618 lines
37 KiB
HTML
618 lines
37 KiB
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<title>pyFTS.data package — pyFTS 1.2.3 documentation</title>
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<div class="section" id="pyfts-data-package">
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<h1>pyFTS.data package<a class="headerlink" href="#pyfts-data-package" title="Permalink to this headline">¶</a></h1>
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<div class="section" id="submodules">
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<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline">¶</a></h2>
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</div>
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<div class="section" id="module-pyFTS.data.AirPassengers">
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<span id="pyfts-data-airpassengers-module"></span><h2>pyFTS.data.AirPassengers module<a class="headerlink" href="#module-pyFTS.data.AirPassengers" title="Permalink to this headline">¶</a></h2>
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<dl class="function">
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<dt id="pyFTS.data.AirPassengers.get_data">
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<code class="descclassname">pyFTS.data.AirPassengers.</code><code class="descname">get_data</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/AirPassengers.html#get_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.AirPassengers.get_data" title="Permalink to this definition">¶</a></dt>
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<dd><p>Get a simple univariate time series data.</p>
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<table class="docutils field-list" frame="void" rules="none">
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<col class="field-name" />
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<col class="field-body" />
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<tbody valign="top">
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<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">numpy array</td>
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</tr>
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</tbody>
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</table>
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</dd></dl>
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<dl class="function">
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<dt id="pyFTS.data.AirPassengers.get_dataframe">
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<code class="descclassname">pyFTS.data.AirPassengers.</code><code class="descname">get_dataframe</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/AirPassengers.html#get_dataframe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.AirPassengers.get_dataframe" title="Permalink to this definition">¶</a></dt>
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<dd><p>Get the complete multivariate time series data.</p>
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<table class="docutils field-list" frame="void" rules="none">
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<col class="field-name" />
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<col class="field-body" />
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<tbody valign="top">
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<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Pandas DataFrame</td>
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</tr>
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</tbody>
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</table>
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</dd></dl>
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</div>
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<div class="section" id="module-pyFTS.data.Enrollments">
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<span id="pyfts-data-enrollments-module"></span><h2>pyFTS.data.Enrollments module<a class="headerlink" href="#module-pyFTS.data.Enrollments" title="Permalink to this headline">¶</a></h2>
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<dl class="function">
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<dt id="pyFTS.data.Enrollments.get_data">
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<code class="descclassname">pyFTS.data.Enrollments.</code><code class="descname">get_data</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/Enrollments.html#get_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.Enrollments.get_data" title="Permalink to this definition">¶</a></dt>
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<dd><p>Get a simple univariate time series data.</p>
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<table class="docutils field-list" frame="void" rules="none">
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<col class="field-name" />
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<col class="field-body" />
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<tbody valign="top">
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<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">numpy array</td>
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</tr>
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</tbody>
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</table>
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</dd></dl>
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<dl class="function">
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<dt id="pyFTS.data.Enrollments.get_dataframe">
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<code class="descclassname">pyFTS.data.Enrollments.</code><code class="descname">get_dataframe</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/Enrollments.html#get_dataframe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.Enrollments.get_dataframe" title="Permalink to this definition">¶</a></dt>
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<dd></dd></dl>
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</div>
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<div class="section" id="module-pyFTS.data.INMET">
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<span id="pyfts-data-inmet-module"></span><h2>pyFTS.data.INMET module<a class="headerlink" href="#module-pyFTS.data.INMET" title="Permalink to this headline">¶</a></h2>
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<p>INMET - Instituto Nacional Meteorologia / Brasil</p>
