span class="mi">1</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">sets</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="TimeGridPartitioner.plot"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.partitioner.TimeGridPartitioner.plot">[docs]</a> <span class="k">def</span> <span class="nf">plot</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ax</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Plot the</span>
|
||||
<span class="sd"> :param ax:</span>
|
||||
<span class="sd"> :return:</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">set_ylim</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">set_xlim</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="o">.</span><span class="n">value</span><span class="p">])</span>
|
||||
<span class="n">ticks</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">x</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
|
||||
<span class="n">s</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="n">s</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="s1">'composite'</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">ss</span> <span class="ow">in</span> <span class="n">s</span><span class="o">.</span><span class="n">sets</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">plot_set</span><span class="p">(</span><span class="n">ax</span><span class="p">,</span> <span class="n">ss</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">plot_set</span><span class="p">(</span><span class="n">ax</span><span class="p">,</span> <span class="n">s</span><span class="p">)</span>
|
||||
<span class="n">ticks</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">centroid</span><span class="p">,</span> <span class="mi">0</span><span class="p">))</span> <span class="o">+</span> <span class="s1">'</span><span class="se">\n</span><span class="s1">'</span> <span class="o">+</span> <span class="n">s</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
|
||||
<span class="n">x</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">centroid</span><span class="p">)</span>
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<h1>Source code for pyFTS.models.seasonal.sfts</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">Simple First Order Seasonal Fuzzy Time Series implementation of Song (1999) based of Conventional FTS by Chen (1996)</span>
|
||||
|
||||
<span class="sd">Q. Song, “Seasonal forecasting in fuzzy time series,” Fuzzy sets Syst., vol. 107, pp. 235–236, 1999.</span>
|
||||
|
||||
<span class="sd">S.-M. Chen, “Forecasting enrollments based on fuzzy time series,” Fuzzy Sets Syst., vol. 81, no. 3, pp. 311–319, 1996.</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">flrg</span><span class="p">,</span> <span class="n">fts</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="SeasonalFLRG"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.sfts.SeasonalFLRG">[docs]</a><span class="k">class</span> <span class="nc">SeasonalFLRG</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">):</span>
|
||||
<span class="sd">"""First Order Seasonal Fuzzy Logical Relationship Group"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">seasonality</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">SeasonalFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="n">seasonality</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<div class="viewcode-block" id="SeasonalFLRG.get_key"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.sfts.SeasonalFLRG.get_key">[docs]</a> <span class="k">def</span> <span class="nf">get_key</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SeasonalFLRG.append_rhs"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.sfts.SeasonalFLRG.append_rhs">[docs]</a> <span class="k">def</span> <span class="nf">append_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">c</span><span class="p">)</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">+</span> <span class="s2">" -> "</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">,</span> <span class="n">key</span><span class="o">=</span><span class="k">lambda</span> <span class="n">s</span><span class="p">:</span> <span class="nb">str</span><span class="p">(</span><span class="n">s</span><span class="p">)):</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">tmp2</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="n">tmp2</span> <span class="o">+</span> <span class="s2">","</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="n">tmp2</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">c</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">tmp</span> <span class="o">+</span> <span class="n">tmp2</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="SeasonalFTS"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.sfts.SeasonalFTS">[docs]</a><span class="k">class</span> <span class="nc">SeasonalFTS</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
|
||||
<span class="sd">"""First Order Seasonal Fuzzy Time Series"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">SeasonalFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Seasonal FTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">"SFTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">seasonality</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_seasonality</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">has_point_forecasting</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<div class="viewcode-block" id="SeasonalFTS.generate_flrg"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.sfts.SeasonalFTS.generate_flrg">[docs]</a> <span class="k">def</span> <span class="nf">generate_flrg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrs</span><span class="p">):</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">flr</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">flrs</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
|
||||
|
||||
<span class="n">season</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_season_by_index</span><span class="p">(</span><span class="n">ct</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
|
||||
|
||||
<span class="n">ss</span> <span class="o">=</span> <span class="nb">str</span><span class="p">(</span><span class="n">season</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">ss</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">ss</span><span class="p">]</span> <span class="o">=</span> <span class="n">SeasonalFLRG</span><span class="p">(</span><span class="n">season</span><span class="p">)</span>
|
||||
|
||||
<span class="c1">#print(season)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">ss</span><span class="p">]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SeasonalFTS.get_midpoints"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.sfts.SeasonalFTS.get_midpoints">[docs]</a> <span class="k">def</span> <span class="nf">get_midpoints</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrg</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">s</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">flrg</span><span class="o">.</span><span class="n">RHS</span><span class="p">])</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SeasonalFTS.train"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.sfts.SeasonalFTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'sets'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'sets'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="n">tmpdata</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">fuzzyfy_series_old</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
<span class="n">flrs</span> <span class="o">=</span> <span class="n">FLR</span><span class="o">.</span><span class="n">generate_non_recurrent_flrs</span><span class="p">(</span><span class="n">tmpdata</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">generate_flrg</span><span class="p">(</span><span class="n">flrs</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="SeasonalFTS.forecast"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.sfts.SeasonalFTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
|
||||
<span class="n">season</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_season_by_index</span><span class="p">(</span><span class="n">k</span><span class="p">)[</span><span class="mi">0</span><span class="p">]</span>
|
||||
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">season</span><span class="p">)]</span>
|
||||
|
||||
<span class="n">mp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_midpoints</span><span class="p">(</span><span class="n">flrg</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">percentile</span><span class="p">(</span><span class="n">mp</span><span class="p">,</span> <span class="mi">50</span><span class="p">))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
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|
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<h1>Source code for pyFTS.models.song</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">First Order Traditional Fuzzy Time Series method by Song & Chissom (1993)</span>
|
||||
|
||||
<span class="sd">Q. Song and B. S. Chissom, “Fuzzy time series and its models,” Fuzzy Sets Syst., vol. 54, no. 3, pp. 269–277, 1993.</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ConventionalFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.song.ConventionalFTS">[docs]</a><span class="k">class</span> <span class="nc">ConventionalFTS</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
|
||||
<span class="sd">"""Traditional Fuzzy Time Series"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">ConventionalFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">"FTS"</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Traditional FTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">"Song & Chissom"</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">R</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">R</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">l</span><span class="p">,</span><span class="n">l</span><span class="p">))</span>
|
||||
|
||||
<div class="viewcode-block" id="ConventionalFTS.flr_membership_matrix"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.song.ConventionalFTS.flr_membership_matrix">[docs]</a> <span class="k">def</span> <span class="nf">flr_membership_matrix</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flr</span><span class="p">):</span>
|
||||
<span class="n">ordered_set</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">set_ordered</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
<span class="n">centroids</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">k</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">ordered_set</span><span class="p">]</span>
|
||||
<span class="n">lm</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">k</span><span class="p">)</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">centroids</span><span class="p">]</span>
|
||||
<span class="n">rm</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">k</span><span class="p">)</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">centroids</span><span class="p">]</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ordered_set</span><span class="p">)</span>
|
||||
<span class="n">r</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">l</span><span class="p">,</span> <span class="n">l</span><span class="p">))</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="n">l</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">l</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
<span class="n">r</span><span class="p">[</span><span class="n">k</span><span class="p">][</span><span class="n">l</span><span class="p">]</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">lm</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="n">rm</span><span class="p">[</span><span class="n">l</span><span class="p">])</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">r</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ConventionalFTS.operation_matrix"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.song.ConventionalFTS.operation_matrix">[docs]</a> <span class="k">def</span> <span class="nf">operation_matrix</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrs</span><span class="p">):</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">R</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">or</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">R</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span> <span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">R</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">((</span><span class="n">l</span><span class="p">,</span> <span class="n">l</span><span class="p">))</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">flrs</span><span class="p">:</span>
|
||||
<span class="n">mm</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flr_membership_matrix</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">l</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">R</span><span class="p">[</span><span class="n">k</span><span class="p">][</span><span class="n">l</span><span class="p">]</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">R</span><span class="p">[</span><span class="n">k</span><span class="p">][</span><span class="n">l</span><span class="p">],</span> <span class="n">mm</span><span class="p">[</span><span class="n">k</span><span class="p">][</span><span class="n">l</span><span class="p">])</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ConventionalFTS.train"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.song.ConventionalFTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="n">tmpdata</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">fuzzyfy_series</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s1">'maximum'</span><span class="p">)</span>
|
||||
<span class="n">flrs</span> <span class="o">=</span> <span class="n">FLR</span><span class="o">.</span><span class="n">generate_non_recurrent_flrs</span><span class="p">(</span><span class="n">tmpdata</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">operation_matrix</span><span class="p">(</span><span class="n">flrs</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ConventionalFTS.forecast"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.song.ConventionalFTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">ordered_sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ordered_sets</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">set_ordered</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
<span class="n">npart</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
<span class="n">mv</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">fuzzyfy_instance</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
|
||||
<span class="n">r</span> <span class="o">=</span> <span class="p">[</span><span class="nb">max</span><span class="p">([</span> <span class="nb">min</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">R</span><span class="p">[</span><span class="n">i</span><span class="p">][</span><span class="n">j</span><span class="p">],</span> <span class="n">mv</span><span class="p">[</span><span class="n">j</span><span class="p">])</span> <span class="k">for</span> <span class="n">j</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="n">npart</span><span class="p">)</span> <span class="p">])</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="n">npart</span><span class="p">)]</span>
|
||||
|
||||
<span class="n">fs</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">r</span> <span class="o">==</span> <span class="nb">max</span><span class="p">(</span><span class="n">r</span><span class="p">)))</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">fs</span><span class="p">)</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">fs</span><span class="p">[</span><span class="mi">0</span><span class="p">]]]</span><span class="o">.</span><span class="n">centroid</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">mp</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">s</span><span class="p">]]</span><span class="o">.</span><span class="n">centroid</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="n">fs</span><span class="p">]</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span> <span class="nb">sum</span><span class="p">(</span><span class="n">mp</span><span class="p">)</span><span class="o">/</span><span class="nb">len</span><span class="p">(</span><span class="n">mp</span><span class="p">))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">+</span> <span class="s2">":</span><span class="se">\n</span><span class="s2">"</span>
|
||||
<span class="k">return</span> <span class="n">tmp</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">R</span><span class="p">)</span></div>
|
||||
</pre></div>
|
||||
|
||||
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|
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|
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|
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<h1>Source code for pyFTS.models.yu</h1><div class="highlight"><pre>
|
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<span></span><span class="sd">"""</span>
|
||||
<span class="sd">First Order Weighted Fuzzy Time Series by Yu(2005)</span>
|
||||
|
||||
<span class="sd">H.-K. Yu, “Weighted fuzzy time series models for TAIEX forecasting,” </span>
|
||||
<span class="sd">Phys. A Stat. Mech. its Appl., vol. 349, no. 3, pp. 609–624, 2005.</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">chen</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="WeightedFLRG"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.yu.WeightedFLRG">[docs]</a><span class="k">class</span> <span class="nc">WeightedFLRG</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">):</span>
|
||||
<span class="sd">"""First Order Weighted Fuzzy Logical Relationship Group"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">LHS</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">WeightedFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="n">LHS</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="o">=</span> <span class="mf">1.0</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
|
||||
<div class="viewcode-block" id="WeightedFLRG.append_rhs"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.yu.WeightedFLRG.append_rhs">[docs]</a> <span class="k">def</span> <span class="nf">append_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">c</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="o">+</span> <span class="mf">1.0</span></div>
|
||||
|
||||
<div class="viewcode-block" id="WeightedFLRG.weights"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.yu.WeightedFLRG.weights">[docs]</a> <span class="k">def</span> <span class="nf">weights</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">tot</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mf">1.0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">count</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">))</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">k</span> <span class="o">/</span> <span class="n">tot</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mf">1.0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">count</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">)])</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">w</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">+</span> <span class="s2">" -> "</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
<span class="n">cc</span> <span class="o">=</span> <span class="mf">1.0</span>
|
||||
<span class="n">tot</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mf">1.0</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">count</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">))</span>
|
||||
