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Updating documentation for the included data modules

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Petrônio Cândido 2018-09-06 14:36:08 -03:00
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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>
<li><a href="pyFTS/data/AirPassengers.html">pyFTS.data.AirPassengers</a></li>
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<h1>Source code for pyFTS.data.Bitcoin</h1><div class="highlight"><pre>
<span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">Bitcoin to USD quotations</span>
<span class="sd">Daily averaged index, by business day, from 2010 to 2018.</span>
<span class="sd">Source: https://finance.yahoo.com/quote/BTC-USD?p=BTC-USD</span>
<span class="sd">&quot;&quot;&quot;</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.Bitcoin.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">():</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the univariate time series data.</span>
<span class="sd"> :return: numpy array</span>
<span class="sd"> &quot;&quot;&quot;</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">&quot;Avg&quot;</span><span class="p">])</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Bitcoin.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
<span class="sd"> :return: Pandas DataFrame</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;https://query.data.world/s/72gews5w3c7oaf7by5vp7evsasluia&#39;</span><span class="p">)</span>
<span class="k">return</span> <span class="n">df</span></div>
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<h1>Source code for pyFTS.data.DowJones</h1><div class="highlight"><pre>
<span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">DJI - Dow Jones</span>
<span class="sd">Daily averaged index, by business day, from 1985 to 2017.</span>
<span class="sd">Source: https://finance.yahoo.com/quote/%5EGSPC/history?p=%5EGSPC</span>
<span class="sd">&quot;&quot;&quot;</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.DowJones.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">():</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the univariate time series data.</span>
<span class="sd"> :return: numpy array</span>
<span class="sd"> &quot;&quot;&quot;</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">&quot;Avg&quot;</span><span class="p">])</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.DowJones.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
<span class="sd"> :return: Pandas DataFrame</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;https://query.data.world/s/d4hfir3xrelkx33o3bfs5dbhyiztml&#39;</span><span class="p">)</span>
<span class="k">return</span> <span class="n">df</span></div>
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<h1>Source code for pyFTS.data.EURGBP</h1><div class="highlight"><pre>
<span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">FOREX market EUR-GBP pair.</span>
<span class="sd">Daily averaged quotations, by business day, from 2016 to 2018.</span>
<span class="sd">&quot;&quot;&quot;</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.EURGBP.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">():</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the univariate time series data.</span>
<span class="sd"> :return: numpy array</span>
<span class="sd"> &quot;&quot;&quot;</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">&quot;Avg&quot;</span><span class="p">])</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.EURGBP.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
<span class="sd"> :return: Pandas DataFrame</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;https://query.data.world/s/gvsaeruthnxjkwzl7z4ki7u5rduah3&#39;</span><span class="p">)</span>
<span class="k">return</span> <span class="n">df</span></div>
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<h1>Source code for pyFTS.data.EURUSD</h1><div class="highlight"><pre>
<span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">FOREX market EUR-USD pair.</span>
<span class="sd">Daily averaged quotations, by business day, from 2016 to 2018.</span>
<span class="sd">&quot;&quot;&quot;</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.EURUSD.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">():</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the univariate time series data.</span>
<span class="sd"> :return: numpy array</span>
<span class="sd"> &quot;&quot;&quot;</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">&quot;Avg&quot;</span><span class="p">])</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.EURUSD.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
<span class="sd"> :return: Pandas DataFrame</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;https://query.data.world/s/od4eojioz4w6o5bbwxjfn6j5zoqtos&#39;</span><span class="p">)</span>
<span class="k">return</span> <span class="n">df</span></div>
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<!doctype html>
<html xmlns="http://www.w3.org/1999/xhtml">