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<p>Belo Horizonte station, from 2000-01-01 to 31/12/2012</p>
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<p>Source: <a class="reference external" href="http://www.inmet.gov.br">http://www.inmet.gov.br</a></p>
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<dl class="function">
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<dt id="pyFTS.data.INMET.get_dataframe">
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<code class="descclassname">pyFTS.data.INMET.</code><code class="descname">get_dataframe</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/INMET.html#get_dataframe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.INMET.get_dataframe" title="Permalink to this definition">¶</a></dt>
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<dd><p>Get the complete multivariate time series data.</p>
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<table class="docutils field-list" frame="void" rules="none">
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<col class="field-name" />
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<col class="field-body" />
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<tbody valign="top">
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<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Pandas DataFrame</td>
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</tr>
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</tbody>
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</table>
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</dd></dl>
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</div>
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<div class="section" id="module-pyFTS.data.NASDAQ">
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<span id="pyfts-data-nasdaq-module"></span><h2>pyFTS.data.NASDAQ module<a class="headerlink" href="#module-pyFTS.data.NASDAQ" title="Permalink to this headline">¶</a></h2>
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<dl class="function">
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<dt id="pyFTS.data.NASDAQ.get_data">
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<code class="descclassname">pyFTS.data.NASDAQ.</code><code class="descname">get_data</code><span class="sig-paren">(</span><em>field='avg'</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/NASDAQ.html#get_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.NASDAQ.get_data" title="Permalink to this definition">¶</a></dt>
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<dd><p>Get a simple univariate time series data.</p>
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<table class="docutils field-list" frame="void" rules="none">
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<col class="field-name" />
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<col class="field-body" />
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<tbody valign="top">
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<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>field</strong> – the dataset field name to extract</td>
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</tr>
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<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">numpy array</td>
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</tr>
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</tbody>
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</table>
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</dd></dl>
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<dl class="function">
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<dt id="pyFTS.data.NASDAQ.get_dataframe">
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<code class="descclassname">pyFTS.data.NASDAQ.</code><code class="descname">get_dataframe</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/NASDAQ.html#get_dataframe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.NASDAQ.get_dataframe" title="Permalink to this definition">¶</a></dt>
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<dd><p>Get the complete multivariate time series data.</p>
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<table class="docutils field-list" frame="void" rules="none">
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<col class="field-name" />
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<col class="field-body" />
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<tbody valign="top">
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<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Pandas DataFrame</td>
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</tr>
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</tbody>
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</table>
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</dd></dl>
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</div>
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<div class="section" id="module-pyFTS.data.SONDA">
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<span id="pyfts-data-sonda-module"></span><h2>pyFTS.data.SONDA module<a class="headerlink" href="#module-pyFTS.data.SONDA" title="Permalink to this headline">¶</a></h2>
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<p>SONDA - Sistema de Organização Nacional de Dados Ambientais, from INPE - Instituto Nacional de Pesquisas Espaciais, Brasil.</p>
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<p>Brasilia station</p>
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<p>Source: <a class="reference external" href="http://sonda.ccst.inpe.br/">http://sonda.ccst.inpe.br/</a></p>
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<dl class="function">
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<dt id="pyFTS.data.SONDA.get_data">
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<code class="descclassname">pyFTS.data.SONDA.</code><code class="descname">get_data</code><span class="sig-paren">(</span><em>field</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/SONDA.html#get_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.SONDA.get_data" title="Permalink to this definition">¶</a></dt>
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<dd><p>Get a simple univariate time series data.</p>
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<table class="docutils field-list" frame="void" rules="none">
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<col class="field-name" />
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<col class="field-body" />