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">tmp2</span><span class="p">)</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="n">tmp2</span> <span class="o">+</span> <span class="s2">","</span>
|
||||
<span class="n">tmp2</span> <span class="o">=</span> <span class="n">tmp2</span> <span class="o">+</span> <span class="n">c</span> <span class="o">+</span> <span class="s2">"("</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">cc</span> <span class="o">/</span> <span class="n">tot</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span> <span class="o">+</span> <span class="s2">")"</span>
|
||||
<span class="n">cc</span> <span class="o">=</span> <span class="n">cc</span> <span class="o">+</span> <span class="mf">1.0</span>
|
||||
<span class="k">return</span> <span class="n">tmp</span> <span class="o">+</span> <span class="n">tmp2</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="WeightedFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.yu.WeightedFTS">[docs]</a><span class="k">class</span> <span class="nc">WeightedFTS</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
|
||||
<span class="sd">"""First Order Weighted Fuzzy Time Series"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">WeightedFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s2">"WFTS"</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Weighted FTS"</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">"Yu"</span>
|
||||
|
||||
<div class="viewcode-block" id="WeightedFTS.generate_FLRG"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.yu.WeightedFTS.generate_FLRG">[docs]</a> <span class="k">def</span> <span class="nf">generate_FLRG</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrs</span><span class="p">):</span>
|
||||
<span class="k">for</span> <span class="n">flr</span> <span class="ow">in</span> <span class="n">flrs</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">flr</span><span class="o">.</span><span class="n">LHS</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span> <span class="o">=</span> <span class="n">WeightedFLRG</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">);</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="WeightedFTS.train"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.yu.WeightedFTS.train">[docs]</a> <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="n">tmpdata</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">fuzzyfy_series</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s1">'maximum'</span><span class="p">)</span>
|
||||
<span class="n">flrs</span> <span class="o">=</span> <span class="n">FLR</span><span class="o">.</span><span class="n">generate_recurrent_flrs</span><span class="p">(</span><span class="n">tmpdata</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">generate_FLRG</span><span class="p">(</span><span class="n">flrs</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="WeightedFTS.forecast"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.yu.WeightedFTS.forecast">[docs]</a> <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">ordered_sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">ordered_sets</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ordered_sets</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">set_ordered</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
|
||||
|
||||
<span class="n">actual</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">get_maximum_membership_fuzzyset</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">actual</span><span class="o">.</span><span class="n">name</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">actual</span><span class="o">.</span><span class="n">centroid</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">flrg</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">actual</span><span class="o">.</span><span class="n">name</span><span class="p">]</span>
|
||||
<span class="n">mp</span> <span class="o">=</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_midpoints</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mp</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">weights</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
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|
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<li><a href="../../../index.html">Documentation overview</a><ul>
|
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<h3>Quick search</h3>
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<h1>Source code for pyFTS.partitioners.CMeans</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">math</span>
|
||||
<span class="kn">import</span> <span class="nn">random</span> <span class="k">as</span> <span class="nn">rnd</span>
|
||||
<span class="kn">import</span> <span class="nn">functools</span><span class="o">,</span> <span class="nn">operator</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">Membership</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">partitioner</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="distance"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.CMeans.distance">[docs]</a><span class="k">def</span> <span class="nf">distance</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">functools</span><span class="o">.</span><span class="n">reduce</span><span class="p">(</span><span class="n">operator</span><span class="o">.</span><span class="n">add</span><span class="p">,</span> <span class="p">[(</span><span class="n">x</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">-</span> <span class="n">y</span><span class="p">[</span><span class="n">k</span><span class="p">])</span> <span class="o">**</span> <span class="mi">2</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">x</span><span class="p">))])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">(</span><span class="n">x</span> <span class="o">-</span> <span class="n">y</span><span class="p">)</span> <span class="o">**</span> <span class="mi">2</span>
|
||||
<span class="k">return</span> <span class="n">math</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="c_means"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.CMeans.c_means">[docs]</a><span class="k">def</span> <span class="nf">c_means</span><span class="p">(</span><span class="n">k</span><span class="p">,</span> <span class="n">dados</span><span class="p">,</span> <span class="n">tam</span><span class="p">):</span>
|
||||
<span class="c1"># Inicializa as centróides escolhendo elementos aleatórios dos conjuntos</span>
|
||||
<span class="n">centroides</span> <span class="o">=</span> <span class="p">[</span><span class="n">dados</span><span class="p">[</span><span class="n">rnd</span><span class="o">.</span><span class="n">randint</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">dados</span><span class="p">)</span><span class="o">-</span><span class="mi">1</span><span class="p">)]</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">k</span><span class="p">)]</span>
|
||||
|
||||
<span class="n">grupos</span> <span class="o">=</span> <span class="p">[</span><span class="o">-</span><span class="mi">1</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">dados</span><span class="p">))]</span>
|
||||
|
||||
<span class="n">it_semmodificacao</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
|
||||
<span class="c1"># para cada instância</span>
|
||||
<span class="n">iteracoes</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">while</span> <span class="n">iteracoes</span> <span class="o"><</span> <span class="mi">1000</span> <span class="ow">and</span> <span class="n">it_semmodificacao</span> <span class="o"><</span> <span class="mi">10</span><span class="p">:</span>
|
||||
<span class="n">inst_count</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
|
||||
<span class="n">modificacao</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">instancia</span> <span class="ow">in</span> <span class="n">dados</span><span class="p">:</span>
|
||||
|
||||
<span class="c1"># verifica a distância para cada centroide</span>
|
||||
<span class="n">grupo_count</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="n">dist</span> <span class="o">=</span> <span class="mi">10000</span>
|
||||
|
||||
<span class="n">grupotmp</span> <span class="o">=</span> <span class="n">grupos</span><span class="p">[</span><span class="n">inst_count</span><span class="p">]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">grupo</span> <span class="ow">in</span> <span class="n">centroides</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">distance</span><span class="p">(</span><span class="n">instancia</span><span class="p">,</span> <span class="n">grupo</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">tmp</span> <span class="o"><</span> <span class="n">dist</span><span class="p">:</span>
|
||||
<span class="n">dist</span> <span class="o">=</span> <span class="n">tmp</span>
|
||||
<span class="c1"># associa a a centroide de menor distância à instância</span>
|
||||
<span class="n">grupos</span><span class="p">[</span><span class="n">inst_count</span><span class="p">]</span> <span class="o">=</span> <span class="n">grupo_count</span>
|
||||
<span class="n">grupo_count</span> <span class="o">=</span> <span class="n">grupo_count</span> <span class="o">+</span> <span class="mi">1</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">grupotmp</span> <span class="o">!=</span> <span class="n">grupos</span><span class="p">[</span><span class="n">inst_count</span><span class="p">]:</span>
|
||||
<span class="n">modificacao</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
|
||||
<span class="n">inst_count</span> <span class="o">=</span> <span class="n">inst_count</span> <span class="o">+</span> <span class="mi">1</span>
|
||||
|
||||
<span class="k">if</span> <span class="ow">not</span> <span class="n">modificacao</span><span class="p">:</span>
|
||||
<span class="n">it_semmodificacao</span> <span class="o">=</span> <span class="n">it_semmodificacao</span> <span class="o">+</span> <span class="mi">1</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">it_semmodificacao</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
|
||||
<span class="c1"># atualiza cada centroide com base nos valores médios de todas as instâncias à ela associadas</span>
|
||||
<span class="n">grupo_count</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">grupo</span> <span class="ow">in</span> <span class="n">centroides</span><span class="p">:</span>
|
||||
<span class="n">total_inst</span> <span class="o">=</span> <span class="n">functools</span><span class="o">.</span><span class="n">reduce</span><span class="p">(</span><span class="n">operator</span><span class="o">.</span><span class="n">add</span><span class="p">,</span> <span class="p">[</span><span class="mi">1</span> <span class="k">for</span> <span class="n">xx</span> <span class="ow">in</span> <span class="n">grupos</span> <span class="k">if</span> <span class="n">xx</span> <span class="o">==</span> <span class="n">grupo_count</span><span class="p">],</span> <span class="mi">0</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">total_inst</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">tam</span> <span class="o">></span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">count</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">tam</span><span class="p">):</span>
|
||||
<span class="n">soma</span> <span class="o">=</span> <span class="n">functools</span><span class="o">.</span><span class="n">reduce</span><span class="p">(</span><span class="n">operator</span><span class="o">.</span><span class="n">add</span><span class="p">,</span>
|
||||
<span class="p">[</span><span class="n">dados</span><span class="p">[</span><span class="n">kk</span><span class="p">][</span><span class="n">count</span><span class="p">]</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">dados</span><span class="p">))</span> <span class="k">if</span>
|
||||
<span class="n">grupos</span><span class="p">[</span><span class="n">kk</span><span class="p">]</span> <span class="o">==</span> <span class="n">grupo_count</span><span class="p">])</span>
|
||||
<span class="n">centroides</span><span class="p">[</span><span class="n">grupo_count</span><span class="p">][</span><span class="n">count</span><span class="p">]</span> <span class="o">=</span> <span class="n">soma</span> <span class="o">/</span> <span class="n">total_inst</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">soma</span> <span class="o">=</span> <span class="n">functools</span><span class="o">.</span><span class="n">reduce</span><span class="p">(</span><span class="n">operator</span><span class="o">.</span><span class="n">add</span><span class="p">,</span>
|
||||
<span class="p">[</span><span class="n">dados</span><span class="p">[</span><span class="n">kk</span><span class="p">]</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">dados</span><span class="p">))</span> <span class="k">if</span> <span class="n">grupos</span><span class="p">[</span><span class="n">kk</span><span class="p">]</span> <span class="o">==</span> <span class="n">grupo_count</span><span class="p">])</span>
|
||||
<span class="n">centroides</span><span class="p">[</span><span class="n">grupo_count</span><span class="p">]</span> <span class="o">=</span> <span class="n">soma</span> <span class="o">/</span> <span class="n">total_inst</span>
|
||||
<span class="n">grupo_count</span> <span class="o">=</span> <span class="n">grupo_count</span> <span class="o">+</span> <span class="mi">1</span>
|
||||
|
||||
<span class="n">iteracoes</span> <span class="o">=</span> <span class="n">iteracoes</span> <span class="o">+</span> <span class="mi">1</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">centroides</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="CMeansPartitioner"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.CMeans.CMeansPartitioner">[docs]</a><span class="k">class</span> <span class="nc">CMeansPartitioner</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="n">Partitioner</span><span class="p">):</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">CMeansPartitioner</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"CMeans"</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="CMeansPartitioner.build"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.CMeans.CMeansPartitioner.build">[docs]</a> <span class="k">def</span> <span class="nf">build</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="n">sets</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="n">centroides</span> <span class="o">=</span> <span class="n">c_means</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">partitions</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
|
||||
<span class="n">centroides</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max</span><span class="p">)</span>
|
||||
<span class="n">centroides</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">min</span><span class="p">)</span>
|
||||
<span class="n">centroides</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">centroides</span><span class="p">))</span>
|
||||
<span class="n">centroides</span><span class="o">.</span><span class="n">sort</span><span class="p">()</span>
|
||||
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">centroides</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">):</span>
|
||||
<span class="n">_name</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_name</span><span class="p">(</span><span class="n">c</span><span class="p">)</span>
|
||||
<span class="n">sets</span><span class="p">[</span><span class="n">_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">(</span><span class="n">_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">,</span>
|
||||
<span class="p">[</span><span class="nb">round</span><span class="p">(</span><span class="n">centroides</span><span class="p">[</span><span class="n">c</span> <span class="o">-</span> <span class="mi">1</span><span class="p">],</span> <span class="mi">3</span><span class="p">),</span> <span class="nb">round</span><span class="p">(</span><span class="n">centroides</span><span class="p">[</span><span class="n">c</span><span class="p">],</span> <span class="mi">3</span><span class="p">),</span> <span class="nb">round</span><span class="p">(</span><span class="n">centroides</span><span class="p">[</span><span class="n">c</span> <span class="o">+</span> <span class="mi">1</span><span class="p">],</span> <span class="mi">3</span><span class="p">)],</span>
|
||||
<span class="nb">round</span><span class="p">(</span><span class="n">centroides</span><span class="p">[</span><span class="n">c</span><span class="p">],</span> <span class="mi">3</span><span class="p">))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">sets</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
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<h1>Source code for pyFTS.partitioners.Entropy</h1><div class="highlight"><pre>
|
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<span></span><span class="sd">"""</span>
|
||||
<span class="sd">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,”</span>
|
||||
<span class="sd">Technol. Forecast. Social Change, vol. 73, no. 5, pp. 524–542, Jun. 2006.</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">math</span>
|
||||
<span class="kn">import</span> <span class="nn">random</span> <span class="k">as</span> <span class="nn">rnd</span>
|
||||
<span class="kn">import</span> <span class="nn">functools</span><span class="o">,</span> <span class="nn">operator</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">Membership</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">partitioner</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="splitBelow"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.Entropy.splitBelow">[docs]</a><span class="k">def</span> <span class="nf">splitBelow</span><span class="p">(</span><span class="n">data</span><span class="p">,</span><span class="n">threshold</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="n">k</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">data</span> <span class="k">if</span> <span class="n">k</span> <span class="o"><=</span> <span class="n">threshold</span><span class="p">]</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="splitAbove"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.Entropy.splitAbove">[docs]</a><span class="k">def</span> <span class="nf">splitAbove</span><span class="p">(</span><span class="n">data</span><span class="p">,</span><span class="n">threshold</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="n">k</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">data</span> <span class="k">if</span> <span class="n">k</span> <span class="o">></span> <span class="n">threshold</span><span class="p">]</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="PMF"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.Entropy.PMF">[docs]</a><span class="k">def</span> <span class="nf">PMF</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">threshold</span><span class="p">):</span>
|
||||
<span class="n">a</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">([</span><span class="mf">1.0</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">splitBelow</span><span class="p">(</span><span class="n">data</span><span class="p">,</span><span class="n">threshold</span><span class="p">)])</span>
|
||||
<span class="n">b</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">([</span><span class="mf">1.0</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">splitAbove</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">threshold</span><span class="p">)])</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="n">a</span> <span class="o">/</span> <span class="n">l</span><span class="p">,</span> <span class="n">b</span> <span class="o">/</span> <span class="n">l</span><span class="p">]</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="entropy"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.Entropy.entropy">[docs]</a><span class="k">def</span> <span class="nf">entropy</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">threshold</span><span class="p">):</span>