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<title>pyFTS.data.Ethereum &#8212; pyFTS 1.2.3 documentation</title>
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<h1>Source code for pyFTS.data.Ethereum</h1><div class="highlight"><pre>
<span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">Ethereum to USD quotations</span>
<span class="sd">Daily averaged index, by business day, from 2016 to 2018.</span>
<span class="sd">Source: https://finance.yahoo.com/quote/ETH-USD?p=ETH-USD</span>
<span class="sd">&quot;&quot;&quot;</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.Ethereum.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">():</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the univariate time series data.</span>
<span class="sd"> :return: numpy array</span>
<span class="sd"> &quot;&quot;&quot;</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">&quot;Avg&quot;</span><span class="p">])</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.Ethereum.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
<span class="sd"> :return: Pandas DataFrame</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;https://query.data.world/s/qj4ly7o4rl7oq527xzy4v76wkr3hws&#39;</span><span class="p">)</span>
<span class="k">return</span> <span class="n">df</span></div>
</pre></div>
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<title>pyFTS.data.GBPUSD &#8212; pyFTS 1.2.3 documentation</title>
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<h1>Source code for pyFTS.data.GBPUSD</h1><div class="highlight"><pre>
<span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">FOREX market GBP-USD pair.</span>
<span class="sd">Daily averaged quotations, by business day, from 2016 to 2018.</span>
<span class="sd">&quot;&quot;&quot;</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.GBPUSD.get_data">[docs]</a><span class="k">def</span> <span class="nf">get_data</span><span class="p">():</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the univariate time series data.</span>
<span class="sd"> :return: numpy array</span>
<span class="sd"> &quot;&quot;&quot;</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">&quot;Avg&quot;</span><span class="p">])</span></div>
<div class="viewcode-block" id="get_dataframe"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.GBPUSD.get_dataframe">[docs]</a><span class="k">def</span> <span class="nf">get_dataframe</span><span class="p">():</span>
<span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Get the complete multivariate time series data.</span>
<span class="sd"> :return: Pandas DataFrame</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">read_csv</span><span class="p">(</span><span class="s1">&#39;https://query.data.world/s/sw4mijpowb3mqv6bsat7cdj54hyxix&#39;</span><span class="p">)</span>
<span class="k">return</span> <span class="n">df</span></div>
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113
docs/build/html/_sources/pyFTS.data.rst.txt vendored
View File

@ -1,6 +1,10 @@
pyFTS.data package
==================
.. toctree::
:maxdepth: 3
:caption: Index:
Module contents
---------------
@ -8,11 +12,24 @@ Module contents
:members:
:undoc-members:
:show-inheritance:
Submodules
----------
pyFTS.data.AirPassengers module
pyFTS.data.common module
------------------------
.. automodule:: pyFTS.data.common
:members:
:undoc-members:
:show-inheritance:
Datasets
--------
AirPassengers dataset
-------------------------------
.. automodule:: pyFTS.data.AirPassengers
@ -20,15 +37,65 @@ pyFTS.data.AirPassengers module
:undoc-members:
:show-inheritance:
pyFTS.data.Enrollments module
Bitcoin dataset
-------------------------------
.. automodule:: pyFTS.data.Bitcoin
:members:
:undoc-members:
:show-inheritance:
DowJones dataset
-----------------------------
.. automodule:: pyFTS.data.DowJones
:members:
:undoc-members:
:show-inheritance:
Enrollments dataset
-----------------------------
.. automodule:: pyFTS.data.Enrollments
:members:
:undoc-members:
:show-inheritance:
Ethereum dataset
-----------------------------
pyFTS.data.INMET module
.. automodule:: pyFTS.data.Ethereum
:members:
:undoc-members:
:show-inheritance:
EUR-GBP dataset
-----------------------------
.. automodule:: pyFTS.data.EURGBP
:members:
:undoc-members:
:show-inheritance:
EUR-USD dataset
-----------------------------
.. automodule:: pyFTS.data.EURUSD
:members:
:undoc-members:
:show-inheritance:
GBP-USD dataset
-----------------------------
.. automodule:: pyFTS.data.GBPUSD
:members:
:undoc-members:
:show-inheritance:
INMET dataset
-----------------------
.. automodule:: pyFTS.data.INMET
@ -36,7 +103,7 @@ pyFTS.data.INMET module
:undoc-members:
:show-inheritance:
pyFTS.data.NASDAQ module
NASDAQ module
------------------------
.. automodule:: pyFTS.data.NASDAQ
@ -44,7 +111,7 @@ pyFTS.data.NASDAQ module
:undoc-members:
:show-inheritance:
pyFTS.data.SONDA module
SONDA dataset
-----------------------
.. automodule:: pyFTS.data.SONDA
@ -52,7 +119,7 @@ pyFTS.data.SONDA module
:undoc-members:
:show-inheritance:
pyFTS.data.SP500 module
S&P 500 dataset
-----------------------