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<tbody valign="top">
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<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>field</strong> – the dataset field name to extract</td>
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</tr>
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<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">numpy array</td>
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</tr>
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</tbody>
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</table>
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</dd></dl>
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<dl class="function">
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<dt id="pyFTS.data.SONDA.get_dataframe">
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<code class="descclassname">pyFTS.data.SONDA.</code><code class="descname">get_dataframe</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/SONDA.html#get_dataframe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.SONDA.get_dataframe" title="Permalink to this definition">¶</a></dt>
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<dd><p>Get the complete multivariate time series data.</p>
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<table class="docutils field-list" frame="void" rules="none">
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<col class="field-name" />
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<col class="field-body" />
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<tbody valign="top">
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<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Pandas DataFrame</td>
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</tr>
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</tbody>
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</table>
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</dd></dl>
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</div>
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<div class="section" id="module-pyFTS.data.SP500">
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<span id="pyfts-data-sp500-module"></span><h2>pyFTS.data.SP500 module<a class="headerlink" href="#module-pyFTS.data.SP500" title="Permalink to this headline">¶</a></h2>
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<dl class="function">
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<dt id="pyFTS.data.SP500.get_data">
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<code class="descclassname">pyFTS.data.SP500.</code><code class="descname">get_data</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/SP500.html#get_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.SP500.get_data" title="Permalink to this definition">¶</a></dt>
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<dd><p>Get the univariate time series data.</p>
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<table class="docutils field-list" frame="void" rules="none">
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<col class="field-name" />
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<col class="field-body" />
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<tbody valign="top">
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<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">numpy array</td>
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</tr>
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</tbody>
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</table>
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</dd></dl>
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<dl class="function">
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<dt id="pyFTS.data.SP500.get_dataframe">
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<code class="descclassname">pyFTS.data.SP500.</code><code class="descname">get_dataframe</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/SP500.html#get_dataframe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.SP500.get_dataframe" title="Permalink to this definition">¶</a></dt>
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<dd><p>Get the complete multivariate time series data.</p>
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<table class="docutils field-list" frame="void" rules="none">
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<col class="field-name" />
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<col class="field-body" />
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<tbody valign="top">
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<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Pandas DataFrame</td>
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</tr>
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</tbody>
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</table>
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</dd></dl>
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</div>
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<div class="section" id="module-pyFTS.data.TAIEX">
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<span id="pyfts-data-taiex-module"></span><h2>pyFTS.data.TAIEX module<a class="headerlink" href="#module-pyFTS.data.TAIEX" title="Permalink to this headline">¶</a></h2>
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<dl class="function">
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<dt id="pyFTS.data.TAIEX.get_data">
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<code class="descclassname">pyFTS.data.TAIEX.</code><code class="descname">get_data</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/TAIEX.html#get_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.TAIEX.get_data" title="Permalink to this definition">¶</a></dt>
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<dd><p>Get the univariate time series data.</p>
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<table class="docutils field-list" frame="void" rules="none">
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<col class="field-name" />
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<col class="field-body" />
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<tbody valign="top">
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<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">numpy array</td>
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</tr>
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</tbody>
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</table>