|
||||
<span class="n">pmf</span> <span class="o">=</span> <span class="n">PMF</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">threshold</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">pmf</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span> <span class="ow">or</span> <span class="n">pmf</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="mi">1</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="o">-</span> <span class="nb">sum</span><span class="p">([</span><span class="n">pmf</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">*</span> <span class="n">math</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">pmf</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="n">pmf</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">*</span> <span class="n">math</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">pmf</span><span class="p">[</span><span class="mi">1</span><span class="p">])])</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="informationGain"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.Entropy.informationGain">[docs]</a><span class="k">def</span> <span class="nf">informationGain</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">thres1</span><span class="p">,</span> <span class="n">thres2</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">entropy</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">thres1</span><span class="p">)</span> <span class="o">-</span> <span class="n">entropy</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">thres2</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="bestSplit"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.Entropy.bestSplit">[docs]</a><span class="k">def</span> <span class="nf">bestSplit</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">npart</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span> <span class="o"><</span> <span class="mi">2</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="kc">None</span>
|
||||
<span class="n">count</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">data</span><span class="p">))</span>
|
||||
<span class="n">ndata</span><span class="o">.</span><span class="n">sort</span><span class="p">()</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
<span class="n">threshold</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">try</span><span class="p">:</span>
|
||||
<span class="k">while</span> <span class="n">count</span> <span class="o"><</span> <span class="n">l</span> <span class="ow">and</span> <span class="n">informationGain</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">ndata</span><span class="p">[</span><span class="n">count</span> <span class="o">-</span> <span class="mi">1</span><span class="p">],</span> <span class="n">ndata</span><span class="p">[</span><span class="n">count</span><span class="p">])</span> <span class="o"><=</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">threshold</span> <span class="o">=</span> <span class="n">ndata</span><span class="p">[</span><span class="n">count</span><span class="p">]</span>
|
||||
<span class="n">count</span> <span class="o">+=</span> <span class="mi">1</span>
|
||||
<span class="k">except</span> <span class="ne">IndexError</span><span class="p">:</span>
|
||||
<span class="nb">print</span><span class="p">(</span><span class="n">threshold</span><span class="p">)</span>
|
||||
<span class="nb">print</span> <span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
<span class="nb">print</span> <span class="p">(</span><span class="n">count</span><span class="p">)</span>
|
||||
|
||||
<span class="n">rem</span> <span class="o">=</span> <span class="n">npart</span> <span class="o">%</span> <span class="mi">2</span>
|
||||
|
||||
<span class="k">if</span> <span class="p">(</span><span class="n">npart</span> <span class="o">-</span> <span class="n">rem</span><span class="p">)</span><span class="o">/</span><span class="mi">2</span> <span class="o">></span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">p1</span> <span class="o">=</span> <span class="n">splitBelow</span><span class="p">(</span><span class="n">data</span><span class="p">,</span><span class="n">threshold</span><span class="p">)</span>
|
||||
<span class="n">p2</span> <span class="o">=</span> <span class="n">splitAbove</span><span class="p">(</span><span class="n">data</span><span class="p">,</span><span class="n">threshold</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">p1</span><span class="p">)</span> <span class="o">></span> <span class="nb">len</span><span class="p">(</span><span class="n">p2</span><span class="p">):</span>
|
||||
<span class="n">np1</span> <span class="o">=</span> <span class="p">(</span><span class="n">npart</span> <span class="o">-</span> <span class="n">rem</span><span class="p">)</span><span class="o">/</span><span class="mi">2</span> <span class="o">+</span> <span class="n">rem</span>
|
||||
<span class="n">np2</span> <span class="o">=</span> <span class="p">(</span><span class="n">npart</span> <span class="o">-</span> <span class="n">rem</span><span class="p">)</span><span class="o">/</span><span class="mi">2</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">np1</span> <span class="o">=</span> <span class="p">(</span><span class="n">npart</span> <span class="o">-</span> <span class="n">rem</span><span class="p">)</span> <span class="o">/</span> <span class="mi">2</span>
|
||||
<span class="n">np2</span> <span class="o">=</span> <span class="p">(</span><span class="n">npart</span> <span class="o">-</span> <span class="n">rem</span><span class="p">)</span> <span class="o">/</span> <span class="mi">2</span> <span class="o">+</span> <span class="n">rem</span>
|
||||
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">[</span><span class="n">threshold</span><span class="p">]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">bestSplit</span><span class="p">(</span><span class="n">p1</span><span class="p">,</span> <span class="n">np1</span> <span class="p">):</span> <span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">bestSplit</span><span class="p">(</span><span class="n">p2</span><span class="p">,</span> <span class="n">np2</span> <span class="p">):</span> <span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">tmp</span>
|
||||
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="p">[</span><span class="n">threshold</span><span class="p">]</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="EntropyPartitioner"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.Entropy.EntropyPartitioner">[docs]</a><span class="k">class</span> <span class="nc">EntropyPartitioner</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="n">Partitioner</span><span class="p">):</span>
|
||||
<span class="sd">"""Huarng Entropy Partitioner"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">EntropyPartitioner</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Entropy"</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="EntropyPartitioner.build"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.Entropy.EntropyPartitioner.build">[docs]</a> <span class="k">def</span> <span class="nf">build</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="n">sets</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<span class="n">partitions</span> <span class="o">=</span> <span class="n">bestSplit</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitions</span><span class="p">)</span>
|
||||
<span class="n">partitions</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">min</span><span class="p">)</span>
|
||||
<span class="n">partitions</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max</span><span class="p">)</span>
|
||||
<span class="n">partitions</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">partitions</span><span class="p">))</span>
|
||||
<span class="n">partitions</span><span class="o">.</span><span class="n">sort</span><span class="p">()</span>
|
||||
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">partitions</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">):</span>
|
||||
<span class="n">_name</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_name</span><span class="p">(</span><span class="n">c</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">membership_function</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">:</span>
|
||||
<span class="n">sets</span><span class="p">[</span><span class="n">_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">(</span><span class="n">_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">,</span>
|
||||
<span class="p">[</span><span class="n">partitions</span><span class="p">[</span><span class="n">c</span> <span class="o">-</span> <span class="mi">1</span><span class="p">],</span> <span class="n">partitions</span><span class="p">[</span><span class="n">c</span><span class="p">],</span> <span class="n">partitions</span><span class="p">[</span><span class="n">c</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]],</span><span class="n">partitions</span><span class="p">[</span><span class="n">c</span><span class="p">])</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">membership_function</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span><span class="p">:</span>
|
||||
<span class="n">b1</span> <span class="o">=</span> <span class="p">(</span><span class="n">partitions</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="o">-</span> <span class="n">partitions</span><span class="p">[</span><span class="n">c</span> <span class="o">-</span> <span class="mi">1</span><span class="p">])</span><span class="o">/</span><span class="mi">2</span>
|
||||
<span class="n">b2</span> <span class="o">=</span> <span class="p">(</span><span class="n">partitions</span><span class="p">[</span><span class="n">c</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">partitions</span><span class="p">[</span><span class="n">c</span><span class="p">])</span> <span class="o">/</span> <span class="mi">2</span>
|
||||
<span class="n">sets</span><span class="p">[</span><span class="n">_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">(</span><span class="n">_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span><span class="p">,</span>
|
||||
<span class="p">[</span><span class="n">partitions</span><span class="p">[</span><span class="n">c</span> <span class="o">-</span> <span class="mi">1</span><span class="p">],</span> <span class="n">partitions</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="o">-</span> <span class="n">b1</span><span class="p">,</span>
|
||||
<span class="n">partitions</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="o">+</span> <span class="n">b2</span><span class="p">,</span> <span class="n">partitions</span><span class="p">[</span><span class="n">c</span> <span class="o">+</span> <span class="mi">1</span><span class="p">]],</span>
|
||||
<span class="n">partitions</span><span class="p">[</span><span class="n">c</span><span class="p">])</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">sets</span></div></div>
|
||||
</pre></div>
|
||||
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<h1>Source code for pyFTS.partitioners.FCM</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">S. T. Li, Y. C. Cheng, and S. Y. Lin, “A FCM-based deterministic forecasting model for fuzzy time series,”</span>
|
||||
<span class="sd">Comput. Math. Appl., vol. 56, no. 12, pp. 3052–3063, Dec. 2008. DOI: 10.1016/j.camwa.2008.07.033.</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">math</span>
|
||||
<span class="kn">import</span> <span class="nn">random</span> <span class="k">as</span> <span class="nn">rnd</span>
|
||||
<span class="kn">import</span> <span class="nn">functools</span><span class="o">,</span> <span class="nn">operator</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">Membership</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">partitioner</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="fuzzy_distance"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.FCM.fuzzy_distance">[docs]</a><span class="k">def</span> <span class="nf">fuzzy_distance</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">functools</span><span class="o">.</span><span class="n">reduce</span><span class="p">(</span><span class="n">operator</span><span class="o">.</span><span class="n">add</span><span class="p">,</span> <span class="p">[(</span><span class="n">x</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">-</span> <span class="n">y</span><span class="p">[</span><span class="n">k</span><span class="p">])</span> <span class="o">**</span> <span class="mi">2</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">x</span><span class="p">))])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">(</span><span class="n">x</span> <span class="o">-</span> <span class="n">y</span><span class="p">)</span> <span class="o">**</span> <span class="mi">2</span>
|
||||
<span class="k">return</span> <span class="n">math</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="membership"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.FCM.membership">[docs]</a><span class="k">def</span> <span class="nf">membership</span><span class="p">(</span><span class="n">val</span><span class="p">,</span> <span class="n">vals</span><span class="p">):</span>
|
||||
<span class="n">soma</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">vals</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">k</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">k</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="n">soma</span> <span class="o">=</span> <span class="n">soma</span> <span class="o">+</span> <span class="p">(</span><span class="n">val</span> <span class="o">/</span> <span class="n">k</span><span class="p">)</span> <span class="o">**</span> <span class="mi">2</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">soma</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="fuzzy_cmeans"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.FCM.fuzzy_cmeans">[docs]</a><span class="k">def</span> <span class="nf">fuzzy_cmeans</span><span class="p">(</span><span class="n">k</span><span class="p">,</span> <span class="n">dados</span><span class="p">,</span> <span class="n">tam</span><span class="p">,</span> <span class="n">m</span><span class="p">,</span> <span class="n">deltadist</span><span class="o">=</span><span class="mf">0.001</span><span class="p">):</span>
|
||||
<span class="n">tam_dados</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">dados</span><span class="p">)</span>
|
||||
|
||||
<span class="c1"># Inicializa as centróides escolhendo elementos aleatórios dos conjuntos</span>
|
||||
<span class="n">centroides</span> <span class="o">=</span> <span class="p">[</span><span class="n">dados</span><span class="p">[</span><span class="n">rnd</span><span class="o">.</span><span class="n">randint</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">tam_dados</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)]</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">k</span><span class="p">)]</span>
|
||||
|
||||
<span class="c1"># Tabela de pertinência das instâncias aos grupos</span>
|
||||
<span class="n">grupos</span> <span class="o">=</span> <span class="p">[[</span><span class="mi">0</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">k</span><span class="p">)]</span> <span class="k">for</span> <span class="n">xx</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">tam_dados</span><span class="p">)]</span>
|
||||
|
||||
<span class="n">alteracaomedia</span> <span class="o">=</span> <span class="mi">1000</span>
|
||||
|
||||
<span class="n">m_exp</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">/</span> <span class="p">(</span><span class="n">m</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span>
|
||||
|
||||
<span class="c1"># para cada instância</span>
|
||||
<span class="n">iteracoes</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
|
||||
<span class="k">while</span> <span class="n">iteracoes</span> <span class="o"><</span> <span class="mi">1000</span> <span class="ow">and</span> <span class="n">alteracaomedia</span> <span class="o">></span> <span class="n">deltadist</span><span class="p">:</span>
|
||||
|
||||
<span class="n">alteracaomedia</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
|
||||
<span class="c1"># verifica a distância para cada centroide</span>
|
||||
<span class="c1"># Atualiza a pertinencia daquela instância para cada um dos grupos</span>
|
||||
|
||||
<span class="n">inst_count</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">instancia</span> <span class="ow">in</span> <span class="n">dados</span><span class="p">:</span>
|
||||
|
||||
<span class="n">dist_grupos</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span> <span class="k">for</span> <span class="n">xx</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">k</span><span class="p">)]</span>
|
||||
|
||||
<span class="n">grupo_count</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">grupo</span> <span class="ow">in</span> <span class="n">centroides</span><span class="p">:</span>
|
||||
<span class="n">dist_grupos</span><span class="p">[</span><span class="n">grupo_count</span><span class="p">]</span> <span class="o">=</span> <span class="n">fuzzy_distance</span><span class="p">(</span><span class="n">grupo</span><span class="p">,</span> <span class="n">instancia</span><span class="p">)</span>
|
||||
<span class="n">grupo_count</span> <span class="o">=</span> <span class="n">grupo_count</span> <span class="o">+</span> <span class="mi">1</span>
|
||||
|
||||
<span class="n">dist_grupos_total</span> <span class="o">=</span> <span class="n">functools</span><span class="o">.</span><span class="n">reduce</span><span class="p">(</span><span class="n">operator</span><span class="o">.</span><span class="n">add</span><span class="p">,</span> <span class="p">[</span><span class="n">xk</span> <span class="k">for</span> <span class="n">xk</span> <span class="ow">in</span> <span class="n">dist_grupos</span><span class="p">])</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">grp</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">k</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">dist_grupos</span><span class="p">[</span><span class="n">grp</span><span class="p">]</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">grupos</span><span class="p">[</span><span class="n">inst_count</span><span class="p">][</span><span class="n">grp</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">grupos</span><span class="p">[</span><span class="n">inst_count</span><span class="p">][</span><span class="n">grp</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span> <span class="o">/</span> <span class="n">membership</span><span class="p">(</span><span class="n">dist_grupos</span><span class="p">[</span><span class="n">grp</span><span class="p">],</span> <span class="n">dist_grupos</span><span class="p">)</span>
|
||||
<span class="c1"># grupos[inst_count][grp] = 1/(dist_grupos[grp] / dist_grupos_total)</span>
|
||||
<span class="c1"># grupos[inst_count][grp] = (1/(dist_grupos[grp]**2))**m_exp / (1/(dist_grupos_total**2))**m_exp</span>
|
||||
|
||||
<span class="n">inst_count</span> <span class="o">=</span> <span class="n">inst_count</span> <span class="o">+</span> <span class="mi">1</span>
|
||||
|
||||
<span class="c1"># return centroides</span>
|
||||
|
||||
<span class="c1"># atualiza cada centroide com base na Média de todos os padrões ponderados pelo grau de pertinência</span>
|
||||
|
||||
<span class="n">grupo_count</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">grupo</span> <span class="ow">in</span> <span class="n">centroides</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">tam</span> <span class="o">></span> <span class="mi">1</span><span class="p">:</span>