.. automodule:: pyFTS.data.SP500
@ -60,7 +127,7 @@ pyFTS.data.SP500 module
:undoc-members:
:show-inheritance:
pyFTS.data.TAIEX module
TAIEX dataset
-----------------------
.. automodule:: pyFTS.data.TAIEX
@ -76,56 +143,48 @@ pyFTS.data.artificial module
:undoc-members:
:show-inheritance:
pyFTS.data.common module
------------------------
.. automodule:: pyFTS.data.common
:members:
:undoc-members:
:show-inheritance:
pyFTS.data.henon module
-----------------------
Henon chaotic time series
-------------------------
.. automodule:: pyFTS.data.henon
:members:
:undoc-members:
:show-inheritance:
pyFTS.data.logistic\_map module
-------------------------------
Logistic\_map chaotic time series
----------------------------------
.. automodule:: pyFTS.data.logistic_map
:members:
:undoc-members:
:show-inheritance:
pyFTS.data.lorentz module
-------------------------
Lorentz chaotic time series
---------------------------
.. automodule:: pyFTS.data.lorentz
:members:
:undoc-members:
:show-inheritance:
pyFTS.data.mackey\_glass module
-------------------------------
Mackey-Glass chaotic time series
--------------------------------
.. automodule:: pyFTS.data.mackey_glass
:members:
:undoc-members:
:show-inheritance:
pyFTS.data.rossler module
-------------------------
Rossler chaotic time series
---------------------------
.. automodule:: pyFTS.data.rossler
:members:
:undoc-members:
:show-inheritance:
pyFTS.data.sunspots module
--------------------------
Sunspots dataset
----------------
.. automodule:: pyFTS.data.sunspots
:members:

44
docs/build/html/genindex.html vendored
View File

@ -698,7 +698,19 @@
<li><a href="pyFTS.data.html#pyFTS.data.AirPassengers.get_data">get_data() (in module pyFTS.data.AirPassengers)</a>
<ul>
<li><a href="pyFTS.data.html#pyFTS.data.Bitcoin.get_data">(in module pyFTS.data.Bitcoin)</a>
</li>
<li><a href="pyFTS.data.html#pyFTS.data.DowJones.get_data">(in module pyFTS.data.DowJones)</a>
</li>
<li><a href="pyFTS.data.html#pyFTS.data.EURGBP.get_data">(in module pyFTS.data.EURGBP)</a>
</li>
<li><a href="pyFTS.data.html#pyFTS.data.EURUSD.get_data">(in module pyFTS.data.EURUSD)</a>
</li>
<li><a href="pyFTS.data.html#pyFTS.data.Enrollments.get_data">(in module pyFTS.data.Enrollments)</a>
</li>
<li><a href="pyFTS.data.html#pyFTS.data.Ethereum.get_data">(in module pyFTS.data.Ethereum)</a>
</li>
<li><a href="pyFTS.data.html#pyFTS.data.GBPUSD.get_data">(in module pyFTS.data.GBPUSD)</a>
</li>
<li><a href="pyFTS.data.html#pyFTS.data.NASDAQ.get_data">(in module pyFTS.data.NASDAQ)</a>
</li>
@ -740,7 +752,19 @@
<li><a href="pyFTS.data.html#pyFTS.data.AirPassengers.get_dataframe">get_dataframe() (in module pyFTS.data.AirPassengers)</a>
<ul>
<li><a href="pyFTS.data.html#pyFTS.data.Bitcoin.get_dataframe">(in module pyFTS.data.Bitcoin)</a>
</li>
<li><a href="pyFTS.data.html#pyFTS.data.DowJones.get_dataframe">(in module pyFTS.data.DowJones)</a>
</li>
<li><a href="pyFTS.data.html#pyFTS.data.EURGBP.get_dataframe">(in module pyFTS.data.EURGBP)</a>
</li>
<li><a href="pyFTS.data.html#pyFTS.data.EURUSD.get_dataframe">(in module pyFTS.data.EURUSD)</a>
</li>
<li><a href="pyFTS.data.html#pyFTS.data.Enrollments.get_dataframe">(in module pyFTS.data.Enrollments)</a>
</li>
<li><a href="pyFTS.data.html#pyFTS.data.Ethereum.get_dataframe">(in module pyFTS.data.Ethereum)</a>
</li>
<li><a href="pyFTS.data.html#pyFTS.data.GBPUSD.get_dataframe">(in module pyFTS.data.GBPUSD)</a>
</li>
<li><a href="pyFTS.data.html#pyFTS.data.INMET.get_dataframe">(in module pyFTS.data.INMET)</a>
</li>
@ -763,14 +787,14 @@
<li><a href="pyFTS.data.html#pyFTS.data.sunspots.get_dataframe">(in module pyFTS.data.sunspots)</a>
</li>
</ul></li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.Util.get_dataframe_from_bd">get_dataframe_from_bd() (in module pyFTS.benchmarks.Util)</a>
</li>
<li><a href="pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS.get_distribution_interquantile">get_distribution_interquantile() (pyFTS.models.ensemble.ensemble.EnsembleFTS method)</a>
</li>
<li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.get_distribution_statistics">get_distribution_statistics() (in module pyFTS.benchmarks.Measures)</a>
</li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="pyFTS.common.html#pyFTS.common.FuzzySet.get_fuzzysets">get_fuzzysets() (in module pyFTS.common.FuzzySet)</a>
</li>
<li><a href="pyFTS.models.seasonal.html#pyFTS.models.seasonal.SeasonalIndexer.DateTimeSeasonalIndexer.get_index">get_index() (pyFTS.models.seasonal.SeasonalIndexer.DateTimeSeasonalIndexer method)</a>
@ -1355,14 +1379,14 @@
</li>
<li><a href="pyFTS.benchmarks.html#module-pyFTS.benchmarks.naive">pyFTS.benchmarks.naive (module)</a>
</li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="pyFTS.benchmarks.html#module-pyFTS.benchmarks.quantreg">pyFTS.benchmarks.quantreg (module)</a>
</li>
<li><a href="pyFTS.benchmarks.html#module-pyFTS.benchmarks.ResidualAnalysis">pyFTS.benchmarks.ResidualAnalysis (module)</a>
</li>
<li><a href="pyFTS.benchmarks.html#module-pyFTS.benchmarks.Util">pyFTS.benchmarks.Util (module)</a>
</li>
</ul></td>
<td style="width: 33%; vertical-align: top;"><ul>