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</dd></dl>
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<dl class="function">
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<dt id="pyFTS.data.TAIEX.get_dataframe">
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<code class="descclassname">pyFTS.data.TAIEX.</code><code class="descname">get_dataframe</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/TAIEX.html#get_dataframe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.TAIEX.get_dataframe" title="Permalink to this definition">¶</a></dt>
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<dd><p>Get the complete multivariate time series data.</p>
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<table class="docutils field-list" frame="void" rules="none">
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<col class="field-name" />
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<col class="field-body" />
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|
|
<tbody valign="top">
|
|||
|
|
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Pandas DataFrame</td>
|
|||
|
|
</tr>
|
|||
|
|
</tbody>
|
|||
|
|
</table>
|
|||
|
|
</dd></dl>
|
|||
|
|
|
|||
|
|
</div>
|
|||
|
|
<div class="section" id="module-pyFTS.data.artificial">
|
|||
|
|
<span id="pyfts-data-artificial-module"></span><h2>pyFTS.data.artificial module<a class="headerlink" href="#module-pyFTS.data.artificial" title="Permalink to this headline">¶</a></h2>
|
|||
|
|
<p>Facilities to generate synthetic stochastic processes</p>
|
|||
|
|
<dl class="function">
|
|||
|
|
<dt id="pyFTS.data.artificial.generate_gaussian_linear">
|
|||
|
|
<code class="descclassname">pyFTS.data.artificial.</code><code class="descname">generate_gaussian_linear</code><span class="sig-paren">(</span><em>mu_ini</em>, <em>sigma_ini</em>, <em>mu_inc</em>, <em>sigma_inc</em>, <em>it=100</em>, <em>num=10</em>, <em>vmin=None</em>, <em>vmax=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/artificial.html#generate_gaussian_linear"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.artificial.generate_gaussian_linear" title="Permalink to this definition">¶</a></dt>
|
|||
|
|
<dd><p>Generate data sampled from Gaussian distribution, with constant or linear changing parameters</p>
|
|||
|
|
<table class="docutils field-list" frame="void" rules="none">
|
|||
|
|
<col class="field-name" />
|
|||
|
|
<col class="field-body" />
|
|||
|
|
<tbody valign="top">
|
|||
|
|
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
|
|||
|
|
<li><strong>mu_ini</strong> – Initial mean</li>
|
|||
|
|
<li><strong>sigma_ini</strong> – Initial variance</li>
|
|||
|
|
<li><strong>mu_inc</strong> – Mean increment after ‘num’ samples</li>
|
|||
|
|
<li><strong>sigma_inc</strong> – Variance increment after ‘num’ samples</li>
|
|||
|
|
<li><strong>it</strong> – Number of iterations</li>
|
|||
|
|
<li><strong>num</strong> – Number of samples generated on each iteration</li>
|
|||
|
|
<li><strong>vmin</strong> – Lower bound value of generated data</li>
|
|||
|
|
<li><strong>vmax</strong> – Upper bound value of generated data</li>
|
|||
|
|
</ul>
|
|||
|
|
</td>
|
|||
|
|
</tr>
|
|||
|
|
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">A list of it*num float values</p>
|
|||
|
|
</td>
|
|||
|
|
</tr>
|
|||
|
|
</tbody>
|
|||
|
|
</table>
|
|||
|
|
</dd></dl>
|
|||
|
|
|
|||
|
|
<dl class="function">
|
|||
|
|
<dt id="pyFTS.data.artificial.generate_uniform_linear">
|
|||
|
|
<code class="descclassname">pyFTS.data.artificial.</code><code class="descname">generate_uniform_linear</code><span class="sig-paren">(</span><em>min_ini</em>, <em>max_ini</em>, <em>min_inc</em>, <em>max_inc</em>, <em>it=100</em>, <em>num=10</em>, <em>vmin=None</em>, <em>vmax=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/artificial.html#generate_uniform_linear"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.artificial.generate_uniform_linear" title="Permalink to this definition">¶</a></dt>
|
|||
|
|
<dd><p>Generate data sampled from Uniform distribution, with constant or linear changing bounds</p>
|
|||
|
|
<table class="docutils field-list" frame="void" rules="none">
|
|||
|
|
<col class="field-name" />
|
|||
|
|
<col class="field-body" />
|
|||
|
|
<tbody valign="top">
|
|||
|
|
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
|
|||
|
|
<li><strong>mu_ini</strong> – Initial mean</li>
|
|||
|
|
<li><strong>sigma_ini</strong> – Initial variance</li>
|
|||
|
|
<li><strong>mu_inc</strong> – Mean increment after ‘num’ samples</li>
|
|||
|
|
<li><strong>sigma_inc</strong> – Variance increment after ‘num’ samples</li>
|
|||
|
|
<li><strong>it</strong> – Number of iterations</li>
|
|||
|
|
<li><strong>num</strong> – Number of samples generated on each iteration</li>
|
|||
|
|
<li><strong>vmin</strong> – Lower bound value of generated data</li>
|
|||
|
|
<li><strong>vmax</strong> – Upper bound value of generated data</li>
|
|||
|
|
</ul>
|
|||
|
|
</td>
|
|||
|
|
</tr>
|
|||
|
|
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">A list of it*num float values</p>
|
|||
|
|
</td>
|
|||
|
|
</tr>
|
|||
|
|
</tbody>
|
|||
|
|
</table>
|
|||
|
|
</dd></dl>
|
|||
|
|
|
|||
|
|
<dl class="function">
|
|||
|
|
<dt id="pyFTS.data.artificial.random_walk">
|
|||
|
|
<code class="descclassname">pyFTS.data.artificial.</code><code class="descname">random_walk</code><span class="sig-paren">(</span><em>n=500</em>, <em>type='gaussian'</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/artificial.html#random_walk"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.artificial.random_walk" title="Permalink to this definition">¶</a></dt>
|
|||
|
|
<dd></dd></dl>
|
|||
|
|
|
|||
|
|
<dl class="function">
|
|||
|
|
<dt id="pyFTS.data.artificial.white_noise">
|
|||
|
|
<code class="descclassname">pyFTS.data.artificial.</code><code class="descname">white_noise</code><span class="sig-paren">(</span><em>n=500</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/artificial.html#white_noise"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.artificial.white_noise" title="Permalink to this definition">¶</a></dt>
|
|||
|
|
<dd></dd></dl>
|
|||
|
|
|
|||
|
|
</div>
|
|||
|
|
<div class="section" id="module-pyFTS.data.common">
|
|||
|
|
<span id="pyfts-data-common-module"></span><h2>pyFTS.data.common module<a class="headerlink" href="#module-pyFTS.data.common" title="Permalink to this headline">¶</a></h2>
|
|||
|
|
<dl class="function">
|
|||
|
|
<dt id="pyFTS.data.common.get_dataframe">
|
|||
|
|