|
||||
<span class="n">oldgrp</span> <span class="o">=</span> <span class="p">[</span><span class="n">xx</span> <span class="k">for</span> <span class="n">xx</span> <span class="ow">in</span> <span class="n">grupo</span><span class="p">]</span>
|
||||
<span class="k">for</span> <span class="n">atr</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">tam</span><span class="p">):</span>
|
||||
<span class="n">soma</span> <span class="o">=</span> <span class="n">functools</span><span class="o">.</span><span class="n">reduce</span><span class="p">(</span><span class="n">operator</span><span class="o">.</span><span class="n">add</span><span class="p">,</span>
|
||||
<span class="p">[</span><span class="n">grupos</span><span class="p">[</span><span class="n">xk</span><span class="p">][</span><span class="n">grupo_count</span><span class="p">]</span> <span class="o">*</span> <span class="n">dados</span><span class="p">[</span><span class="n">xk</span><span class="p">][</span><span class="n">atr</span><span class="p">]</span> <span class="k">for</span> <span class="n">xk</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">tam_dados</span><span class="p">)])</span>
|
||||
<span class="n">norm</span> <span class="o">=</span> <span class="n">functools</span><span class="o">.</span><span class="n">reduce</span><span class="p">(</span><span class="n">operator</span><span class="o">.</span><span class="n">add</span><span class="p">,</span> <span class="p">[</span><span class="n">grupos</span><span class="p">[</span><span class="n">xk</span><span class="p">][</span><span class="n">grupo_count</span><span class="p">]</span> <span class="k">for</span> <span class="n">xk</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">tam_dados</span><span class="p">)])</span>
|
||||
<span class="n">centroides</span><span class="p">[</span><span class="n">grupo_count</span><span class="p">][</span><span class="n">atr</span><span class="p">]</span> <span class="o">=</span> <span class="n">soma</span> <span class="o">/</span> <span class="n">norm</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">oldgrp</span> <span class="o">=</span> <span class="n">grupo</span>
|
||||
<span class="n">soma</span> <span class="o">=</span> <span class="n">functools</span><span class="o">.</span><span class="n">reduce</span><span class="p">(</span><span class="n">operator</span><span class="o">.</span><span class="n">add</span><span class="p">,</span>
|
||||
<span class="p">[</span><span class="n">grupos</span><span class="p">[</span><span class="n">xk</span><span class="p">][</span><span class="n">grupo_count</span><span class="p">]</span> <span class="o">*</span> <span class="n">dados</span><span class="p">[</span><span class="n">xk</span><span class="p">]</span> <span class="k">for</span> <span class="n">xk</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">tam_dados</span><span class="p">)])</span>
|
||||
<span class="n">norm</span> <span class="o">=</span> <span class="n">functools</span><span class="o">.</span><span class="n">reduce</span><span class="p">(</span><span class="n">operator</span><span class="o">.</span><span class="n">add</span><span class="p">,</span> <span class="p">[</span><span class="n">grupos</span><span class="p">[</span><span class="n">xk</span><span class="p">][</span><span class="n">grupo_count</span><span class="p">]</span> <span class="k">for</span> <span class="n">xk</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">tam_dados</span><span class="p">)])</span>
|
||||
<span class="n">centroides</span><span class="p">[</span><span class="n">grupo_count</span><span class="p">]</span> <span class="o">=</span> <span class="n">soma</span> <span class="o">/</span> <span class="n">norm</span>
|
||||
|
||||
<span class="n">alteracaomedia</span> <span class="o">=</span> <span class="n">alteracaomedia</span> <span class="o">+</span> <span class="n">fuzzy_distance</span><span class="p">(</span><span class="n">oldgrp</span><span class="p">,</span> <span class="n">grupo</span><span class="p">)</span>
|
||||
<span class="n">grupo_count</span> <span class="o">=</span> <span class="n">grupo_count</span> <span class="o">+</span> <span class="mi">1</span>
|
||||
|
||||
<span class="n">alteracaomedia</span> <span class="o">=</span> <span class="n">alteracaomedia</span> <span class="o">/</span> <span class="n">k</span>
|
||||
<span class="n">iteracoes</span> <span class="o">=</span> <span class="n">iteracoes</span> <span class="o">+</span> <span class="mi">1</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">centroides</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="FCMPartitioner"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.FCM.FCMPartitioner">[docs]</a><span class="k">class</span> <span class="nc">FCMPartitioner</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="n">Partitioner</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> </span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">FCMPartitioner</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"FCM"</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="FCMPartitioner.build"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.FCM.FCMPartitioner.build">[docs]</a> <span class="k">def</span> <span class="nf">build</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="n">sets</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<span class="n">centroids</span> <span class="o">=</span> <span class="n">fuzzy_cmeans</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">partitions</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>
|
||||
<span class="n">centroids</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max</span><span class="p">)</span>
|
||||
<span class="n">centroids</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">min</span><span class="p">)</span>
|
||||
<span class="n">centroids</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">centroids</span><span class="p">))</span>
|
||||
<span class="n">centroids</span><span class="o">.</span><span class="n">sort</span><span class="p">()</span>
|
||||
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">centroids</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">):</span>
|
||||
<span class="n">_name</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_name</span><span class="p">(</span><span class="n">c</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">membership_function</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">:</span>
|
||||
<span class="n">sets</span><span class="p">[</span><span class="n">_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">(</span><span class="n">_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">,</span>
|
||||
<span class="p">[</span><span class="nb">round</span><span class="p">(</span><span class="n">centroids</span><span class="p">[</span><span class="n">c</span> <span class="o">-</span> <span class="mi">1</span><span class="p">],</span> <span class="mi">3</span><span class="p">),</span> <span class="nb">round</span><span class="p">(</span><span class="n">centroids</span><span class="p">[</span><span class="n">c</span><span class="p">],</span> <span class="mi">3</span><span class="p">),</span>
|
||||
<span class="nb">round</span><span class="p">(</span><span class="n">centroids</span><span class="p">[</span><span class="n">c</span> <span class="o">+</span> <span class="mi">1</span><span class="p">],</span> <span class="mi">3</span><span class="p">)],</span>
|
||||
<span class="nb">round</span><span class="p">(</span><span class="n">centroids</span><span class="p">[</span><span class="n">c</span><span class="p">],</span> <span class="mi">3</span><span class="p">))</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">membership_function</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span><span class="p">:</span>
|
||||
<span class="n">q1</span> <span class="o">=</span> <span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">centroids</span><span class="p">[</span><span class="n">c</span><span class="p">],</span> <span class="mi">3</span><span class="p">)</span> <span class="o">-</span> <span class="nb">round</span><span class="p">(</span><span class="n">centroids</span><span class="p">[</span><span class="n">c</span> <span class="o">-</span> <span class="mi">1</span><span class="p">],</span> <span class="mi">3</span><span class="p">))</span> <span class="o">/</span> <span class="mi">2</span>
|
||||
<span class="n">q2</span> <span class="o">=</span> <span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">centroids</span><span class="p">[</span><span class="n">c</span> <span class="o">+</span> <span class="mi">1</span><span class="p">],</span> <span class="mi">3</span><span class="p">)</span> <span class="o">-</span> <span class="nb">round</span><span class="p">(</span><span class="n">centroids</span><span class="p">[</span><span class="n">c</span><span class="p">],</span> <span class="mi">3</span><span class="p">))</span> <span class="o">/</span> <span class="mi">2</span>
|
||||
<span class="n">sets</span><span class="p">[</span><span class="n">_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">(</span><span class="n">_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">,</span>
|
||||
<span class="p">[</span><span class="nb">round</span><span class="p">(</span><span class="n">centroids</span><span class="p">[</span><span class="n">c</span> <span class="o">-</span> <span class="mi">1</span><span class="p">],</span> <span class="mi">3</span><span class="p">),</span> <span class="nb">round</span><span class="p">(</span><span class="n">centroids</span><span class="p">[</span><span class="n">c</span><span class="p">],</span> <span class="mi">3</span><span class="p">)</span> <span class="o">-</span> <span class="n">q1</span><span class="p">,</span>
|
||||
<span class="nb">round</span><span class="p">(</span><span class="n">centroids</span><span class="p">[</span><span class="n">c</span><span class="p">],</span> <span class="mi">3</span><span class="p">)</span> <span class="o">+</span> <span class="n">q2</span><span class="p">,</span> <span class="nb">round</span><span class="p">(</span><span class="n">centroids</span><span class="p">[</span><span class="n">c</span> <span class="o">+</span> <span class="mi">1</span><span class="p">],</span> <span class="mi">3</span><span class="p">)],</span>
|
||||
<span class="nb">round</span><span class="p">(</span><span class="n">centroids</span><span class="p">[</span><span class="n">c</span><span class="p">],</span> <span class="mi">3</span><span class="p">))</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">sets</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
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|
||||
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|
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|
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|
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|
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|
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120
docs/_build/html/_modules/pyFTS/partitioners/Grid.html
vendored
Normal file
120
docs/_build/html/_modules/pyFTS/partitioners/Grid.html
vendored
Normal file
@ -0,0 +1,120 @@
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<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
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<h1>Source code for pyFTS.partitioners.Grid</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""Even Length Grid Partitioner"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">math</span>
|
||||
<span class="kn">import</span> <span class="nn">random</span> <span class="k">as</span> <span class="nn">rnd</span>
|
||||
<span class="kn">import</span> <span class="nn">functools</span><span class="o">,</span> <span class="nn">operator</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">Membership</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">partitioner</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="GridPartitioner"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.Grid.GridPartitioner">[docs]</a><span class="k">class</span> <span class="nc">GridPartitioner</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="n">Partitioner</span><span class="p">):</span>
|
||||
<span class="sd">"""Even Length Grid Partitioner"""</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Even Length Grid Partitioner</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">GridPartitioner</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Grid"</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="GridPartitioner.build"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.Grid.GridPartitioner.build">[docs]</a> <span class="k">def</span> <span class="nf">build</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="n">sets</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<span class="n">kwargs</span> <span class="o">=</span> <span class="p">{</span><span class="s1">'type'</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">type</span><span class="p">,</span> <span class="s1">'variable'</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">variable</span><span class="p">}</span>
|
||||
|
||||
<span class="n">dlen</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">max</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">min</span>
|
||||
<span class="n">partlen</span> <span class="o">=</span> <span class="n">dlen</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitions</span>
|
||||
|
||||
<span class="n">count</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">min</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">max</span><span class="p">,</span> <span class="n">partlen</span><span class="p">):</span>
|
||||
<span class="n">_name</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_name</span><span class="p">(</span><span class="n">count</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">membership_function</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">:</span>
|
||||
<span class="n">sets</span><span class="p">[</span><span class="n">_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">(</span><span class="n">_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">,</span> <span class="p">[</span><span class="n">c</span> <span class="o">-</span> <span class="n">partlen</span><span class="p">,</span> <span class="n">c</span><span class="p">,</span> <span class="n">c</span> <span class="o">+</span> <span class="n">partlen</span><span class="p">],</span><span class="n">c</span><span class="p">,</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">membership_function</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">gaussmf</span><span class="p">:</span>
|
||||
<span class="n">sets</span><span class="p">[</span><span class="n">_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">(</span><span class="n">_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">gaussmf</span><span class="p">,</span> <span class="p">[</span><span class="n">c</span><span class="p">,</span> <span class="n">partlen</span> <span class="o">/</span> <span class="mi">3</span><span class="p">],</span> <span class="n">c</span><span class="p">,</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">membership_function</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span><span class="p">:</span>
|
||||
<span class="n">q</span> <span class="o">=</span> <span class="n">partlen</span> <span class="o">/</span> <span class="mi">2</span>
|
||||
<span class="n">sets</span><span class="p">[</span><span class="n">_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">(</span><span class="n">_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span><span class="p">,</span> <span class="p">[</span><span class="n">c</span> <span class="o">-</span> <span class="n">partlen</span><span class="p">,</span> <span class="n">c</span> <span class="o">-</span> <span class="n">q</span><span class="p">,</span> <span class="n">c</span> <span class="o">+</span> <span class="n">q</span><span class="p">,</span> <span class="n">c</span> <span class="o">+</span> <span class="n">partlen</span><span class="p">],</span> <span class="n">c</span><span class="p">,</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
<span class="n">count</span> <span class="o">+=</span> <span class="mi">1</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">min</span> <span class="o">-</span> <span class="n">partlen</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">sets</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
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|
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131
docs/_build/html/_modules/pyFTS/partitioners/Huarng.html
vendored
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131
docs/_build/html/_modules/pyFTS/partitioners/Huarng.html
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<h1>Source code for pyFTS.partitioners.Huarng</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">K. H. Huarng, “Effective lengths of intervals to improve forecasting in fuzzy time series,”</span>
|
||||
<span class="sd">Fuzzy Sets Syst., vol. 123, no. 3, pp. 387–394, Nov. 2001.</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">math</span>
|
||||
<span class="kn">import</span> <span class="nn">random</span> <span class="k">as</span> <span class="nn">rnd</span>
|
||||
<span class="kn">import</span> <span class="nn">functools</span><span class="o">,</span> <span class="nn">operator</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">Transformations</span>
|
||||
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">partitioner</span>
|
||||
|
||||
<div class="viewcode-block" id="HuarngPartitioner"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.Huarng.HuarngPartitioner">[docs]</a><span class="k">class</span> <span class="nc">HuarngPartitioner</span><span class="p">(</span><span class="n">partitioner</span><span class="o">.</span><span class="n">Partitioner</span><span class="p">):</span>
|
||||
<span class="sd">"""Huarng Empirical Partitioner"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="nb">super</span><span class="p">(</span><span class="n">HuarngPartitioner</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="o">=</span><span class="s2">"Huarng"</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="HuarngPartitioner.build"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.Huarng.HuarngPartitioner.build">[docs]</a> <span class="k">def</span> <span class="nf">build</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="n">diff</span> <span class="o">=</span> <span class="n">Transformations</span><span class="o">.</span><span class="n">Differential</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
|
||||
<span class="n">data2</span> <span class="o">=</span> <span class="n">diff</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">davg</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">data2</span><span class="p">)</span> <span class="o">/</span> <span class="mi">2</span> <span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">davg</span> <span class="o"><=</span> <span class="mf">1.0</span><span class="p">:</span>
|
||||
<span class="n">base</span> <span class="o">=</span> <span class="mf">0.1</span>
|
||||
<span class="k">elif</span> <span class="mi">1</span> <span class="o"><</span> <span class="n">davg</span> <span class="o"><=</span> <span class="mi">10</span><span class="p">:</span>
|
||||
<span class="n">base</span> <span class="o">=</span> <span class="mf">1.0</span>
|
||||
<span class="k">elif</span> <span class="mi">10</span> <span class="o"><</span> <span class="n">davg</span> <span class="o"><=</span> <span class="mi">100</span><span class="p">:</span>
|
||||
<span class="n">base</span> <span class="o">=</span> <span class="mi">10</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">base</span> <span class="o">=</span> <span class="mi">100</span>