<li><a href="pyFTS.common.html#module-pyFTS.common">pyFTS.common (module)</a>
</li>
<li><a href="pyFTS.common.html#module-pyFTS.common.Composite">pyFTS.common.Composite (module)</a>
@ -1392,10 +1416,22 @@
<li><a href="pyFTS.data.html#module-pyFTS.data.AirPassengers">pyFTS.data.AirPassengers (module)</a>
</li>
<li><a href="pyFTS.data.html#module-pyFTS.data.artificial">pyFTS.data.artificial (module)</a>
</li>
<li><a href="pyFTS.data.html#module-pyFTS.data.Bitcoin">pyFTS.data.Bitcoin (module)</a>
</li>
<li><a href="pyFTS.data.html#module-pyFTS.data.common">pyFTS.data.common (module)</a>
</li>
<li><a href="pyFTS.data.html#module-pyFTS.data.DowJones">pyFTS.data.DowJones (module)</a>
</li>
<li><a href="pyFTS.data.html#module-pyFTS.data.Enrollments">pyFTS.data.Enrollments (module)</a>
</li>
<li><a href="pyFTS.data.html#module-pyFTS.data.Ethereum">pyFTS.data.Ethereum (module)</a>
</li>
<li><a href="pyFTS.data.html#module-pyFTS.data.EURGBP">pyFTS.data.EURGBP (module)</a>
</li>
<li><a href="pyFTS.data.html#module-pyFTS.data.EURUSD">pyFTS.data.EURUSD (module)</a>
</li>
<li><a href="pyFTS.data.html#module-pyFTS.data.GBPUSD">pyFTS.data.GBPUSD (module)</a>
</li>
<li><a href="pyFTS.data.html#module-pyFTS.data.henon">pyFTS.data.henon (module)</a>
</li>

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@ -199,16 +199,46 @@
<td>&#160;&#160;&#160;
<a href="pyFTS.data.html#module-pyFTS.data.artificial"><code class="xref">pyFTS.data.artificial</code></a></td><td>
<em></em></td></tr>
<tr class="cg-1">
<td></td>
<td>&#160;&#160;&#160;
<a href="pyFTS.data.html#module-pyFTS.data.Bitcoin"><code class="xref">pyFTS.data.Bitcoin</code></a></td><td>
<em></em></td></tr>
<tr class="cg-1">
<td></td>
<td>&#160;&#160;&#160;
<a href="pyFTS.data.html#module-pyFTS.data.common"><code class="xref">pyFTS.data.common</code></a></td><td>
<em></em></td></tr>
<tr class="cg-1">
<td></td>
<td>&#160;&#160;&#160;
<a href="pyFTS.data.html#module-pyFTS.data.DowJones"><code class="xref">pyFTS.data.DowJones</code></a></td><td>
<em></em></td></tr>
<tr class="cg-1">
<td></td>
<td>&#160;&#160;&#160;
<a href="pyFTS.data.html#module-pyFTS.data.Enrollments"><code class="xref">pyFTS.data.Enrollments</code></a></td><td>
<em></em></td></tr>
<tr class="cg-1">
<td></td>
<td>&#160;&#160;&#160;
<a href="pyFTS.data.html#module-pyFTS.data.Ethereum"><code class="xref">pyFTS.data.Ethereum</code></a></td><td>
<em></em></td></tr>
<tr class="cg-1">
<td></td>
<td>&#160;&#160;&#160;
<a href="pyFTS.data.html#module-pyFTS.data.EURGBP"><code class="xref">pyFTS.data.EURGBP</code></a></td><td>
<em></em></td></tr>
<tr class="cg-1">
<td></td>
<td>&#160;&#160;&#160;
<a href="pyFTS.data.html#module-pyFTS.data.EURUSD"><code class="xref">pyFTS.data.EURUSD</code></a></td><td>
<em></em></td></tr>
<tr class="cg-1">
<td></td>
<td>&#160;&#160;&#160;
<a href="pyFTS.data.html#module-pyFTS.data.GBPUSD"><code class="xref">pyFTS.data.GBPUSD</code></a></td><td>
<em></em></td></tr>
<tr class="cg-1">
<td></td>
<td>&#160;&#160;&#160;

321
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@ -54,21 +54,28 @@
<li><a class="reference internal" href="#">pyFTS.data package</a><ul>
<li><a class="reference internal" href="#module-pyFTS.data">Module contents</a></li>
<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="#datasets">Datasets</a></li>
<li><a class="reference internal" href="#module-pyFTS.data.AirPassengers">AirPassengers dataset</a></li>
<li><a class="reference internal" href="#module-pyFTS.data.Bitcoin">Bitcoin dataset</a></li>
<li><a class="reference internal" href="#module-pyFTS.data.DowJones">DowJones dataset</a></li>
<li><a class="reference internal" href="#module-pyFTS.data.Enrollments">Enrollments dataset</a></li>
<li><a class="reference internal" href="#module-pyFTS.data.Ethereum">Ethereum dataset</a></li>
<li><a class="reference internal" href="#module-pyFTS.data.EURGBP">EUR-GBP dataset</a></li>
<li><a class="reference internal" href="#module-pyFTS.data.EURUSD">EUR-USD dataset</a></li>
<li><a class="reference internal" href="#module-pyFTS.data.GBPUSD">GBP-USD dataset</a></li>
<li><a class="reference internal" href="#module-pyFTS.data.INMET">INMET dataset</a></li>
<li><a class="reference internal" href="#module-pyFTS.data.NASDAQ">NASDAQ module</a></li>
<li><a class="reference internal" href="#module-pyFTS.data.SONDA">SONDA dataset</a></li>
<li><a class="reference internal" href="#module-pyFTS.data.SP500">S&amp;P 500 dataset</a></li>
<li><a class="reference internal" href="#module-pyFTS.data.TAIEX">TAIEX dataset</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.henon">Henon chaotic time series</a></li>
<li><a class="reference internal" href="#module-pyFTS.data.logistic_map">Logistic_map chaotic time series</a></li>
<li><a class="reference internal" href="#module-pyFTS.data.lorentz">Lorentz chaotic time series</a></li>
<li><a class="reference internal" href="#module-pyFTS.data.mackey_glass">Mackey-Glass chaotic time series</a></li>
<li><a class="reference internal" href="#module-pyFTS.data.rossler">Rossler chaotic time series</a></li>