<code class="descclassname">pyFTS.data.common.</code><code class="descname">get_dataframe</code><span class="sig-paren">(</span><em>filename</em>, <em>url</em>, <em>sep=';'</em>, <em>compression='infer'</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/common.html#get_dataframe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.common.get_dataframe" title="Permalink to this definition">¶</a></dt>
|
|||
|
|
<dd><p>This method check if filename already exists, read the file and return its data.
|
|||
|
|
If the file don’t already exists, it will be downloaded and decompressed.</p>
|
|||
|
|
<table class="docutils field-list" frame="void" rules="none">
|
|||
|
|
<col class="field-name" />
|
|||
|
|
<col class="field-body" />
|
|||
|
|
<tbody valign="top">
|
|||
|
|
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
|
|||
|
|
<li><strong>filename</strong> – dataset local filename</li>
|
|||
|
|
<li><strong>url</strong> – dataset internet URL</li>
|
|||
|
|
<li><strong>sep</strong> – CSV field separator</li>
|
|||
|
|
<li><strong>compression</strong> – type of compression</li>
|
|||
|
|
</ul>
|
|||
|
|
</td>
|
|||
|
|
</tr>
|
|||
|
|
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">Pandas dataset</p>
|
|||
|
|
</td>
|
|||
|
|
</tr>
|
|||
|
|
</tbody>
|
|||
|
|
</table>
|
|||
|
|
</dd></dl>
|
|||
|
|
|
|||
|
|
</div>
|
|||
|
|
<div class="section" id="module-pyFTS.data.henon">
|
|||
|
|
<span id="pyfts-data-henon-module"></span><h2>pyFTS.data.henon module<a class="headerlink" href="#module-pyFTS.data.henon" title="Permalink to this headline">¶</a></h2>
|
|||
|
|
<dl class="function">
|
|||
|
|
<dt id="pyFTS.data.henon.get_data">
|
|||
|
|
<code class="descclassname">pyFTS.data.henon.</code><code class="descname">get_data</code><span class="sig-paren">(</span><em>var, a=1.4, b=0.3, initial_values=[1, 1], iterations=1000</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/henon.html#get_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.henon.get_data" title="Permalink to this definition">¶</a></dt>
|
|||
|
|
<dd></dd></dl>
|
|||
|
|
|
|||
|
|
<dl class="function">
|
|||
|
|
<dt id="pyFTS.data.henon.get_dataframe">
|
|||
|
|
<code class="descclassname">pyFTS.data.henon.</code><code class="descname">get_dataframe</code><span class="sig-paren">(</span><em>a=1.4, b=0.3, initial_values=[1, 1], iterations=1000</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/henon.html#get_dataframe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.henon.get_dataframe" title="Permalink to this definition">¶</a></dt>
|
|||
|
|
<dd><ol class="upperalpha simple" start="13">
|
|||
|
|
<li>Hénon. “A two-dimensional mapping with a strange attractor”. Commun. Math. Phys. 50, 69-77 (1976)</li>
|
|||
|
|
</ol>
|
|||
|
|
<p>dx/dt = a + by(t-1) - x(t-1)^2
|
|||
|
|
dy/dt = x</p>
|
|||
|
|
<table class="docutils field-list" frame="void" rules="none">
|
|||
|
|
<col class="field-name" />
|
|||
|
|
<col class="field-body" />
|
|||
|
|
<tbody valign="top">
|
|||
|
|
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
|
|||
|
|
<li><strong>a</strong> – Equation coefficient</li>
|
|||
|
|
<li><strong>b</strong> – Equation coefficient</li>
|
|||
|
|
<li><strong>initial_values</strong> – numpy array with the initial values of x and y. Default: [1, 1]</li>
|
|||
|
|
<li><strong>iterations</strong> – number of iterations. Default: 1000</li>
|
|||
|
|
</ul>
|
|||
|
|
</td>
|
|||
|
|
</tr>
|
|||
|
|
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">Panda dataframe with the x and y values</p>
|
|||
|
|
</td>
|
|||
|
|
</tr>
|
|||
|
|
</tbody>
|
|||
|
|
</table>
|
|||
|
|
</dd></dl>
|
|||
|
|
|
|||
|
|
</div>
|
|||
|
|
<div class="section" id="module-pyFTS.data.logistic_map">
|
|||
|
|
<span id="pyfts-data-logistic-map-module"></span><h2>pyFTS.data.logistic_map module<a class="headerlink" href="#module-pyFTS.data.logistic_map" title="Permalink to this headline">¶</a></h2>
|
|||
|
|
<dl class="function">
|
|||
|
|
<dt id="pyFTS.data.logistic_map.get_data">
|
|||
|
|
<code class="descclassname">pyFTS.data.logistic_map.</code><code class="descname">get_data</code><span class="sig-paren">(</span><em>r=4</em>, <em>initial_value=0.3</em>, <em>iterations=100</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/logistic_map.html#get_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.logistic_map.get_data" title="Permalink to this definition">¶</a></dt>
|
|||
|
|
<dd><p>May, Robert M. (1976). “Simple mathematical models with very complicated dynamics”.
|
|||
|
|
Nature. 261 (5560): 459–467. doi:10.1038/261459a0.</p>
|
|||
|
|
<p>x(t) = r * x(t-1) * (1 - x(t -1) )</p>
|
|||
|
|
<table class="docutils field-list" frame="void" rules="none">
|
|||
|
|
<col class="field-name" />
|
|||
|
|
<col class="field-body" />
|
|||
|
|
<tbody valign="top">
|
|||
|
|
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
|
|||
|
|
<li><strong>r</strong> – Equation coefficient</li>
|
|||
|
|
<li><strong>initial_value</strong> – Initial value of x. Default: 0.3</li>
|
|||
|
|
<li><strong>iterations</strong> – number of iterations. Default: 100</li>
|
|||
|
|
</ul>
|
|||
|
|
</td>
|
|||
|
|
</tr>
|
|||
|
|
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
|
|||
|
|
</td>
|
|||
|
|
</tr>
|
|||
|
|
</tbody>
|
|||
|
|
</table>
|
|||
|
|
</dd></dl>
|
|||
|
|
|
|||
|
|
</div>
|
|||
|
|
<div class="section" id="module-pyFTS.data.lorentz">
|
|||
|
|
<span id="pyfts-data-lorentz-module"></span><h2>pyFTS.data.lorentz module<a class="headerlink" href="#module-pyFTS.data.lorentz" title="Permalink to this headline">¶</a></h2>
|
|||
|
|
<dl class="function">
|
|||
|
|
<dt id="pyFTS.data.lorentz.get_data">
|
|||
|
|
<code class="descclassname">pyFTS.data.lorentz.</code><code class="descname">get_data</code><span class="sig-paren">(</span><em>var, a=10.0, b=28.0, c=2.6666666666666665, dt=0.01, initial_values=[0.1, 0, 0], iterations=1000</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/lorentz.html#get_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.lorentz.get_data" title="Permalink to this definition">¶</a></dt>
|
|||
|
|
<dd></dd></dl>
|
|||
|
|
|
|||
|
|
<dl class="function">
|
|||
|
|
<dt id="pyFTS.data.lorentz.get_dataframe">
|
|||
|
|
<code class="descclassname">pyFTS.data.lorentz.</code><code class="descname">get_dataframe</code><span class="sig-paren">(</span><em>a=10.0, b=28.0, c=2.6666666666666665, dt=0.01, initial_values=[0.1, 0, 0], iterations=1000</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/lorentz.html#get_dataframe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.lorentz.get_dataframe" title="Permalink to this definition">¶</a></dt>
|
|||
|
|
<dd><p>Lorenz, Edward Norton (1963). “Deterministic nonperiodic flow”. Journal of the Atmospheric Sciences. 20 (2): 130–141.