|
||||
|
||||
<span class="n">sets</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<span class="n">dlen</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">max</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">min</span>
|
||||
<span class="n">npart</span> <span class="o">=</span> <span class="n">math</span><span class="o">.</span><span class="n">ceil</span><span class="p">(</span><span class="n">dlen</span> <span class="o">/</span> <span class="n">base</span><span class="p">)</span>
|
||||
<span class="n">partition</span> <span class="o">=</span> <span class="n">math</span><span class="o">.</span><span class="n">ceil</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">min</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">npart</span><span class="p">):</span>
|
||||
<span class="n">_name</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_name</span><span class="p">(</span><span class="n">c</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">membership_function</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">:</span>
|
||||
<span class="n">sets</span><span class="p">[</span><span class="n">_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">(</span><span class="n">_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">,</span>
|
||||
<span class="p">[</span><span class="n">partition</span> <span class="o">-</span> <span class="n">base</span><span class="p">,</span> <span class="n">partition</span><span class="p">,</span> <span class="n">partition</span> <span class="o">+</span> <span class="n">base</span><span class="p">],</span> <span class="n">partition</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">membership_function</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">gaussmf</span><span class="p">:</span>
|
||||
<span class="n">sets</span><span class="p">[</span><span class="n">_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">(</span><span class="n">_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">gaussmf</span><span class="p">,</span>
|
||||
<span class="p">[</span><span class="n">partition</span><span class="p">,</span> <span class="n">base</span><span class="o">/</span><span class="mi">2</span><span class="p">],</span> <span class="n">partition</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">membership_function</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span><span class="p">:</span>
|
||||
<span class="n">sets</span><span class="p">[</span><span class="n">_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">(</span><span class="n">_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span><span class="p">,</span>
|
||||
<span class="p">[</span><span class="n">partition</span> <span class="o">-</span> <span class="n">base</span><span class="p">,</span> <span class="n">partition</span> <span class="o">-</span> <span class="p">(</span><span class="n">base</span><span class="o">/</span><span class="mi">2</span><span class="p">),</span>
|
||||
<span class="n">partition</span> <span class="o">+</span> <span class="p">(</span><span class="n">base</span> <span class="o">/</span> <span class="mi">2</span><span class="p">),</span> <span class="n">partition</span> <span class="o">+</span> <span class="n">base</span><span class="p">],</span> <span class="n">partition</span><span class="p">)</span>
|
||||
|
||||
<span class="n">partition</span> <span class="o">+=</span> <span class="n">base</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">sets</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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167
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167
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<h1>Source code for pyFTS.partitioners.Util</h1><div class="highlight"><pre>
|
||||
<span></span><span class="sd">"""</span>
|
||||
<span class="sd">Facility methods for pyFTS partitioners module</span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
<span class="kn">import</span> <span class="nn">matplotlib</span> <span class="k">as</span> <span class="nn">plt</span>
|
||||
<span class="kn">import</span> <span class="nn">matplotlib.colors</span> <span class="k">as</span> <span class="nn">pltcolors</span>
|
||||
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
|
||||
<span class="c1">#from mpl_toolkits.mplot3d import Axes3D</span>
|
||||
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">Util</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span><span class="p">,</span><span class="n">Huarng</span><span class="p">,</span><span class="n">FCM</span><span class="p">,</span><span class="n">Entropy</span>
|
||||
|
||||
<span class="n">all_methods</span> <span class="o">=</span> <span class="p">[</span><span class="n">Grid</span><span class="o">.</span><span class="n">GridPartitioner</span><span class="p">,</span> <span class="n">Entropy</span><span class="o">.</span><span class="n">EntropyPartitioner</span><span class="p">,</span> <span class="n">FCM</span><span class="o">.</span><span class="n">FCMPartitioner</span><span class="p">,</span> <span class="n">Huarng</span><span class="o">.</span><span class="n">HuarngPartitioner</span><span class="p">]</span>
|
||||
|
||||
<span class="n">mfs</span> <span class="o">=</span> <span class="p">[</span><span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">gaussmf</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span><span class="p">]</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="plot_sets"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.Util.plot_sets">[docs]</a><span class="k">def</span> <span class="nf">plot_sets</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">sets</span><span class="p">,</span> <span class="n">titles</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">[</span><span class="mi">12</span><span class="p">,</span> <span class="mi">10</span><span class="p">],</span> <span class="n">save</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">file</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="n">num</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">sets</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">axis</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">fig</span><span class="p">,</span> <span class="n">axes</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">subplots</span><span class="p">(</span><span class="n">nrows</span><span class="o">=</span><span class="n">num</span><span class="p">,</span> <span class="n">ncols</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span><span class="n">figsize</span><span class="o">=</span><span class="n">size</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span><span class="n">num</span><span class="p">):</span>
|
||||
<span class="n">ticks</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">x</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">ax</span> <span class="o">=</span> <span class="n">axes</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="k">if</span> <span class="n">axis</span> <span class="ow">is</span> <span class="kc">None</span> <span class="k">else</span> <span class="n">axis</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="n">titles</span><span class="p">[</span><span class="n">k</span><span class="p">])</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">set_ylim</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mf">1.1</span><span class="p">])</span>
|
||||
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="n">sets</span><span class="p">[</span><span class="n">k</span><span class="p">]</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
|
||||
<span class="n">s</span> <span class="o">=</span> <span class="n">sets</span><span class="p">[</span><span class="n">k</span><span class="p">][</span><span class="n">key</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="n">s</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">:</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">parameters</span><span class="p">,[</span><span class="mi">0</span><span class="p">,</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">])</span>
|
||||
<span class="k">elif</span> <span class="n">s</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">gaussmf</span><span class="p">:</span>
|
||||
<span class="n">tmpx</span> <span class="o">=</span> <span class="p">[</span> <span class="n">kk</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">lower</span><span class="p">,</span> <span class="n">s</span><span class="o">.</span><span class="n">upper</span><span class="p">)]</span>
|
||||
<span class="n">tmpy</span> <span class="o">=</span> <span class="p">[</span><span class="n">s</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">kk</span><span class="p">)</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">lower</span><span class="p">,</span> <span class="n">s</span><span class="o">.</span><span class="n">upper</span><span class="p">)]</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">tmpx</span><span class="p">,</span> <span class="n">tmpy</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="n">s</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span><span class="p">:</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">parameters</span><span class="p">,</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">,</span> <span class="mi">0</span><span class="p">])</span>
|
||||
<span class="n">ticks</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">centroid</span><span class="p">,</span> <span class="mi">0</span><span class="p">))</span> <span class="o">+</span> <span class="s1">'</span><span class="se">\n</span><span class="s1">'</span> <span class="o">+</span> <span class="n">s</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
|
||||
<span class="n">x</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">centroid</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">xaxis</span><span class="o">.</span><span class="n">set_ticklabels</span><span class="p">(</span><span class="n">ticks</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">xaxis</span><span class="o">.</span><span class="n">set_ticks</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">axis</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">plt</span><span class="o">.</span><span class="n">tight_layout</span><span class="p">()</span>
|
||||
|
||||
<span class="n">Util</span><span class="o">.</span><span class="n">show_and_save_image</span><span class="p">(</span><span class="n">fig</span><span class="p">,</span> <span class="n">file</span><span class="p">,</span> <span class="n">save</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="plot_partitioners"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.Util.plot_partitioners">[docs]</a><span class="k">def</span> <span class="nf">plot_partitioners</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">objs</span><span class="p">,</span> <span class="n">tam</span><span class="o">=</span><span class="p">[</span><span class="mi">12</span><span class="p">,</span> <span class="mi">10</span><span class="p">],</span> <span class="n">save</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">file</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="n">sets</span> <span class="o">=</span> <span class="p">[</span><span class="n">k</span><span class="o">.</span><span class="n">sets</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">objs</span><span class="p">]</span>
|
||||
<span class="n">titles</span> <span class="o">=</span> <span class="p">[</span><span class="n">k</span><span class="o">.</span><span class="n">name</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">objs</span><span class="p">]</span>
|
||||
<span class="n">plot_sets</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">sets</span><span class="p">,</span> <span class="n">titles</span><span class="p">,</span> <span class="n">tam</span><span class="p">,</span> <span class="n">save</span><span class="p">,</span> <span class="n">file</span><span class="p">,</span> <span class="n">axis</span><span class="p">)</span></div>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="explore_partitioners"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.Util.explore_partitioners">[docs]</a><span class="k">def</span> <span class="nf">explore_partitioners</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">npart</span><span class="p">,</span> <span class="n">methods</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">mf</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">transformation</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
|
||||
<span class="n">size</span><span class="o">=</span><span class="p">[</span><span class="mi">12</span><span class="p">,</span> <span class="mi">10</span><span class="p">],</span> <span class="n">save</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">file</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Create partitioners for the mf membership functions and npart partitions and show the partitioning images.</span>
|
||||
<span class="sd"> :data: Time series data</span>
|
||||
<span class="sd"> :npart: Maximum number of partitions of the universe of discourse</span>
|
||||
<span class="sd"> :methods: A list with the partitioning methods to be used</span>
|
||||
<span class="sd"> :mf: A list with the membership functions to be used</span>
|
||||
<span class="sd"> :transformation: a transformation to be used in partitioner</span>
|
||||
<span class="sd"> :size: list, the size of the output image [width, height]</span>
|
||||
<span class="sd"> :save: boolean, if the image will be saved on disk</span>
|
||||
<span class="sd"> :file: string, the file path to save the image</span>
|
||||
<span class="sd"> :return: the list of the built partitioners</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">if</span> <span class="n">methods</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">methods</span> <span class="o">=</span> <span class="n">all_methods</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">mf</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">mf</span> <span class="o">=</span> <span class="n">mfs</span>
|
||||
|
||||
<span class="n">objs</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">methods</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">m</span> <span class="ow">in</span> <span class="n">mf</span><span class="p">:</span>
|
||||
<span class="n">obj</span> <span class="o">=</span> <span class="n">p</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">,</span> <span class="n">npart</span><span class="o">=</span><span class="n">npart</span><span class="p">,</span> <span class="n">func</span><span class="o">=</span><span class="n">m</span><span class="p">,</span> <span class="n">transformation</span><span class="o">=</span><span class="n">transformation</span><span class="p">)</span>
|
||||
<span class="n">obj</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">obj</span><span class="o">.</span><span class="n">name</span> <span class="o">+</span> <span class="s2">" - "</span> <span class="o">+</span> <span class="n">obj</span><span class="o">.</span><span class="n">membership_function</span><span class="o">.</span><span class="vm">__name__</span>
|
||||
<span class="n">objs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">obj</span><span class="p">)</span>
|
||||
|
||||
<span class="n">plot_partitioners</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">objs</span><span class="p">,</span> <span class="n">size</span><span class="p">,</span> <span class="n">save</span><span class="p">,</span> <span class="n">file</span><span class="p">)</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">objs</span></div>
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
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|
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<h1>Source code for pyFTS.partitioners.parallel_util</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">from</span> <span class="nn">copy</span> <span class="k">import</span> <span class="n">deepcopy</span>
|
||||
<span class="kn">from</span> <span class="nn">joblib</span> <span class="k">import</span> <span class="n">Parallel</span><span class="p">,</span> <span class="n">delayed</span>
|
||||
<span class="kn">import</span> <span class="nn">multiprocessing</span>
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">Util</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span><span class="p">,</span><span class="n">Huarng</span><span class="p">,</span><span class="n">FCM</span><span class="p">,</span><span class="n">Entropy</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Util</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="explore_partitioners"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.parallel_util.explore_partitioners">[docs]</a><span class="k">def</span> <span class="nf">explore_partitioners</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">npart</span><span class="p">,</span> <span class="n">methods</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">mf</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">tam</span><span class="o">=</span><span class="p">[</span><span class="mi">12</span><span class="p">,</span> <span class="mi">10</span><span class="p">],</span> <span class="n">save</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">file</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
|
||||
<span class="n">all_methods</span> <span class="o">=</span> <span class="p">[</span><span class="n">Grid</span><span class="o">.</span><span class="n">GridPartitioner</span><span class="p">,</span> <span class="n">Entropy</span><span class="o">.</span><span class="n">EntropyPartitioner</span><span class="p">,</span> <span class="n">FCM</span><span class="o">.</span><span class="n">FCMPartitioner</span><span class="p">]</span>
|
||||
<span class="n">mfs</span> <span class="o">=</span> <span class="p">[</span><span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">gaussmf</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span><span class="p">]</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">methods</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">methods</span> <span class="o">=</span> <span class="n">all_methods</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">mf</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">mf</span> <span class="o">=</span> <span class="n">mfs</span>
|
||||
|
||||
<span class="n">num_cores</span> <span class="o">=</span> <span class="n">multiprocessing</span><span class="o">.</span><span class="n">cpu_count</span><span class="p">()</span>
|
||||
|
||||
<span class="n">objs</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">method</span> <span class="ow">in</span> <span class="n">methods</span><span class="p">:</span>
|
||||
<span class="nb">print</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">method</span><span class="p">))</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="n">Parallel</span><span class="p">(</span><span class="n">n_jobs</span><span class="o">=</span><span class="n">num_cores</span><span class="p">)(</span><span class="n">delayed</span><span class="p">(</span><span class="n">method</span><span class="p">)(</span><span class="n">deepcopy</span><span class="p">(</span><span class="n">data</span><span class="p">),</span> <span class="n">npart</span><span class="p">,</span> <span class="n">m</span><span class="p">)</span> <span class="k">for</span> <span class="n">m</span> <span class="ow">in</span> <span class="n">mf</span><span class="p">)</span>
|
||||
<span class="n">objs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
|
||||
|
||||
<span class="n">objs</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">objs</span><span class="p">)</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
|
||||
|
||||