<li><a class="reference internal" href="#module-pyFTS.data.sunspots">Sunspots dataset</a></li>
</ul>
</li>
</ul>
@ -108,6 +115,8 @@
<div class="section" id="pyfts-data-package">
<h1>pyFTS.data package<a class="headerlink" href="#pyfts-data-package" title="Permalink to this headline"></a></h1>
<div class="toctree-wrapper compound">
</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>
@ -115,8 +124,38 @@
<div class="section" id="submodules">
<h2>Submodules<a class="headerlink" href="#submodules" title="Permalink to this headline"></a></h2>
</div>
<div class="section" id="module-pyFTS.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="datasets">
<h2>Datasets<a class="headerlink" href="#datasets" title="Permalink to this headline"></a></h2>
</div>
<div class="section" id="module-pyFTS.data.AirPassengers">
<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>
<span id="airpassengers-dataset"></span><h2>AirPassengers dataset<a class="headerlink" href="#module-pyFTS.data.AirPassengers" title="Permalink to this headline"></a></h2>
<p>Monthly totals of a airline passengers from USA, from January 1949 through December 1960.</p>
<p>Source: Hyndman, R.J., Time Series Data Library, <a class="reference external" href="http://www-personal.buseco.monash.edu.au/~hyndman/TSDL/">http://www-personal.buseco.monash.edu.au/~hyndman/TSDL/</a>.</p>
<dl class="function">
@ -147,9 +186,77 @@
</table>
</dd></dl>
</div>
<div class="section" id="module-pyFTS.data.Bitcoin">
<span id="bitcoin-dataset"></span><h2>Bitcoin dataset<a class="headerlink" href="#module-pyFTS.data.Bitcoin" title="Permalink to this headline"></a></h2>
<p>Bitcoin to USD quotations</p>
<p>Daily averaged index, by business day, from 2010 to 2018.</p>
<p>Source: <a class="reference external" href="https://finance.yahoo.com/quote/BTC-USD?p=BTC-USD">https://finance.yahoo.com/quote/BTC-USD?p=BTC-USD</a></p>
<dl class="function">
<dt id="pyFTS.data.Bitcoin.get_data">
<code class="descclassname">pyFTS.data.Bitcoin.</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/Bitcoin.html#get_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.Bitcoin.get_data" title="Permalink to this definition"></a></dt>
<dd><p>Get the 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.Bitcoin.get_dataframe">
<code class="descclassname">pyFTS.data.Bitcoin.</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/Bitcoin.html#get_dataframe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.Bitcoin.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.DowJones">
<span id="dowjones-dataset"></span><h2>DowJones dataset<a class="headerlink" href="#module-pyFTS.data.DowJones" title="Permalink to this headline"></a></h2>
<p>DJI - Dow Jones</p>
<p>Daily averaged index, by business day, from 1985 to 2017.</p>
<p>Source: <a class="reference external" href="https://finance.yahoo.com/quote/%5EGSPC/history?p=%5EGSPC">https://finance.yahoo.com/quote/%5EGSPC/history?p=%5EGSPC</a></p>
<dl class="function">
<dt id="pyFTS.data.DowJones.get_data">
<code class="descclassname">pyFTS.data.DowJones.</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/DowJones.html#get_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.DowJones.get_data" title="Permalink to this definition"></a></dt>
<dd><p>Get the 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.DowJones.get_dataframe">
<code class="descclassname">pyFTS.data.DowJones.</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/DowJones.html#get_dataframe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.DowJones.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.Enrollments">
<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>
<span id="enrollments-dataset"></span><h2>Enrollments dataset<a class="headerlink" href="#module-pyFTS.data.Enrollments" title="Permalink to this headline"></a></h2>
<p>Yearly University of Alabama enrollments from 1971 to 1992.</p>
<dl class="function">
<dt id="pyFTS.data.Enrollments.get_data">
@ -170,9 +277,142 @@
<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>
<dd></dd></dl>
</div>
<div class="section" id="module-pyFTS.data.Ethereum">
<span id="ethereum-dataset"></span><h2>Ethereum dataset<a class="headerlink" href="#module-pyFTS.data.Ethereum" title="Permalink to this headline"></a></h2>
<p>Ethereum to USD quotations</p>
<p>Daily averaged index, by business day, from 2016 to 2018.</p>
<p>Source: <a class="reference external" href="https://finance.yahoo.com/quote/ETH-USD?p=ETH-USD">https://finance.yahoo.com/quote/ETH-USD?p=ETH-USD</a></p>
<dl class="function">
<dt id="pyFTS.data.Ethereum.get_data">
<code class="descclassname">pyFTS.data.Ethereum.</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/Ethereum.html#get_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.Ethereum.get_data" title="Permalink to this definition"></a></dt>
<dd><p>Get the 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.Ethereum.get_dataframe">
<code class="descclassname">pyFTS.data.Ethereum.</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/Ethereum.html#get_dataframe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.Ethereum.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.EURGBP">