|
|||
|
|
<a class="reference external" href="https://doi.org/10.1175/1520-0469(1963">https://doi.org/10.1175/1520-0469(1963</a>)020<0130:DNF>2.0.CO;2</p>
|
|||
|
|
<p>dx/dt = a(y -x)
|
|||
|
|
dy/dt = x(b - z) - y
|
|||
|
|
dz/dt = xy - cz</p>
|
|||
|
|
<table class="docutils field-list" frame="void" rules="none">
|
|||
|
|
<col class="field-name" />
|
|||
|
|
<col class="field-body" />
|
|||
|
|
<tbody valign="top">
|
|||
|
|
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
|
|||
|
|
<li><strong>a</strong> – Equation coefficient. Default value: 10</li>
|
|||
|
|
<li><strong>b</strong> – Equation coefficient. Default value: 28</li>
|
|||
|
|
<li><strong>c</strong> – Equation coefficient. Default value: 8.0/3.0</li>
|
|||
|
|
<li><strong>dt</strong> – Time differential for continuous time integration. Default value: 0.01</li>
|
|||
|
|
<li><strong>initial_values</strong> – numpy array with the initial values of x,y and z. Default: [0.1, 0, 0]</li>
|
|||
|
|
<li><strong>iterations</strong> – number of iterations. Default: 1000</li>
|
|||
|
|
</ul>
|
|||
|
|
</td>
|
|||
|
|
</tr>
|
|||
|
|
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">Panda dataframe with the x, y and z values</p>
|
|||
|
|
</td>
|
|||
|
|
</tr>
|
|||
|
|
</tbody>
|
|||
|
|
</table>
|
|||
|
|
</dd></dl>
|
|||
|
|
|
|||
|
|
</div>
|
|||
|
|
<div class="section" id="module-pyFTS.data.mackey_glass">
|
|||
|
|
<span id="pyfts-data-mackey-glass-module"></span><h2>pyFTS.data.mackey_glass module<a class="headerlink" href="#module-pyFTS.data.mackey_glass" title="Permalink to this headline">¶</a></h2>
|
|||
|
|
<dl class="function">
|
|||
|
|
<dt id="pyFTS.data.mackey_glass.get_data">
|
|||
|
|
<code class="descclassname">pyFTS.data.mackey_glass.</code><code class="descname">get_data</code><span class="sig-paren">(</span><em>b=0.1</em>, <em>c=0.2</em>, <em>tau=17</em>, <em>initial_values=array([0.5</em>, <em>0.55882353</em>, <em>0.61764706</em>, <em>0.67647059</em>, <em>0.73529412</em>, <em>0.79411765</em>, <em>0.85294118</em>, <em>0.91176471</em>, <em>0.97058824</em>, <em>1.02941176</em>, <em>1.08823529</em>, <em>1.14705882</em>, <em>1.20588235</em>, <em>1.26470588</em>, <em>1.32352941</em>, <em>1.38235294</em>, <em>1.44117647</em>, <em>1.5 ])</em>, <em>iterations=1000</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/mackey_glass.html#get_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.mackey_glass.get_data" title="Permalink to this definition">¶</a></dt>
|
|||
|
|
<dd><p>Mackey, M. C. and Glass, L. (1977). Oscillation and chaos in physiological control systems.