<span class="n">Util</span><span class="o">.</span><span class="n">plot_partitioners</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">objs</span><span class="p">,</span> <span class="n">tam</span><span class="p">,</span> <span class="n">save</span><span class="p">,</span> <span class="n">file</span><span class="p">)</span></div>
|
||||
|
||||
</pre></div>
|
||||
|
||||
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|
||||
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|
||||
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|
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<h1>Source code for pyFTS.partitioners.partitioner</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">Membership</span>
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">matplotlib.pylab</span> <span class="k">as</span> <span class="nn">plt</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="Partitioner"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner">[docs]</a><span class="k">class</span> <span class="nc">Partitioner</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Universe of Discourse partitioner. Split data on several fuzzy sets</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Universe of Discourse partitioner scheme. Split data on several fuzzy sets</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'name'</span><span class="p">,</span><span class="s2">""</span><span class="p">)</span>
|
||||
<span class="sd">"""partitioner name"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">partitions</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'npart'</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
|
||||
<span class="sd">"""The number of universe of discourse partitions, i.e., the number of fuzzy sets that will be created"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">membership_function</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'func'</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">)</span>
|
||||
<span class="sd">"""Fuzzy membership function (pyFTS.common.Membership)"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">setnames</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'names'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="sd">"""list of partitions names. If None is given the partitions will be auto named with prefix"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">prefix</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'prefix'</span><span class="p">,</span> <span class="s1">'A'</span><span class="p">)</span>
|
||||
<span class="sd">"""prefix of auto generated partition names"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">transformation</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'transformation'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="sd">"""data transformation to be applied on data"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">indexer</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'indexer'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">variable</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'variable'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'type'</span><span class="p">,</span> <span class="s1">'common'</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'preprocess'</span><span class="p">,</span><span class="kc">True</span><span class="p">):</span>
|
||||
|
||||
<span class="n">data</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'data'</span><span class="p">,[</span><span class="kc">None</span><span class="p">])</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_data</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">data</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">transformation</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">transformation</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="n">data</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_data</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="n">_min</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmin</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">_min</span> <span class="o">==</span> <span class="o">-</span><span class="n">np</span><span class="o">.</span><span class="n">inf</span><span class="p">:</span>
|
||||
<span class="n">ndata</span><span class="p">[</span><span class="n">ndata</span> <span class="o">==</span> <span class="o">-</span><span class="n">np</span><span class="o">.</span><span class="n">inf</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="n">_min</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmin</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">min</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">_min</span> <span class="o">*</span> <span class="mf">1.1</span> <span class="k">if</span> <span class="n">_min</span> <span class="o"><</span> <span class="mi">0</span> <span class="k">else</span> <span class="n">_min</span> <span class="o">*</span> <span class="mf">0.9</span><span class="p">)</span>
|
||||
|
||||
<span class="n">_max</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">max</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">_max</span> <span class="o">*</span> <span class="mf">1.1</span> <span class="k">if</span> <span class="n">_max</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="n">_max</span> <span class="o">*</span> <span class="mf">0.9</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">build</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">setnames</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">setnames</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">set_ordered</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
|
||||
|
||||
<span class="k">del</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="Partitioner.build"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner.build">[docs]</a> <span class="k">def</span> <span class="nf">build</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Perform the partitioning of the Universe of Discourse</span>
|
||||
|
||||
<span class="sd"> :param data: training data</span>
|
||||
<span class="sd"> :return: </span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">pass</span></div>
|
||||
|
||||
<div class="viewcode-block" id="Partitioner.get_name"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner.get_name">[docs]</a> <span class="k">def</span> <span class="nf">get_name</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">counter</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">prefix</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">counter</span><span class="p">)</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">setnames</span> <span class="ow">is</span> <span class="kc">None</span> <span class="k">else</span> <span class="bp">self</span><span class="o">.</span><span class="n">setnames</span><span class="p">[</span><span class="n">counter</span><span class="p">]</span></div>
|
||||
|
||||
<div class="viewcode-block" id="Partitioner.lower_set"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner.lower_set">[docs]</a> <span class="k">def</span> <span class="nf">lower_set</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span></div>
|
||||
|
||||
<div class="viewcode-block" id="Partitioner.upper_set"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner.upper_set">[docs]</a> <span class="k">def</span> <span class="nf">upper_set</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]]</span></div>
|
||||
|
||||
<div class="viewcode-block" id="Partitioner.plot"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner.plot">[docs]</a> <span class="k">def</span> <span class="nf">plot</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ax</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Plot the </span>
|
||||
<span class="sd"> :param ax: </span>
|
||||
<span class="sd"> :return: </span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">set_ylim</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">set_xlim</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">min</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">max</span><span class="p">])</span>
|
||||
<span class="n">ticks</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">x</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
|
||||
<span class="n">s</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span>
|
||||
<span class="k">if</span> <span class="n">s</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="s1">'common'</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">plot_set</span><span class="p">(</span><span class="n">ax</span><span class="p">,</span> <span class="n">s</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="n">s</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="s1">'composite'</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">ss</span> <span class="ow">in</span> <span class="n">s</span><span class="o">.</span><span class="n">sets</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">plot_set</span><span class="p">(</span><span class="n">ax</span><span class="p">,</span> <span class="n">ss</span><span class="p">)</span>
|
||||
<span class="n">ticks</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">centroid</span><span class="p">,</span><span class="mi">0</span><span class="p">))</span><span class="o">+</span><span class="s1">'</span><span class="se">\n</span><span class="s1">'</span><span class="o">+</span><span class="n">s</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
|
||||
<span class="n">x</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">centroid</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">xaxis</span><span class="o">.</span><span class="n">set_ticklabels</span><span class="p">(</span><span class="n">ticks</span><span class="p">)</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">xaxis</span><span class="o">.</span><span class="n">set_ticks</span><span class="p">(</span><span class="n">x</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="Partitioner.plot_set"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner.plot_set">[docs]</a> <span class="k">def</span> <span class="nf">plot_set</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ax</span><span class="p">,</span> <span class="n">s</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="n">s</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">:</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="n">s</span><span class="o">.</span><span class="n">parameters</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">s</span><span class="o">.</span><span class="n">parameters</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">s</span><span class="o">.</span><span class="n">parameters</span><span class="p">[</span><span class="mi">2</span><span class="p">]],</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="n">s</span><span class="o">.</span><span class="n">alpha</span><span class="p">,</span> <span class="mi">0</span><span class="p">])</span>
|
||||
<span class="k">elif</span> <span class="n">s</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">gaussmf</span><span class="p">:</span>
|
||||
<span class="n">tmpx</span> <span class="o">=</span> <span class="p">[</span><span class="n">kk</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">lower</span><span class="p">,</span> <span class="n">s</span><span class="o">.</span><span class="n">upper</span><span class="p">)]</span>
|
||||
<span class="n">tmpy</span> <span class="o">=</span> <span class="p">[</span><span class="n">s</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">kk</span><span class="p">)</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">lower</span><span class="p">,</span> <span class="n">s</span><span class="o">.</span><span class="n">upper</span><span class="p">)]</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">tmpx</span><span class="p">,</span> <span class="n">tmpy</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="n">s</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span><span class="p">:</span>
|
||||
<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">parameters</span><span class="p">,</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="n">s</span><span class="o">.</span><span class="n">alpha</span><span class="p">,</span> <span class="n">s</span><span class="o">.</span><span class="n">alpha</span><span class="p">,</span> <span class="mi">0</span><span class="p">])</span></div>
|
||||
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">+</span> <span class="s2">":</span><span class="se">\n</span><span class="s2">"</span>
|
||||
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
|
||||
<span class="n">tmp</span> <span class="o">+=</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">])</span><span class="o">+</span> <span class="s2">"</span><span class="se">\n</span><span class="s2">"</span>
|
||||
<span class="k">return</span> <span class="n">tmp</span></div>
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
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|
||||
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|
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|
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|
||||
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|
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|
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|
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|
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<h3>Quick search</h3>
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330
docs/_build/html/_modules/pyFTS/probabilistic/ProbabilityDistribution.html
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330
docs/_build/html/_modules/pyFTS/probabilistic/ProbabilityDistribution.html
vendored
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<h1>Source code for pyFTS.probabilistic.ProbabilityDistribution</h1><div class="highlight"><pre>
|
||||
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
|
||||
<span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span><span class="n">SortedCollection</span><span class="p">,</span><span class="n">tree</span>
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">kde</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="ProbabilityDistribution"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution">[docs]</a><span class="k">class</span> <span class="nc">ProbabilityDistribution</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Represents a discrete or continous probability distribution</span>
|
||||
<span class="sd"> If type is histogram, the PDF is discrete</span>
|
||||
<span class="sd"> If type is KDE the PDF is continuous</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="nb">type</span> <span class="o">=</span> <span class="s2">"KDE"</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">uod</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"uod"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="sd">"""Universe of discourse"""</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">data</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">=</span> <span class="nb">type</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> If type is histogram, the PDF is discrete</span>
|
||||
<span class="sd"> If type is KDE the PDF is continuous</span>
|
||||
<span class="sd"> """</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">bins</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"bins"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="sd">"""Number of bins on a discrete PDF"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">labels</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"bins_labels"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
<span class="sd">"""Bins labels on a discrete PDF"""</span>
|
||||
|
||||
<span class="n">data</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"data"</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="s2">"KDE"</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">kde</span> <span class="o">=</span> <span class="n">kde</span><span class="o">.</span><span class="n">KernelSmoothing</span><span class="p">(</span><span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"h"</span><span class="p">,</span> <span class="mf">0.5</span><span class="p">),</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"kernel"</span><span class="p">,</span> <span class="s2">"epanechnikov"</span><span class="p">))</span>
|
||||
<span class="n">_min</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmin</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">_min</span> <span class="o">=</span> <span class="n">_min</span> <span class="o">*</span> <span class="o">.</span><span class="mi">7</span> <span class="k">if</span> <span class="n">_min</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="n">_min</span> <span class="o">*</span> <span class="mf">1.3</span>
|
||||
<span class="n">_max</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmax</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">_max</span> <span class="o">=</span> <span class="n">_max</span> <span class="o">*</span> <span class="mf">1.3</span> <span class="k">if</span> <span class="n">_max</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="n">_max</span> <span class="o">*</span> <span class="o">.</span><span class="mi">7</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">uod</span> <span class="o">=</span> <span class="p">[</span><span class="n">_min</span><span class="p">,</span> <span class="n">_max</span><span class="p">]</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">nbins</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"num_bins"</span><span class="p">,</span> <span class="mi">100</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">bins</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">bins</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="nb">int</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">uod</span><span class="p">[</span><span class="mi">0</span><span class="p">]),</span> <span class="nb">int</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">uod</span><span class="p">[</span><span class="mi">1</span><span class="p">]),</span> <span class="nb">int</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">nbins</span><span class="p">))</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">labels</span> <span class="o">=</span> <span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">k</span><span class="p">)</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">bins</span><span class="p">]</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">uod</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">resolution</span> <span class="o">=</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">uod</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">uod</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">nbins</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">bin_index</span> <span class="o">=</span> <span class="n">SortedCollection</span><span class="o">.</span><span class="n">SortedCollection</span><span class="p">(</span><span class="n">iterable</span><span class="o">=</span><span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">bins</span><span class="p">))</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">quantile_index</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">distribution</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">cdf</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">qtl</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">bins</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">data</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">"name"</span><span class="p">,</span> <span class="s2">""</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilityDistribution.set"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.set">[docs]</a> <span class="k">def</span> <span class="nf">set</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">,</span> <span class="n">density</span><span class="p">):</span>