<span id="eur-gbp-dataset"></span><h2>EUR-GBP dataset<a class="headerlink" href="#module-pyFTS.data.EURGBP" title="Permalink to this headline"></a></h2>
<p>FOREX market EUR-GBP pair.</p>
<p>Daily averaged quotations, by business day, from 2016 to 2018.</p>
<dl class="function">
<dt id="pyFTS.data.EURGBP.get_data">
<code class="descclassname">pyFTS.data.EURGBP.</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/EURGBP.html#get_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.EURGBP.get_data" title="Permalink to this definition"></a></dt>
<dd><p>Get the 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.EURGBP.get_dataframe">
<code class="descclassname">pyFTS.data.EURGBP.</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/EURGBP.html#get_dataframe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.EURGBP.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.EURUSD">
<span id="eur-usd-dataset"></span><h2>EUR-USD dataset<a class="headerlink" href="#module-pyFTS.data.EURUSD" title="Permalink to this headline"></a></h2>
<p>FOREX market EUR-USD pair.</p>
<p>Daily averaged quotations, by business day, from 2016 to 2018.</p>
<dl class="function">
<dt id="pyFTS.data.EURUSD.get_data">
<code class="descclassname">pyFTS.data.EURUSD.</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/EURUSD.html#get_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.EURUSD.get_data" title="Permalink to this definition"></a></dt>
<dd><p>Get the 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.EURUSD.get_dataframe">
<code class="descclassname">pyFTS.data.EURUSD.</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/EURUSD.html#get_dataframe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.EURUSD.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.GBPUSD">
<span id="gbp-usd-dataset"></span><h2>GBP-USD dataset<a class="headerlink" href="#module-pyFTS.data.GBPUSD" title="Permalink to this headline"></a></h2>
<p>FOREX market GBP-USD pair.</p>
<p>Daily averaged quotations, by business day, from 2016 to 2018.</p>
<dl class="function">
<dt id="pyFTS.data.GBPUSD.get_data">
<code class="descclassname">pyFTS.data.GBPUSD.</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/GBPUSD.html#get_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.GBPUSD.get_data" title="Permalink to this definition"></a></dt>
<dd><p>Get the 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.GBPUSD.get_dataframe">
<code class="descclassname">pyFTS.data.GBPUSD.</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/GBPUSD.html#get_dataframe"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.data.GBPUSD.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.INMET">
<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>
<span id="inmet-dataset"></span><h2>INMET dataset<a class="headerlink" href="#module-pyFTS.data.INMET" title="Permalink to this headline"></a></h2>
<p>INMET - Instituto Nacional Meteorologia / Brasil</p>
<p>Belo Horizonte station, from 2000-01-01 to 31/12/2012</p>
<p>Source: <a class="reference external" href="http://www.inmet.gov.br">http://www.inmet.gov.br</a></p>
@ -192,7 +432,7 @@
</div>
<div class="section" id="module-pyFTS.data.NASDAQ">
<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>
<span id="nasdaq-module"></span><h2>NASDAQ module<a class="headerlink" href="#module-pyFTS.data.NASDAQ" title="Permalink to this headline"></a></h2>
<p>National Association of Securities Dealers Automated Quotations - Composite Index (NASDAQ IXIC)</p>
<p>Daily averaged index by business day, from 2000 to 2016.</p>
<p>Source: <a class="reference external" href="http://www.nasdaq.com/aspx/flashquotes.aspx?symbol=IXIC&amp;selected=IXIC">http://www.nasdaq.com/aspx/flashquotes.aspx?symbol=IXIC&amp;selected=IXIC</a></p>
@ -228,7 +468,7 @@
</div>
<div class="section" id="module-pyFTS.data.SONDA">
<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>
<span id="sonda-dataset"></span><h2>SONDA dataset<a class="headerlink" href="#module-pyFTS.data.SONDA" title="Permalink to this headline"></a></h2>
<p>SONDA - Sistema de Organização Nacional de Dados Ambientais, from INPE - Instituto Nacional de Pesquisas Espaciais, Brasil.</p>
<p>Brasilia station</p>
<p>Source: <a class="reference external" href="http://sonda.ccst.inpe.br/">http://sonda.ccst.inpe.br/</a></p>
@ -264,7 +504,7 @@
</div>
<div class="section" id="module-pyFTS.data.SP500">
<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>
<span id="s-p-500-dataset"></span><h2>S&amp;P 500 dataset<a class="headerlink" href="#module-pyFTS.data.SP500" title="Permalink to this headline"></a></h2>
<p>S&amp;P500 - Standard &amp; Poor’s 500</p>
<p>Daily averaged index, by business day, from 1950 to 2017.</p>
<p>Source: <a class="reference external" href="https://finance.yahoo.com/quote/%5EGSPC/history?p=%5EGSPC">https://finance.yahoo.com/quote/%5EGSPC/history?p=%5EGSPC</a></p>
@ -298,7 +538,7 @@
</div>
<div class="section" id="module-pyFTS.data.TAIEX">
<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>