|
|||
|
|
Science, 197(4300):287-289.</p>
|
|||
|
|
<p>dy/dt = -by(t)+ cy(t - tau) / 1+y(t-tau)^10</p>
|
|||
|
|
<table class="docutils field-list" frame="void" rules="none">
|
|||
|
|
<col class="field-name" />
|
|||
|
|
<col class="field-body" />
|
|||
|
|
<tbody valign="top">
|
|||
|
|
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
|
|||
|
|
<li><strong>b</strong> – Equation coefficient</li>
|
|||
|
|
<li><strong>c</strong> – Equation coefficient</li>
|
|||
|
|
<li><strong>tau</strong> – Lag parameter, default: 17</li>
|
|||
|
|
<li><strong>initial_values</strong> – numpy array with the initial values of y. Default: np.linspace(0.5,1.5,18)</li>
|
|||
|
|
<li><strong>iterations</strong> – number of iterations. Default: 1000</li>
|
|||
|
|
</ul>
|
|||
|
|
</td>
|
|||
|
|
</tr>
|
|||
|
|
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
|
|||
|
|
</td>
|
|||
|
|
</tr>
|
|||
|
|
</tbody>
|
|||
|
|
</table>
|
|||
|
|
</dd></dl>
|
|||
|
|
|
|||
|
|
</div>
|
|||
|
|
<div class="section" id="module-pyFTS.data.rossler">
|
|||
|
|
<span id="pyfts-data-rossler-module"></span><h2>pyFTS.data.rossler module<a class="headerlink" href="#module-pyFTS.data.rossler" title="Permalink to this headline">¶</a></h2>
|
|||
|
|
<dl class="function">
|
|||
|
|
<dt id="pyFTS.data.rossler.get_data">
|
|||
|
|
<code class="descclassname">pyFTS.data.rossler.</code><code class="descname">get_data</code><span class="sig-paren">(</span><em>var, a=0.2, b=0.2, c=5.7, dt=0.01, initial_values=[0.001, 0.001, 0.001], iterations=5000</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/rossler.html#get_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.rossler.get_data" title="Permalink to this definition">¶</a></dt>
|
|||
|
|
<dd></dd></dl>
|
|||
|
|
|
|||
|
|
<dl class="function">
|
|||
|
|
<dt id="pyFTS.data.rossler.get_dataframe">
|
|||
|
|
<code class="descclassname">pyFTS.data.rossler.</code><code class="descname">get_dataframe</code><span class="sig-paren">(</span><em>a=0.2, b=0.2, c=5.7, dt=0.01, initial_values=[0.001, 0.001, 0.001], iterations=5000</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/rossler.html#get_dataframe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.rossler.get_dataframe" title="Permalink to this definition">¶</a></dt>
|
|||
|
|
<dd><ol class="upperalpha simple" start="15">
|
|||
|
|
<li><ol class="first upperalpha" start="5">
|
|||
|
|
<li>Rössler, Phys. Lett. 57A, 397 (1976).</li>
|
|||
|
|
</ol>
|
|||
|
|
</li>
|
|||
|
|
</ol>
|
|||
|
|
<p>dx/dt = -z - y
|
|||
|
|
dy/dt = x + ay
|
|||
|
|
dz/dt = b + z( x - c )</p>
|
|||
|
|
<table class="docutils field-list" frame="void" rules="none">
|
|||
|
|
<col class="field-name" />
|
|||
|
|
<col class="field-body" />
|
|||
|
|
<tbody valign="top">
|
|||
|
|
<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
|
|||
|
|
<li><strong>a</strong> – Equation coefficient. Default value: 0.2</li>
|
|||
|
|
<li><strong>b</strong> – Equation coefficient. Default value: 0.2</li>
|
|||
|
|
<li><strong>c</strong> – Equation coefficient. Default value: 5.7</li>
|
|||
|
|
<li><strong>dt</strong> – Time differential for continuous time integration. Default value: 0.01</li>
|
|||
|
|
<li><strong>initial_values</strong> – numpy array with the initial values of x,y and z. Default: [0.001, 0.001, 0.001]</li>
|
|||
|
|
<li><strong>iterations</strong> – number of iterations. Default: 5000</li>
|
|||
|
|
</ul>
|
|||
|
|
</td>
|
|||
|
|
</tr>
|
|||
|
|
<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">Panda dataframe with the x, y and z values</p>
|
|||
|
|
</td>
|
|||
|
|
</tr>
|
|||
|
|
</tbody>
|
|||
|
|
</table>
|
|||
|
|
</dd></dl>
|
|||
|
|
|
|||
|
|
</div>
|
|||
|
|
<div class="section" id="module-pyFTS.data.sunspots">
|
|||
|
|
<span id="pyfts-data-sunspots-module"></span><h2>pyFTS.data.sunspots module<a class="headerlink" href="#module-pyFTS.data.sunspots" title="Permalink to this headline">¶</a></h2>
|
|||
|
|
<dl class="function">
|
|||
|
|
<dt id="pyFTS.data.sunspots.get_data">
|
|||
|
|
<code class="descclassname">pyFTS.data.sunspots.</code><code class="descname">get_data</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/sunspots.html#get_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.sunspots.get_data" title="Permalink to this definition">¶</a></dt>
|
|||
|
|
<dd><p>Get a simple univariate time series data.</p>
|