|
||||
<span class="n">k</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">bin_index</span><span class="o">.</span><span class="n">find_ge</span><span class="p">(</span><span class="n">value</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">=</span> <span class="n">density</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilityDistribution.append"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.append">[docs]</a> <span class="k">def</span> <span class="nf">append</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="s2">"histogram"</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">values</span><span class="p">:</span>
|
||||
<span class="n">v</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">bin_index</span><span class="o">.</span><span class="n">find_ge</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">v</span><span class="p">]</span> <span class="o">+=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="o">+=</span> <span class="mi">1</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">values</span><span class="p">)</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">distribution</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="n">dens</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">density</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">bins</span><span class="p">)</span>
|
||||
<span class="k">for</span> <span class="n">v</span><span class="p">,</span><span class="n">d</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">dens</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">bins</span><span class="p">[</span><span class="n">v</span><span class="p">]]</span> <span class="o">=</span> <span class="n">d</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilityDistribution.append_interval"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.append_interval">[docs]</a> <span class="k">def</span> <span class="nf">append_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">intervals</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="s2">"histogram"</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">interval</span> <span class="ow">in</span> <span class="n">intervals</span><span class="p">:</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">bin_index</span><span class="o">.</span><span class="n">inside</span><span class="p">(</span><span class="n">interval</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">interval</span><span class="p">[</span><span class="mi">1</span><span class="p">]):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">+=</span> <span class="mi">1</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="o">+=</span> <span class="mi">1</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilityDistribution.density"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.density">[docs]</a> <span class="k">def</span> <span class="nf">density</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">scalar</span> <span class="o">=</span> <span class="kc">False</span>
|
||||
|
||||
<span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">values</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="n">values</span> <span class="o">=</span> <span class="p">[</span><span class="n">values</span><span class="p">]</span>
|
||||
<span class="n">scalar</span> <span class="o">=</span> <span class="kc">True</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">values</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="s2">"histogram"</span><span class="p">:</span>
|
||||
<span class="n">v</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">bin_index</span><span class="o">.</span><span class="n">find_ge</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">v</span><span class="p">]</span> <span class="o">/</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="o">+</span> <span class="mf">1e-5</span><span class="p">))</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="s2">"KDE"</span><span class="p">:</span>
|
||||
<span class="n">v</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">kde</span><span class="o">.</span><span class="n">probability</span><span class="p">(</span><span class="n">k</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">v</span><span class="p">)</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">v</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">bin_index</span><span class="o">.</span><span class="n">find_ge</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">v</span><span class="p">])</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">scalar</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="n">ret</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilityDistribution.differential_offset"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.differential_offset">[docs]</a> <span class="k">def</span> <span class="nf">differential_offset</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">value</span><span class="p">):</span>
|
||||
<span class="n">nbins</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="n">dist</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">bins</span><span class="p">:</span>
|
||||
<span class="n">nk</span> <span class="o">=</span> <span class="n">k</span><span class="o">+</span><span class="n">value</span>
|
||||
<span class="n">nbins</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">nk</span><span class="p">)</span>
|
||||
<span class="n">dist</span><span class="p">[</span><span class="n">nk</span><span class="p">]</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">]</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">bins</span> <span class="o">=</span> <span class="n">nbins</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">distribution</span> <span class="o">=</span> <span class="n">dist</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">labels</span> <span class="o">=</span> <span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">k</span><span class="p">)</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">bins</span><span class="p">]</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">bin_index</span> <span class="o">=</span> <span class="n">SortedCollection</span><span class="o">.</span><span class="n">SortedCollection</span><span class="p">(</span><span class="n">iterable</span><span class="o">=</span><span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">bins</span><span class="p">))</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">quantile_index</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">cdf</span> <span class="o">=</span> <span class="kc">None</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">qtl</span> <span class="o">=</span> <span class="kc">None</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilityDistribution.expected_value"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.expected_value">[docs]</a> <span class="k">def</span> <span class="nf">expected_value</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">nansum</span><span class="p">([</span><span class="n">v</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">v</span><span class="p">]</span> <span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">bins</span><span class="p">])</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilityDistribution.build_cdf_qtl"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.build_cdf_qtl">[docs]</a> <span class="k">def</span> <span class="nf">build_cdf_qtl</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="mf">0.0</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">cdf</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">qtl</span> <span class="o">=</span> <span class="p">{}</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">bins</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">+=</span> <span class="bp">self</span><span class="o">.</span><span class="n">density</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
|
||||
<span class="k">if</span> <span class="n">k</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">cdf</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">cdf</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">=</span> <span class="n">ret</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">str</span><span class="p">(</span><span class="n">ret</span><span class="p">)</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">qtl</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">qtl</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">ret</span><span class="p">)]</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">qtl</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">ret</span><span class="p">)]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
|
||||
|
||||
<span class="n">_keys</span> <span class="o">=</span> <span class="p">[</span><span class="nb">float</span><span class="p">(</span><span class="n">k</span><span class="p">)</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">qtl</span><span class="o">.</span><span class="n">keys</span><span class="p">())]</span>
|
||||
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">quantile_index</span> <span class="o">=</span> <span class="n">SortedCollection</span><span class="o">.</span><span class="n">SortedCollection</span><span class="p">(</span><span class="n">iterable</span><span class="o">=</span><span class="n">_keys</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilityDistribution.cummulative"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.cummulative">[docs]</a> <span class="k">def</span> <span class="nf">cummulative</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">cdf</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">build_cdf_qtl</span><span class="p">()</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">values</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">val</span> <span class="ow">in</span> <span class="n">values</span><span class="p">:</span>
|
||||
<span class="n">k</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">bin_index</span><span class="o">.</span><span class="n">find_ge</span><span class="p">(</span><span class="n">val</span><span class="p">)</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">cdf</span><span class="p">[</span><span class="n">k</span><span class="p">])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">k</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">bin_index</span><span class="o">.</span><span class="n">find_ge</span><span class="p">(</span><span class="n">values</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">cdf</span><span class="p">[</span><span class="n">values</span><span class="p">]</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilityDistribution.quantile"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.quantile">[docs]</a> <span class="k">def</span> <span class="nf">quantile</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">values</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">qtl</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">build_cdf_qtl</span><span class="p">()</span>
|
||||
|
||||
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">values</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
|
||||
<span class="k">for</span> <span class="n">val</span> <span class="ow">in</span> <span class="n">values</span><span class="p">:</span>
|
||||
<span class="n">k</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">quantile_index</span><span class="o">.</span><span class="n">find_ge</span><span class="p">(</span><span class="n">val</span><span class="p">)</span>
|
||||
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">qtl</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">k</span><span class="p">)][</span><span class="mi">0</span><span class="p">])</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">k</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">quantile_index</span><span class="o">.</span><span class="n">find_ge</span><span class="p">(</span><span class="n">values</span><span class="p">)</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">qtl</span><span class="p">[</span><span class="nb">str</span><span class="p">(</span><span class="n">k</span><span class="p">)]</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilityDistribution.entropy"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.entropy">[docs]</a> <span class="k">def</span> <span class="nf">entropy</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">h</span> <span class="o">=</span> <span class="o">-</span><span class="nb">sum</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">])</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">bins</span><span class="p">])</span>
|
||||
<span class="k">return</span> <span class="n">h</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilityDistribution.crossentropy"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.crossentropy">[docs]</a> <span class="k">def</span> <span class="nf">crossentropy</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">q</span><span class="p">):</span>
|
||||
<span class="n">h</span> <span class="o">=</span> <span class="o">-</span><span class="nb">sum</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">q</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">])</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">bins</span><span class="p">])</span>
|
||||
<span class="k">return</span> <span class="n">h</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilityDistribution.kullbackleiblerdivergence"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.kullbackleiblerdivergence">[docs]</a> <span class="k">def</span> <span class="nf">kullbackleiblerdivergence</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">q</span><span class="p">):</span>
|
||||
<span class="n">h</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">]</span><span class="o">/</span><span class="n">q</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">])</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">bins</span><span class="p">])</span>
|
||||
<span class="k">return</span> <span class="n">h</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilityDistribution.empiricalloglikelihood"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.empiricalloglikelihood">[docs]</a> <span class="k">def</span> <span class="nf">empiricalloglikelihood</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">_s</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">bins</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">_s</span> <span class="o">+=</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">])</span>
|
||||
<span class="k">return</span> <span class="n">_s</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilityDistribution.pseudologlikelihood"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.pseudologlikelihood">[docs]</a> <span class="k">def</span> <span class="nf">pseudologlikelihood</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
|
||||
<span class="n">densities</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">density</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="n">_s</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">densities</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">k</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">_s</span> <span class="o">+=</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">_s</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilityDistribution.averageloglikelihood"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.averageloglikelihood">[docs]</a> <span class="k">def</span> <span class="nf">averageloglikelihood</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
|
||||
<span class="n">densities</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">density</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="n">_s</span> <span class="o">=</span> <span class="mi">0</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">densities</span><span class="p">:</span>
|
||||
<span class="k">if</span> <span class="n">k</span> <span class="o">></span> <span class="mi">0</span><span class="p">:</span>
|
||||
<span class="n">_s</span> <span class="o">+=</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">k</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">_s</span> <span class="o">/</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span></div>
|
||||
|
||||
<div class="viewcode-block" id="ProbabilityDistribution.plot"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.plot">[docs]</a> <span class="k">def</span> <span class="nf">plot</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">axis</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span><span class="n">color</span><span class="o">=</span><span class="s2">"black"</span><span class="p">,</span><span class="n">tam</span><span class="o">=</span><span class="p">[</span><span class="mi">10</span><span class="p">,</span> <span class="mi">6</span><span class="p">],</span> <span class="n">title</span> <span class="o">=</span> <span class="kc">None</span><span class="p">):</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">axis</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="n">tam</span><span class="p">)</span>
|
||||
<span class="n">axis</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">111</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="s2">"histogram"</span><span class="p">:</span>
|
||||
<span class="n">ys</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">]</span><span class="o">/</span><span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">bins</span><span class="p">]</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ys</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">bins</span><span class="p">]</span>
|
||||
<span class="n">yp</span> <span class="o">=</span> <span class="p">[</span><span class="mi">0</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">]</span>
|
||||
<span class="n">axis</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">data</span><span class="p">,</span> <span class="n">yp</span><span class="p">,</span> <span class="n">c</span><span class="o">=</span><span class="s2">"red"</span><span class="p">)</span>
|
||||
|
||||
<span class="k">if</span> <span class="n">title</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
|
||||
<span class="n">title</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span>
|
||||
<span class="n">axis</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">bins</span><span class="p">,</span> <span class="n">ys</span><span class="p">,</span> <span class="n">c</span><span class="o">=</span><span class="n">color</span><span class="p">)</span>
|
||||
<span class="n">axis</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="n">title</span><span class="p">)</span>
|
||||
|
||||
<span class="n">axis</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">'Universe of Discourse'</span><span class="p">)</span>
|
||||
<span class="n">axis</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">'Probability'</span><span class="p">)</span></div>
|
||||
|
||||
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">=</span> <span class="s2">""</span>
|
||||
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">bins</span><span class="p">):</span>
|
||||
<span class="n">ret</span> <span class="o">+=</span> <span class="nb">str</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">k</span><span class="p">,</span><span class="mi">2</span><span class="p">))</span> <span class="o">+</span> <span class="s1">':</span><span class="se">\t</span><span class="s1">'</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="s2">"histogram"</span><span class="p">:</span>
|
||||