<span id="taiex-dataset"></span><h2>TAIEX dataset<a class="headerlink" href="#module-pyFTS.data.TAIEX" title="Permalink to this headline"></a></h2>
<p>The Taiwan Stock Exchange Capitalization Weighted Stock Index (TAIEX)</p>
<p>Daily averaged index by business day, from 1995 to 2014.</p>
<p>Source: <a class="reference external" href="http://www.twse.com.tw/en/products/indices/Index_Series.php">http://www.twse.com.tw/en/products/indices/Index_Series.php</a></p>
@ -398,36 +638,9 @@
<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>
<span id="henon-chaotic-time-series"></span><h2>Henon chaotic time series<a class="headerlink" href="#module-pyFTS.data.henon" title="Permalink to this headline"></a></h2>
<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>
@ -474,7 +687,7 @@ dy/dt = x</p>
</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>
<span id="logistic-map-chaotic-time-series"></span><h2>Logistic_map chaotic time series<a class="headerlink" href="#module-pyFTS.data.logistic_map" title="Permalink to this headline"></a></h2>
<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>
@ -502,7 +715,7 @@ Nature. 261 (5560): 459–467. doi:10.1038/261459a0.</p>
</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>
<span id="lorentz-chaotic-time-series"></span><h2>Lorentz chaotic time series<a class="headerlink" href="#module-pyFTS.data.lorentz" title="Permalink to this headline"></a></h2>
<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&lt;0130:DNF&gt;2.0.CO;2</p>
<p>dx/dt = a(y -x)
@ -551,7 +764,7 @@ dz/dt = xy - cz</p>
</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>
<span id="mackey-glass-chaotic-time-series"></span><h2>Mackey-Glass chaotic time series<a class="headerlink" href="#module-pyFTS.data.mackey_glass" title="Permalink to this headline"></a></h2>
<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>
@ -581,7 +794,7 @@ Science, 197(4300):287-289.</p>
</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>
<span id="rossler-chaotic-time-series"></span><h2>Rossler chaotic time series<a class="headerlink" href="#module-pyFTS.data.rossler" title="Permalink to this headline"></a></h2>
<ol class="upperalpha simple" start="15">
<li><ol class="first upperalpha" start="5">
<li>Rössler, Phys. Lett. 57A, 397 (1976).</li>
@ -634,7 +847,7 @@ dz/dt = b + z( x - c )</p>
</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>
<span id="sunspots-dataset"></span><h2>Sunspots dataset<a class="headerlink" href="#module-pyFTS.data.sunspots" title="Permalink to this headline"></a></h2>
<p>Monthly sunspot numbers from 1749 to May 2016</p>
<p>Source: <a class="reference external" href="https://www.esrl.noaa.gov/psd/gcos_wgsp/Timeseries/SUNSPOT/">https://www.esrl.noaa.gov/psd/gcos_wgsp/Timeseries/SUNSPOT/</a></p>
<dl class="function">

35
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@ -129,21 +129,28 @@
<li class="toctree-l1"><a class="reference internal" href="pyFTS.data.html">pyFTS.data package</a><ul>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data">Module contents</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#submodules">Submodules</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.AirPassengers">pyFTS.data.AirPassengers module</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.Enrollments">pyFTS.data.Enrollments module</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.INMET">pyFTS.data.INMET module</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.NASDAQ">pyFTS.data.NASDAQ module</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.SONDA">pyFTS.data.SONDA module</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.SP500">pyFTS.data.SP500 module</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.TAIEX">pyFTS.data.TAIEX module</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.artificial">pyFTS.data.artificial module</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.common">pyFTS.data.common module</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.henon">pyFTS.data.henon module</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.logistic_map">pyFTS.data.logistic_map module</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.lorentz">pyFTS.data.lorentz module</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.mackey_glass">pyFTS.data.mackey_glass module</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.rossler">pyFTS.data.rossler module</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.sunspots">pyFTS.data.sunspots module</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#datasets">Datasets</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.AirPassengers">AirPassengers dataset</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.Bitcoin">Bitcoin dataset</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.DowJones">DowJones dataset</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.Enrollments">Enrollments dataset</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.Ethereum">Ethereum dataset</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.EURGBP">EUR-GBP