|||
|
|
<table class="docutils field-list" frame="void" rules="none">
|
|||
|
|
<col class="field-name" />
|
|||
|
|
<col class="field-body" />
|
|||
|
|
<tbody valign="top">
|
|||
|
|
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">numpy array</td>
|
|||
|
|
</tr>
|
|||
|
|
</tbody>
|
|||
|
|
</table>
|
|||
|
|
</dd></dl>
|
|||
|
|
|
|||
|
|
<dl class="function">
|
|||
|
|
<dt id="pyFTS.data.sunspots.get_dataframe">
|
|||
|
|
<code class="descclassname">pyFTS.data.sunspots.</code><code class="descname">get_dataframe</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/data/sunspots.html#get_dataframe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.sunspots.get_dataframe" title="Permalink to this definition">¶</a></dt>
|
|||
|
|
<dd><p>Get the complete multivariate time series data.</p>
|
|||
|
|
<table class="docutils field-list" frame="void" rules="none">
|
|||
|
|
<col class="field-name" />
|
|||
|
|
<col class="field-body" />
|
|||
|
|
<tbody valign="top">
|
|||
|
|
<tr class="field-odd field"><th class="field-name">Returns:</th><td class="field-body">Pandas DataFrame</td>
|
|||
|
|
</tr>
|
|||
|
|
</tbody>
|
|||
|
|
</table>
|
|||
|
|
</dd></dl>
|
|||
|
|
|
|||
|
|
</div>
|
|||
|
|
<div class="section" id="module-pyFTS.data">
|
|||
|
|
<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-pyFTS.data" title="Permalink to this headline">¶</a></h2>
|
|||
|
|
<p>Module for pyFTS standard datasets facilities</p>
|
|||
|
|
</div>
|
|||
|
|
</div>
|
|||
|
|
|
|||
|
|
|
|||
|
|
</div>
|
|||
|
|
</div>
|
|||
|
|
</div>
|
|||
|
|
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
|
|||
|
|
<div class="sphinxsidebarwrapper">
|
|||
|
|
<h3><a href="index.html">Table Of Contents</a></h3>
|
|||
|
|
<ul>
|
|||
|
|
<li><a class="reference internal" href="#">pyFTS.data package</a><ul>
|
|||
|
|
<li><a class="reference internal" href="#submodules">Submodules</a></li>
|
|||
|
|
<li><a class="reference internal" href="#module-pyFTS.data.AirPassengers">pyFTS.data.AirPassengers module</a></li>
|
|||
|
|
<li><a class="reference internal" href="#module-pyFTS.data.Enrollments">pyFTS.data.Enrollments module</a></li>
|
|||
|
|
<li><a class="reference internal" href="#module-pyFTS.data.INMET">pyFTS.data.INMET module</a></li>
|
|||
|
|
<li><a class="reference internal" href="#module-pyFTS.data.NASDAQ">pyFTS.data.NASDAQ module</a></li>
|
|||
|
|
<li><a class="reference internal" href="#module-pyFTS.data.SONDA">pyFTS.data.SONDA module</a></li>
|
|||
|
|
<li><a class="reference internal" href="#module-pyFTS.data.SP500">pyFTS.data.SP500 module</a></li>
|
|||
|
|
<li><a class="reference internal" href="#module-pyFTS.data.TAIEX">pyFTS.data.TAIEX module</a></li>
|
|||
|
|
<li><a class="reference internal" href="#module-pyFTS.data.artificial">pyFTS.data.artificial module</a></li>
|
|||
|
|
<li><a class="reference internal" href="#module-pyFTS.data.common">pyFTS.data.common module</a></li>
|
|||
|
|
<li><a class="reference internal" href="#module-pyFTS.data.henon">pyFTS.data.henon module</a></li>
|
|||
|
|
<li><a class="reference internal" href="#module-pyFTS.data.logistic_map">pyFTS.data.logistic_map module</a></li>
|
|||
|
|
<li><a class="reference internal" href="#module-pyFTS.data.lorentz">pyFTS.data.lorentz module</a></li>
|
|||
|
|
<li><a class="reference internal" href="#module-pyFTS.data.mackey_glass">pyFTS.data.mackey_glass module</a></li>
|
|||
|
|
<li><a class="reference internal" href="#module-pyFTS.data.rossler">pyFTS.data.rossler module</a></li>
|
|||
|
|
<li><a class="reference internal" href="#module-pyFTS.data.sunspots">pyFTS.data.sunspots module</a></li>
|
|||
|
|
<li><a class="reference internal" href="#module-pyFTS.data">Module contents</a></li>
|
|||
|
|
</ul>
|
|||
|
|
</li>
|
|||
|
|
</ul>
|
|||
|
|
<div class="relations">
|
|||
|
|
<h3>Related Topics</h3>
|
|||
|
|
<ul>
|
|||
|
|
<li><a href="index.html">Documentation overview</a><ul>
|
|||
|
|
</ul></li>
|
|||
|
|
</ul>
|
|||
|
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|
|||
|
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|
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|
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<h3>This Page</h3>
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©2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
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