<span class="n">ret</span> <span class="o">+=</span> <span class="nb">str</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">count</span><span class="p">,</span><span class="mi">3</span><span class="p">))</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="s2">"KDE"</span><span class="p">:</span>
|
||||
<span class="n">ret</span> <span class="o">+=</span> <span class="nb">str</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">density</span><span class="p">(</span><span class="n">k</span><span class="p">),</span><span class="mi">3</span><span class="p">))</span>
|
||||
<span class="k">else</span><span class="p">:</span>
|
||||
<span class="n">ret</span> <span class="o">+=</span> <span class="nb">str</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">distribution</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="mi">6</span><span class="p">))</span>
|
||||
<span class="n">ret</span> <span class="o">+=</span> <span class="s1">'</span><span class="se">\n</span><span class="s1">'</span>
|
||||
<span class="k">return</span> <span class="n">ret</span></div>
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
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|
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134
docs/_build/html/_modules/pyFTS/probabilistic/kde.html
vendored
Normal file
134
docs/_build/html/_modules/pyFTS/probabilistic/kde.html
vendored
Normal file
@ -0,0 +1,134 @@
|
||||
|
||||
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
|
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<title>pyFTS.probabilistic.kde — pyFTS 1.2.3 documentation</title>
|
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|
||||
|
||||
<h1>Source code for pyFTS.probabilistic.kde</h1><div class="highlight"><pre>
|
||||
<span></span><span class="c1"># -*- coding: utf8 -*-</span>
|
||||
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd">Kernel Density Estimation </span>
|
||||
<span class="sd">"""</span>
|
||||
|
||||
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Transformations</span>
|
||||
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
|
||||
|
||||
|
||||
<div class="viewcode-block" id="KernelSmoothing"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.kde.KernelSmoothing">[docs]</a><span class="k">class</span> <span class="nc">KernelSmoothing</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
|
||||
<span class="sd">"""Kernel Density Estimation"""</span>
|
||||
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">h</span><span class="p">,</span> <span class="n">kernel</span><span class="o">=</span><span class="s2">"epanechnikov"</span><span class="p">):</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">h</span> <span class="o">=</span> <span class="n">h</span>
|
||||
<span class="sd">"""Width parameter"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">kernel</span> <span class="o">=</span> <span class="n">kernel</span>
|
||||
<span class="sd">"""Kernel function"""</span>
|
||||
<span class="bp">self</span><span class="o">.</span><span class="n">transf</span> <span class="o">=</span> <span class="n">Transformations</span><span class="o">.</span><span class="n">Scale</span><span class="p">(</span><span class="nb">min</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span><span class="nb">max</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
|
||||
|
||||
<div class="viewcode-block" id="KernelSmoothing.kernel_function"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.kde.KernelSmoothing.kernel_function">[docs]</a> <span class="k">def</span> <span class="nf">kernel_function</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">u</span><span class="p">):</span>
|
||||
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">kernel</span> <span class="o">==</span> <span class="s2">"epanechnikov"</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="p">(</span><span class="mi">3</span><span class="o">/</span><span class="mi">4</span><span class="p">)</span><span class="o">*</span><span class="p">(</span><span class="mf">1.0</span> <span class="o">-</span> <span class="n">u</span><span class="o">**</span><span class="mi">2</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">tmp</span> <span class="k">if</span> <span class="n">tmp</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="mi">0</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">kernel</span> <span class="o">==</span> <span class="s2">"gaussian"</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="p">(</span><span class="mf">1.0</span><span class="o">/</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="mi">2</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="p">))</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="o">-</span><span class="mf">0.5</span><span class="o">*</span><span class="n">u</span><span class="o">**</span><span class="mi">2</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">kernel</span> <span class="o">==</span> <span class="s2">"uniform"</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="mf">0.5</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">kernel</span> <span class="o">==</span> <span class="s2">"triangular"</span><span class="p">:</span>
|
||||
<span class="n">tmp</span> <span class="o">=</span> <span class="mf">1.0</span> <span class="o">-</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">u</span><span class="p">)</span>
|
||||
<span class="k">return</span> <span class="n">tmp</span> <span class="k">if</span> <span class="n">tmp</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="mi">0</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">kernel</span> <span class="o">==</span> <span class="s2">"logistic"</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="mf">1.0</span><span class="o">/</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="n">u</span><span class="p">)</span><span class="o">+</span><span class="mi">2</span><span class="o">+</span><span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="o">-</span><span class="n">u</span><span class="p">))</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">kernel</span> <span class="o">==</span> <span class="s2">"cosine"</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="o">/</span><span class="mf">4.0</span><span class="p">)</span><span class="o">*</span><span class="n">np</span><span class="o">.</span><span class="n">cos</span><span class="p">((</span><span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="o">/</span><span class="mf">2.0</span><span class="p">)</span><span class="o">*</span><span class="n">u</span><span class="p">)</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">kernel</span> <span class="o">==</span> <span class="s2">"sigmoid"</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="p">(</span><span class="mf">2.0</span><span class="o">/</span><span class="n">np</span><span class="o">.</span><span class="n">pi</span><span class="p">)</span><span class="o">*</span><span class="p">(</span><span class="mf">1.0</span><span class="o">/</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="n">u</span><span class="p">)</span><span class="o">+</span><span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="o">-</span><span class="n">u</span><span class="p">)))</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">kernel</span> <span class="o">==</span> <span class="s2">"tophat"</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="mi">1</span> <span class="k">if</span> <span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">u</span><span class="p">)</span> <span class="o"><</span> <span class="mf">0.5</span> <span class="k">else</span> <span class="mi">0</span>
|
||||
<span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">kernel</span> <span class="o">==</span> <span class="s2">"exponential"</span><span class="p">:</span>
|
||||
<span class="k">return</span> <span class="mf">0.5</span> <span class="o">*</span> <span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="o">-</span><span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">u</span><span class="p">))</span></div>
|
||||
|
||||
<div class="viewcode-block" id="KernelSmoothing.probability"><a class="viewcode-back" href="../../../pyFTS.probabilistic.html#pyFTS.probabilistic.kde.KernelSmoothing.probability">[docs]</a> <span class="k">def</span> <span class="nf">probability</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
|
||||
<span class="sd">"""</span>
|
||||
<span class="sd"> Probability of the point x on data</span>
|
||||
|
||||
<span class="sd"> :param x:</span>
|
||||
<span class="sd"> :param data:</span>
|
||||
<span class="sd"> :return:</span>
|
||||
<span class="sd"> """</span>
|
||||
<span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
|
||||
<span class="n">ndata</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">transf</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
|
||||
<span class="n">nx</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">transf</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
|
||||
<span class="n">p</span> <span class="o">=</span> <span class="nb">sum</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">kernel_function</span><span class="p">((</span><span class="n">nx</span> <span class="o">-</span> <span class="n">k</span><span class="p">)</span><span class="o">/</span><span class="bp">self</span><span class="o">.</span><span class="n">h</span><span class="p">)</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">ndata</span><span class="p">])</span> <span class="o">/</span> <span class="n">l</span><span class="o">*</span><span class="bp">self</span><span class="o">.</span><span class="n">h</span>
|
||||
|
||||
<span class="k">return</span> <span class="n">p</span></div></div>
|
||||
</pre></div>
|
||||
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
|
||||
<div class="sphinxsidebarwrapper"><div class="relations">
|
||||
<h3>Related Topics</h3>
|
||||
<ul>
|
||||
<li><a href="../../../index.html">Documentation overview</a><ul>
|
||||
<li><a href="../../index.html">Module code</a><ul>
|
||||
</ul></li>
|
||||
</ul></li>
|
||||
</ul>
|
||||
</div>
|
||||
<div id="searchbox" style="display: none" role="search">
|
||||
<h3>Quick search</h3>
|
||||
<div class="searchformwrapper">
|
||||
<form class="search" action="../../../search.html" method="get">
|
||||
<input type="text" name="q" />
|
||||
<input type="submit" value="Go" />
|
||||
<input type="hidden" name="check_keywords" value="yes" />
|
||||
<input type="hidden" name="area" value="default" />
|
||||
</form>
|
||||
</div>
|
||||
</div>
|
||||
<script type="text/javascript">$('#searchbox').show(0);</script>
|
||||
</div>
|
||||
</div>
|
||||
<div class="clearer"></div>
|
||||
</div>
|
||||
<div class="footer">
|
||||
©2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
|
||||
|
||||
|
|
||||
Powered by <a href="http://sphinx-doc.org/">Sphinx 1.7.2</a>
|
||||
& <a href="https://github.com/bitprophet/alabaster">Alabaster 0.7.10</a>
|
||||
|
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</div>
|
||||
|
||||
|
||||
|
||||
|
||||
</body>
|
||||
</html>
|
||||
20
docs/_build/html/_sources/index.rst.txt
vendored
Normal file
20
docs/_build/html/_sources/index.rst.txt
vendored
Normal file
@ -0,0 +1,20 @@
|
||||
.. pyFTS documentation master file, created by
|
||||
sphinx-quickstart on Wed Aug 29 13:47:28 2018.
|
||||
You can adapt this file completely to your liking, but it should at least
|
||||
contain the root `toctree` directive.
|
||||
|
||||
Welcome to pyFTS's documentation!
|
||||
=================================
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 2
|
||||
:caption: Contents:
|
||||
|
||||
|
||||
|
||||
Indices and tables
|
||||
==================
|
||||
|
||||
* :ref:`genindex`
|
||||
* :ref:`modindex`
|
||||
* :ref:`search`
|
||||
7
docs/_build/html/_sources/modules.rst.txt
vendored
Normal file
7
docs/_build/html/_sources/modules.rst.txt
vendored
Normal file
@ -0,0 +1,7 @@
|
||||
pyFTS
|
||||
=====
|
||||
|
||||
.. toctree::
|
||||
:maxdepth: 4
|
||||
|
||||
pyFTS
|
||||
94
docs/_build/html/_sources/pyFTS.benchmarks.rst.txt
vendored
Normal file
94
docs/_build/html/_sources/pyFTS.benchmarks.rst.txt
vendored
Normal file
@ -0,0 +1,94 @@
|
||||
pyFTS.benchmarks package
|
||||
========================
|
||||
|
||||
Submodules
|
||||
----------
|
||||
|
||||
pyFTS.benchmarks.Measures module
|
||||
--------------------------------
|
||||
|
||||
.. automodule:: pyFTS.benchmarks.Measures
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.benchmarks.ResidualAnalysis module
|
||||
----------------------------------------
|
||||
|
||||
.. automodule:: pyFTS.benchmarks.ResidualAnalysis
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.benchmarks.Util module
|
||||
----------------------------
|
||||
|
||||
.. automodule:: pyFTS.benchmarks.Util
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.benchmarks.arima module
|
||||
-----------------------------
|
||||
|
||||
.. automodule:: pyFTS.benchmarks.arima
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.benchmarks.benchmarks module
|
||||
----------------------------------
|
||||
|
||||
.. automodule:: pyFTS.benchmarks.benchmarks
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.benchmarks.distributed\_benchmarks module
|
||||
-----------------------------------------------
|
||||
|
||||
.. automodule:: pyFTS.benchmarks.distributed_benchmarks
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.benchmarks.knn module
|
||||
---------------------------
|
||||
|
||||
.. automodule:: pyFTS.benchmarks.knn
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.benchmarks.naive module
|
||||
-----------------------------
|
||||
|
||||
.. automodule:: pyFTS.benchmarks.naive
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.benchmarks.parallel\_benchmarks module
|
||||
--------------------------------------------
|
||||
|
||||
.. automodule:: pyFTS.benchmarks.parallel_benchmarks
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.benchmarks.quantreg module
|
||||
--------------------------------
|
||||
|
||||
.. automodule:: pyFTS.benchmarks.quantreg
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
|
||||
Module contents
|
||||
---------------
|
||||
|
||||
.. automodule:: pyFTS.benchmarks
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
94
docs/_build/html/_sources/pyFTS.common.rst.txt
vendored
Normal file
94
docs/_build/html/_sources/pyFTS.common.rst.txt
vendored
Normal file
@ -0,0 +1,94 @@
|
||||
pyFTS.common package
|
||||
====================
|
||||
|
||||
Submodules
|
||||
----------
|
||||
|
||||
pyFTS.common.Composite module
|
||||
-----------------------------
|
||||
|
||||
.. automodule:: pyFTS.common.Composite
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.common.FLR module
|
||||
-----------------------
|
||||
|
||||
.. automodule:: pyFTS.common.FLR
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.common.FuzzySet module
|
||||
----------------------------
|
||||
|
||||
.. automodule:: pyFTS.common.FuzzySet
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.common.Membership module
|
||||
------------------------------
|
||||
|
||||
.. automodule:: pyFTS.common.Membership
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.common.SortedCollection module
|
||||
------------------------------------
|
||||
|
||||
.. automodule:: pyFTS.common.SortedCollection
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.common.Transformations module
|
||||
-----------------------------------
|
||||
|
||||
.. automodule:: pyFTS.common.Transformations
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.common.Util module
|
||||
------------------------
|
||||
|
||||
.. automodule:: pyFTS.common.Util
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.common.flrg module
|
||||
------------------------
|
||||
|
||||
.. automodule:: pyFTS.common.flrg
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.common.fts module
|
||||
-----------------------
|
||||
|
||||
.. automodule:: pyFTS.common.fts
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.common.tree module
|
||||
------------------------
|
||||
|
||||
.. automodule:: pyFTS.common.tree
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
|
||||
Module contents
|
||||
---------------
|
||||
|
||||
.. automodule:: pyFTS.common
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
134
docs/_build/html/_sources/pyFTS.data.rst.txt
vendored
Normal file
134
docs/_build/html/_sources/pyFTS.data.rst.txt
vendored
Normal file
@ -0,0 +1,134 @@
|
||||
pyFTS.data package
|
||||
==================
|
||||
|
||||
Submodules
|
||||
----------
|
||||
|
||||
pyFTS.data.AirPassengers module
|
||||
-------------------------------
|
||||
|
||||
.. automodule:: pyFTS.data.AirPassengers
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.data.Enrollments module
|
||||
-----------------------------
|
||||
|
||||
.. automodule:: pyFTS.data.Enrollments
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.data.INMET module
|
||||
-----------------------
|
||||
|
||||
.. automodule:: pyFTS.data.INMET
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.data.NASDAQ module
|
||||
------------------------
|
||||
|
||||
.. automodule:: pyFTS.data.NASDAQ
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.data.SONDA module
|
||||
-----------------------
|
||||
|
||||
.. automodule:: pyFTS.data.SONDA
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.data.SP500 module
|
||||
-----------------------
|
||||
|
||||
.. automodule:: pyFTS.data.SP500
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.data.TAIEX module
|
||||
-----------------------
|
||||
|
||||
.. automodule:: pyFTS.data.TAIEX
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.data.artificial module
|
||||
----------------------------
|
||||
|
||||
.. automodule:: pyFTS.data.artificial
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.data.common module
|
||||
------------------------
|
||||
|
||||
.. automodule:: pyFTS.data.common
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.data.henon module
|
||||
-----------------------
|
||||
|
||||
.. automodule:: pyFTS.data.henon
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.data.logistic\_map module
|
||||
-------------------------------
|
||||
|
||||
.. automodule:: pyFTS.data.logistic_map
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.data.lorentz module
|
||||
-------------------------
|
||||
|
||||
.. automodule:: pyFTS.data.lorentz
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.data.mackey\_glass module
|
||||
-------------------------------
|
||||
|
||||
.. automodule:: pyFTS.data.mackey_glass
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.data.rossler module
|
||||
-------------------------
|
||||
|
||||
.. automodule:: pyFTS.data.rossler
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.data.sunspots module
|
||||
--------------------------
|
||||
|
||||
.. automodule:: pyFTS.data.sunspots
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
|
||||
Module contents
|
||||
---------------
|
||||
|
||||
.. automodule:: pyFTS.data
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
30
docs/_build/html/_sources/pyFTS.models.ensemble.rst.txt
vendored
Normal file
30
docs/_build/html/_sources/pyFTS.models.ensemble.rst.txt
vendored
Normal file
@ -0,0 +1,30 @@
|
||||
pyFTS.models.ensemble package
|
||||
=============================
|
||||
|
||||
Submodules
|
||||
----------
|
||||
|
||||
pyFTS.models.ensemble.ensemble module
|
||||
-------------------------------------
|
||||
|
||||
.. automodule:: pyFTS.models.ensemble.ensemble
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
pyFTS.models.ensemble.multiseasonal module
|
||||
------------------------------------------
|
||||
|
||||
.. automodule:: pyFTS.models.ensemble.multiseasonal
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
|
||||
|
||||
Module contents
|
||||
---------------
|
||||
|
||||
.. automodule:: pyFTS.models.ensemble
|
||||
:members:
|
||||
:undoc-members:
|
||||
:show-inheritance:
|
||||
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in New Issue
Block a user