dataset</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.EURUSD">EUR-USD dataset</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.GBPUSD">GBP-USD dataset</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.INMET">INMET dataset</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.NASDAQ">NASDAQ module</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.SONDA">SONDA dataset</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.SP500">S&amp;P 500 dataset</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.TAIEX">TAIEX dataset</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.artificial">pyFTS.data.artificial module</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.henon">Henon chaotic time series</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.logistic_map">Logistic_map chaotic time series</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.lorentz">Lorentz chaotic time series</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.mackey_glass">Mackey-Glass chaotic time series</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.rossler">Rossler chaotic time series</a></li>
<li class="toctree-l2"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.sunspots">Sunspots dataset</a></li>
</ul>
</li>
<li class="toctree-l1"><a class="reference internal" href="pyFTS.models.html">pyFTS.models package</a><ul>

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docs/pyFTS.data.rst
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@ -1,6 +1,10 @@
pyFTS.data package
==================
.. toctree::
:maxdepth: 3
:caption: Index:
Module contents
---------------
@ -8,11 +12,24 @@ Module contents
:members:
:undoc-members:
:show-inheritance:
Submodules
----------
pyFTS.data.AirPassengers module
pyFTS.data.common module
------------------------
.. automodule:: pyFTS.data.common
:members:
:undoc-members:
:show-inheritance:
Datasets
--------
AirPassengers dataset
-------------------------------
.. automodule:: pyFTS.data.AirPassengers
@ -20,15 +37,65 @@ pyFTS.data.AirPassengers module
:undoc-members:
:show-inheritance:
pyFTS.data.Enrollments module
Bitcoin dataset
-------------------------------
.. automodule:: pyFTS.data.Bitcoin
:members:
:undoc-members:
:show-inheritance:
DowJones dataset
-----------------------------
.. automodule:: pyFTS.data.DowJones
:members:
:undoc-members:
:show-inheritance:
Enrollments dataset
-----------------------------
.. automodule:: pyFTS.data.Enrollments
:members:
:undoc-members:
:show-inheritance:
Ethereum dataset
-----------------------------
pyFTS.data.INMET module
.. automodule:: pyFTS.data.Ethereum
:members:
:undoc-members:
:show-inheritance:
EUR-GBP dataset
-----------------------------
.. automodule:: pyFTS.data.EURGBP
:members:
:undoc-members:
:show-inheritance:
EUR-USD dataset
-----------------------------
.. automodule:: pyFTS.data.EURUSD
:members:
:undoc-members:
:show-inheritance:
GBP-USD dataset
-----------------------------
.. automodule:: pyFTS.data.GBPUSD
:members:
:undoc-members:
:show-inheritance:
INMET dataset
-----------------------
.. automodule:: pyFTS.data.INMET
@ -36,7 +103,7 @@ pyFTS.data.INMET module
:undoc-members:
:show-inheritance:
pyFTS.data.NASDAQ module
NASDAQ module
------------------------
.. automodule:: pyFTS.data.NASDAQ
@ -44,7 +111,7 @@ pyFTS.data.NASDAQ module
:undoc-members:
:show-inheritance:
pyFTS.data.SONDA module
SONDA dataset
-----------------------
.. automodule:: pyFTS.data.SONDA
@ -52,7 +119,7 @@ pyFTS.data.SONDA module
:undoc-members:
:show-inheritance:
pyFTS.data.SP500 module
S&P 500 dataset
-----------------------
.. automodule:: pyFTS.data.SP500
@ -60,7 +127,7 @@ pyFTS.data.SP500 module
:undoc-members:
:show-inheritance:
pyFTS.data.TAIEX module
TAIEX dataset
-----------------------
.. automodule:: pyFTS.data.TAIEX
@ -76,56 +143,48 @@ pyFTS.data.artificial module
:undoc-members:
:show-inheritance:
pyFTS.data.common module
------------------------
.. automodule:: pyFTS.data.common
:members:
:undoc-members:
:show-inheritance:
pyFTS.data.henon module
-----------------------
Henon chaotic time series
-------------------------
.. automodule:: pyFTS.data.henon
:members:
:undoc-members:
:show-inheritance:
pyFTS.data.logistic\_map module
-------------------------------
Logistic\_map chaotic time series
----------------------------------
.. automodule:: pyFTS.data.logistic_map
:members:
:undoc-members:
:show-inheritance:
pyFTS.data.lorentz module
-------------------------
Lorentz chaotic time series
---------------------------
.. automodule:: pyFTS.data.lorentz
:members:
:undoc-members:
:show-inheritance:
pyFTS.data.mackey\_glass module
-------------------------------
Mackey-Glass chaotic time series
--------------------------------
.. automodule:: pyFTS.data.mackey_glass
:members:
:undoc-members:
:show-inheritance:
pyFTS.data.rossler module
-------------------------
Rossler chaotic time series
---------------------------
.. automodule:: pyFTS.data.rossler
:members:
:undoc-members:
:show-inheritance:
pyFTS.data.sunspots module
--------------------------
Sunspots dataset
----------------
.. automodule:: pyFTS.data.sunspots
:members: