Documentation update

docs/build/html/_modules/index.html

@@ -111,6 +111,8 @@
 <li><a href="pyFTS/data/mackey_glass.html">pyFTS.data.mackey_glass</a></li>
 <li><a href="pyFTS/data/rossler.html">pyFTS.data.rossler</a></li>
 <li><a href="pyFTS/data/sunspots.html">pyFTS.data.sunspots</a></li>
+<li><a href="pyFTS/hyperparam/GridSearch.html">pyFTS.hyperparam.GridSearch</a></li>
+<li><a href="pyFTS/hyperparam/Util.html">pyFTS.hyperparam.Util</a></li>
 <li><a href="pyFTS/models/chen.html">pyFTS.models.chen</a></li>
 <li><a href="pyFTS/models/cheng.html">pyFTS.models.cheng</a></li>
 <li><a href="pyFTS/models/ensemble/ensemble.html">pyFTS.models.ensemble.ensemble</a></li>
@@ -121,10 +123,12 @@
 <li><a href="pyFTS/models/incremental/Retrainer.html">pyFTS.models.incremental.Retrainer</a></li>
 <li><a href="pyFTS/models/ismailefendi.html">pyFTS.models.ismailefendi</a></li>
 <li><a href="pyFTS/models/multivariate/FLR.html">pyFTS.models.multivariate.FLR</a></li>
+<li><a href="pyFTS/models/multivariate/cmvfts.html">pyFTS.models.multivariate.cmvfts</a></li>
 <li><a href="pyFTS/models/multivariate/common.html">pyFTS.models.multivariate.common</a></li>
 <li><a href="pyFTS/models/multivariate/flrg.html">pyFTS.models.multivariate.flrg</a></li>
 <li><a href="pyFTS/models/multivariate/mvfts.html">pyFTS.models.multivariate.mvfts</a></li>
 <li><a href="pyFTS/models/multivariate/variable.html">pyFTS.models.multivariate.variable</a></li>
+<li><a href="pyFTS/models/multivariate/wmvfts.html">pyFTS.models.multivariate.wmvfts</a></li>
 <li><a href="pyFTS/models/nonstationary/common.html">pyFTS.models.nonstationary.common</a></li>
 <li><a href="pyFTS/models/nonstationary/cvfts.html">pyFTS.models.nonstationary.cvfts</a></li>
 <li><a href="pyFTS/models/nonstationary/flrg.html">pyFTS.models.nonstationary.flrg</a></li>

docs/build/html/_modules/pyFTS/benchmarks/Measures.html

@@ -419,7 +419,10 @@
         <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">forecasts</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)):</span>
             <span class="n">forecasts</span> <span class="o">=</span> <span class="p">[</span><span class="n">forecasts</span><span class="p">]</span>
 
-        <span class="n">forecasts</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">forecasts</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
+        <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)</span> <span class="o">!=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span> <span class="o">-</span> <span class="n">model</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span>
+            <span class="n">forecasts</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">forecasts</span><span class="p">[:</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
+        <span class="k">else</span><span class="p">:</span>
+            <span class="n">forecasts</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">forecasts</span><span class="p">)</span>
 
         <span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">rmse</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">model</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>
         <span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">round</span><span class="p">(</span><span class="n">mape</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">model</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:],</span> <span class="n">forecasts</span><span class="p">),</span> <span class="mi">2</span><span class="p">))</span>

docs/build/html/_modules/pyFTS/benchmarks/benchmarks.html

@@ -93,6 +93,7 @@
 <span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">ProbabilityDistribution</span>
 <span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Transformations</span>
 <span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">song</span><span class="p">,</span> <span class="n">chen</span><span class="p">,</span> <span class="n">yu</span><span class="p">,</span> <span class="n">ismailefendi</span><span class="p">,</span> <span class="n">sadaei</span><span class="p">,</span> <span class="n">hofts</span><span class="p">,</span> <span class="n">pwfts</span><span class="p">,</span> <span class="n">ifts</span><span class="p">,</span> <span class="n">cheng</span><span class="p">,</span> <span class="n">hwang</span>
+<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="k">import</span> <span class="n">mvfts</span><span class="p">,</span> <span class="n">wmvfts</span><span class="p">,</span> <span class="n">cmvfts</span>
 <span class="kn">from</span> <span class="nn">pyFTS.models.ensemble</span> <span class="k">import</span> <span class="n">ensemble</span>
 <span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span><span class="p">,</span> <span class="n">naive</span><span class="p">,</span> <span class="n">arima</span><span class="p">,</span> <span class="n">ResidualAnalysis</span><span class="p">,</span> <span class="n">quantreg</span><span class="p">,</span> <span class="n">knn</span>
 <span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Util</span> <span class="k">as</span> <span class="n">bUtil</span>
@@ -131,10 +132,16 @@
 <div class="viewcode-block" id="get_point_methods"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.get_point_methods">[docs]</a><span class="k">def</span> <span class="nf">get_point_methods</span><span class="p">():</span>
     <span class="sd">&quot;&quot;&quot;Return all FTS methods for point forecasting&quot;&quot;&quot;</span>
     <span class="k">return</span> <span class="p">[</span><span class="n">song</span><span class="o">.</span><span class="n">ConventionalFTS</span><span class="p">,</span> <span class="n">chen</span><span class="o">.</span><span class="n">ConventionalFTS</span><span class="p">,</span> <span class="n">yu</span><span class="o">.</span><span class="n">WeightedFTS</span><span class="p">,</span> <span class="n">ismailefendi</span><span class="o">.</span><span class="n">ImprovedWeightedFTS</span><span class="p">,</span>
-            <span class="n">cheng</span><span class="o">.</span><span class="n">TrendWeightedFTS</span><span class="p">,</span> <span class="n">sadaei</span><span class="o">.</span><span class="n">ExponentialyWeightedFTS</span><span class="p">,</span> <span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">,</span> <span class="n">hwang</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">,</span>
+            <span class="n">cheng</span><span class="o">.</span><span class="n">TrendWeightedFTS</span><span class="p">,</span> <span class="n">sadaei</span><span class="o">.</span><span class="n">ExponentialyWeightedFTS</span><span class="p">,</span>
+            <span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">,</span> <span class="n">hofts</span><span class="o">.</span><span class="n">WeightedHighOrderFTS</span><span class="p">,</span> <span class="n">hwang</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">,</span>
             <span class="n">pwfts</span><span class="o">.</span><span class="n">ProbabilisticWeightedFTS</span><span class="p">]</span></div>
 
 
+<div class="viewcode-block" id="get_point_multivariate_methods"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.get_point_multivariate_methods">[docs]</a><span class="k">def</span> <span class="nf">get_point_multivariate_methods</span><span class="p">():</span>
+    <span class="sd">&quot;&quot;&quot;Return all multivariate FTS methods por point forecasting&quot;&quot;&quot;</span>
+    <span class="k">return</span> <span class="p">[</span><span class="n">mvfts</span><span class="o">.</span><span class="n">MVFTS</span><span class="p">,</span> <span class="n">wmvfts</span><span class="o">.</span><span class="n">WeightedMVFTS</span><span class="p">,</span> <span class="n">cmvfts</span><span class="o">.</span><span class="n">ClusteredMVFTS</span><span class="p">]</span></div>
+
+
 <div class="viewcode-block" id="get_benchmark_interval_methods"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.get_benchmark_interval_methods">[docs]</a><span class="k">def</span> <span class="nf">get_benchmark_interval_methods</span><span class="p">():</span>
     <span class="sd">&quot;&quot;&quot;Return all non FTS methods for point_to_interval forecasting&quot;&quot;&quot;</span>
     <span class="k">return</span> <span class="p">[</span> <span class="n">arima</span><span class="o">.</span><span class="n">ARIMA</span><span class="p">,</span> <span class="n">quantreg</span><span class="o">.</span><span class="n">QuantileRegression</span><span class="p">]</span></div>

docs/build/html/_modules/pyFTS/common/Composite.html

@@ -85,12 +85,14 @@
     <span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Composite Fuzzy Set</span>
 <span class="sd">    &quot;&quot;&quot;</span>
-    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">superset</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
+    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">superset</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
         <span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">        Create an empty composite fuzzy set</span>
 <span class="sd">        :param name: fuzzy set name</span>
 <span class="sd">        &quot;&quot;&quot;</span>
-        <span class="nb">super</span><span class="p">(</span><span class="n">FuzzySet</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="s1">&#39;composite&#39;</span><span class="p">)</span>
+        <span class="k">if</span> <span class="s1">&#39;type&#39;</span> <span class="ow">in</span> <span class="n">kwargs</span><span class="p">:</span>
+            <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">&#39;type&#39;</span><span class="p">)</span>
+        <span class="nb">super</span><span class="p">(</span><span class="n">FuzzySet</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="s1">&#39;composite&#39;</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">superset</span> <span class="o">=</span> <span class="n">superset</span>
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">superset</span><span class="p">:</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="p">[]</span>

docs/build/html/_modules/pyFTS/common/FuzzySet.html

@@ -274,10 +274,13 @@
     <span class="k">if</span> <span class="n">ordered_sets</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
         <span class="n">ordered_sets</span> <span class="o">=</span> <span class="n">set_ordered</span><span class="p">(</span><span class="n">fuzzy_sets</span><span class="p">)</span>
 
-    <span class="n">fs</span> <span class="o">=</span> <span class="p">[</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
+    <span class="k">try</span><span class="p">:</span>
-          <span class="k">for</span> <span class="n">ix</span> <span class="ow">in</span> <span class="n">__binary_search</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="n">fuzzy_sets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="p">)</span>
+        <span class="n">fs</span> <span class="o">=</span> <span class="p">[</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
-          <span class="k">if</span> <span class="n">fuzzy_sets</span><span class="p">[</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">ix</span><span class="p">]]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">inst</span><span class="p">)</span> <span class="o">&gt;</span> <span class="n">alpha_cut</span><span class="p">]</span>
+              <span class="k">for</span> <span class="n">ix</span> <span class="ow">in</span> <span class="n">__binary_search</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="n">fuzzy_sets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="p">)</span>
-    <span class="k">return</span> <span class="n">fs</span></div>
+              <span class="k">if</span> <span class="n">fuzzy_sets</span><span class="p">[</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">ix</span><span class="p">]]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">inst</span><span class="p">)</span> <span class="o">&gt;</span> <span class="n">alpha_cut</span><span class="p">]</span>
+        <span class="k">return</span> <span class="n">fs</span>
+    <span class="k">except</span> <span class="ne">Exception</span> <span class="k">as</span> <span class="n">ex</span><span class="p">:</span>
+        <span class="k">raise</span> <span class="n">ex</span></div>
 
 
 <div class="viewcode-block" id="get_maximum_membership_fuzzyset"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.FuzzySet.get_maximum_membership_fuzzyset">[docs]</a><span class="k">def</span> <span class="nf">get_maximum_membership_fuzzyset</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="n">fuzzy_sets</span><span class="p">,</span> <span class="n">ordered_sets</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>

docs/build/html/_modules/pyFTS/common/Util.html

@@ -307,7 +307,6 @@
     <span class="k">return</span> <span class="n">model</span></div>
 
 
-
 <div class="viewcode-block" id="distributed_train"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.distributed_train">[docs]</a><span class="k">def</span> <span class="nf">distributed_train</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">train_method</span><span class="p">,</span> <span class="n">nodes</span><span class="p">,</span> <span class="n">fts_method</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">num_batches</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span>
                       <span class="n">train_parameters</span><span class="o">=</span><span class="p">{},</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
     <span class="kn">import</span> <span class="nn">dispy</span><span class="o">,</span> <span class="nn">dispy.httpd</span><span class="o">,</span> <span class="nn">datetime</span>

docs/build/html/_modules/pyFTS/common/fts.html

@@ -168,6 +168,9 @@
 <span class="sd">        :keyword distributed: boolean, indicate if the forecasting procedure will be distributed in a dispy cluster</span>
 <span class="sd">        :keyword nodes: a list with the dispy cluster nodes addresses</span>
 <span class="sd">        :keyword explain: try to explain, step by step, the one-step-ahead point forecasting result given the input data.</span>
+<span class="sd">        :keyword generators: for multivariate methods on multi step ahead forecasting, generators is a dict where the keys</span>
+<span class="sd">                            are the variables names (except the target_variable) and the values are lambda functions that</span>
+<span class="sd">                            accept one value (the actual value of the variable) and return the next value.</span>
 
 <span class="sd">        :return: a numpy array with the forecasted data</span>
 <span class="sd">        &quot;&quot;&quot;</span>
@@ -261,10 +264,12 @@
 
 <span class="sd">        :param data: time series data with the minimal length equal to the max_lag of the model</span>
 <span class="sd">        :param steps: the number of steps ahead to forecast</span>
-<span class="sd">        :param kwargs: model specific parameters</span>
+<span class="sd">        :keyword start: in the multi step forecasting, the index of the data where to start forecasting</span>
 <span class="sd">        :return: a list with the forecasted values</span>
 <span class="sd">        &quot;&quot;&quot;</span>
 
+
+
         <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">):</span>
             <span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>
 

docs/build/html/_modules/pyFTS/hyperparam/GridSearch.html

@@ -0,0 +1,227 @@
+
+
+<!doctype html>
+
+<html xmlns="http://www.w3.org/1999/xhtml">
+  <head>
+    <meta http-equiv="X-UA-Compatible" content="IE=Edge" />
+    <meta http-equiv="Content-Type" content="text/html; charset=utf-8" /><script type="text/javascript">
+
+      var _gaq = _gaq || [];
+      _gaq.push(['_setAccount', 'UA-55120145-3']);
+      _gaq.push(['_trackPageview']);
+
+      (function() {
+        var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
+        ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
+        var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
+      })();
+    </script>
+    <title>pyFTS.hyperparam.GridSearch &#8212; pyFTS 1.2.3 documentation</title>
+    <link rel="stylesheet" href="../../../_static/bizstyle.css" type="text/css" />
+    <link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
+    <script type="text/javascript" src="../../../_static/documentation_options.js"></script>
+    <script type="text/javascript" src="../../../_static/jquery.js"></script>
+    <script type="text/javascript" src="../../../_static/underscore.js"></script>
+    <script type="text/javascript" src="../../../_static/doctools.js"></script>
+    <script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script>
+    <script type="text/javascript" src="../../../_static/bizstyle.js"></script>
+    <link rel="index" title="Index" href="../../../genindex.html" />
+    <link rel="search" title="Search" href="../../../search.html" />
+    <meta name="viewport" content="width=device-width,initial-scale=1.0">
+    <!--[if lt IE 9]>
+    <script type="text/javascript" src="_static/css3-mediaqueries.js"></script>
+    <![endif]-->
+  </head><body>
+    <div class="related" role="navigation" aria-label="related navigation">
+      <h3>Navigation</h3>
+      <ul>
+        <li class="right" style="margin-right: 10px">
+          <a href="../../../genindex.html" title="General Index"
+             accesskey="I">index</a></li>
+        <li class="right" >
+          <a href="../../../py-modindex.html" title="Python Module Index"
+             >modules</a> |</li>
+        <li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.2.3 documentation</a> &#187;</li>
+          <li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li> 
+      </ul>
+    </div>
+      <div class="sphinxsidebar" role="navigation" aria-label="main navigation">
+        <div class="sphinxsidebarwrapper">
+            <p class="logo"><a href="../../../index.html">
+              <img class="logo" src="../../../_static/logo_heading2.png" alt="Logo"/>
+            </a></p>
+<div id="searchbox" style="display: none" role="search">
+  <h3>Quick search</h3>
+    <div class="searchformwrapper">
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+  <h1>Source code for pyFTS.hyperparam.GridSearch</h1><div class="highlight"><pre>
+<span></span>
+<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Util</span><span class="p">,</span> <span class="n">Membership</span>
+<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span>
+<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span>
+<span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span>
+<span class="kn">from</span> <span class="nn">pyFTS.hyperparam</span> <span class="k">import</span> <span class="n">Util</span> <span class="k">as</span> <span class="n">hUtil</span>
+<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="kn">import</span> <span class="nn">dispy</span>
+<span class="kn">from</span> <span class="nn">itertools</span> <span class="k">import</span> <span class="n">product</span>
+
+
+<div class="viewcode-block" id="dict_individual"><a class="viewcode-back" href="../../../pyFTS.hyperparam.html#pyFTS.hyperparam.GridSearch.dict_individual">[docs]</a><span class="k">def</span> <span class="nf">dict_individual</span><span class="p">(</span><span class="n">mf</span><span class="p">,</span> <span class="n">partitioner</span><span class="p">,</span> <span class="n">partitions</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="n">lags</span><span class="p">,</span> <span class="n">alpha_cut</span><span class="p">):</span>
+    <span class="k">return</span> <span class="p">{</span>
+        <span class="s1">&#39;mf&#39;</span><span class="p">:</span> <span class="n">mf</span><span class="p">,</span>
+        <span class="s1">&#39;partitioner&#39;</span><span class="p">:</span> <span class="n">partitioner</span><span class="p">,</span>
+        <span class="s1">&#39;npart&#39;</span><span class="p">:</span> <span class="n">partitions</span><span class="p">,</span>
+        <span class="s1">&#39;alpha&#39;</span><span class="p">:</span> <span class="n">alpha_cut</span><span class="p">,</span>
+        <span class="s1">&#39;order&#39;</span><span class="p">:</span> <span class="n">order</span><span class="p">,</span>
+        <span class="s1">&#39;lags&#39;</span><span class="p">:</span> <span class="n">lags</span>
+    <span class="p">}</span></div>
+
+
+<div class="viewcode-block" id="metodo_cluster"><a class="viewcode-back" href="../../../pyFTS.hyperparam.html#pyFTS.hyperparam.GridSearch.metodo_cluster">[docs]</a><span class="k">def</span> <span class="nf">metodo_cluster</span><span class="p">(</span><span class="n">individual</span><span class="p">,</span> <span class="n">train</span><span class="p">,</span> <span class="n">test</span><span class="p">):</span>
+    <span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Util</span><span class="p">,</span> <span class="n">Membership</span>
+    <span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span>
+    <span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span><span class="p">,</span> <span class="n">Entropy</span>
+    <span class="kn">from</span> <span class="nn">pyFTS.benchmarks</span> <span class="k">import</span> <span class="n">Measures</span>
+
+    <span class="k">if</span> <span class="n">individual</span><span class="p">[</span><span class="s1">&#39;mf&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
+        <span class="n">mf</span> <span class="o">=</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span>
+    <span class="k">elif</span> <span class="n">individual</span><span class="p">[</span><span class="s1">&#39;mf&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span>
+        <span class="n">mf</span> <span class="o">=</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span>
+    <span class="k">elif</span> <span class="n">individual</span><span class="p">[</span><span class="s1">&#39;mf&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">3</span> <span class="ow">and</span> <span class="n">individual</span><span class="p">[</span><span class="s1">&#39;partitioner&#39;</span><span class="p">]</span> <span class="o">!=</span> <span class="mi">2</span><span class="p">:</span>
+        <span class="n">mf</span> <span class="o">=</span> <span class="n">Membership</span><span class="o">.</span><span class="n">gaussmf</span>
+    <span class="k">else</span><span class="p">:</span>
+        <span class="n">mf</span> <span class="o">=</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span>
+
+    <span class="k">if</span> <span class="n">individual</span><span class="p">[</span><span class="s1">&#39;partitioner&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
+        <span class="n">partitioner</span> <span class="o">=</span> <span class="n">Grid</span><span class="o">.</span><span class="n">GridPartitioner</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">train</span><span class="p">,</span> <span class="n">npart</span><span class="o">=</span><span class="n">individual</span><span class="p">[</span><span class="s1">&#39;npart&#39;</span><span class="p">],</span> <span class="n">func</span><span class="o">=</span><span class="n">mf</span><span class="p">)</span>
+    <span class="k">elif</span> <span class="n">individual</span><span class="p">[</span><span class="s1">&#39;partitioner&#39;</span><span class="p">]</span> <span class="o">==</span> <span class="mi">2</span><span class="p">:</span>
+        <span class="n">npart</span> <span class="o">=</span> <span class="n">individual</span><span class="p">[</span><span class="s1">&#39;npart&#39;</span><span class="p">]</span> <span class="k">if</span> <span class="n">individual</span><span class="p">[</span><span class="s1">&#39;npart&#39;</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">10</span> <span class="k">else</span> <span class="mi">10</span>
+        <span class="n">partitioner</span> <span class="o">=</span> <span class="n">Entropy</span><span class="o">.</span><span class="n">EntropyPartitioner</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">train</span><span class="p">,</span> <span class="n">npart</span><span class="o">=</span><span class="n">npart</span><span class="p">,</span> <span class="n">func</span><span class="o">=</span><span class="n">mf</span><span class="p">)</span>
+
+
+    <span class="n">model</span> <span class="o">=</span> <span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">(</span><span class="n">partitioner</span><span class="o">=</span><span class="n">partitioner</span><span class="p">,</span>
+                               <span class="n">lags</span><span class="o">=</span><span class="n">individual</span><span class="p">[</span><span class="s1">&#39;lags&#39;</span><span class="p">],</span>
+                               <span class="n">alpha_cut</span><span class="o">=</span><span class="n">individual</span><span class="p">[</span><span class="s1">&#39;alpha&#39;</span><span class="p">],</span>
+                               <span class="n">order</span><span class="o">=</span><span class="n">individual</span><span class="p">[</span><span class="s1">&#39;order&#39;</span><span class="p">])</span>
+
+    <span class="n">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">train</span><span class="p">)</span>
+
+    <span class="n">rmse</span><span class="p">,</span> <span class="n">mape</span><span class="p">,</span> <span class="n">u</span> <span class="o">=</span> <span class="n">Measures</span><span class="o">.</span><span class="n">get_point_statistics</span><span class="p">(</span><span class="n">test</span><span class="p">,</span> <span class="n">model</span><span class="p">)</span>
+
+    <span class="k">return</span> <span class="n">individual</span><span class="p">,</span> <span class="n">rmse</span></div>
+
+
+<div class="viewcode-block" id="execute"><a class="viewcode-back" href="../../../pyFTS.hyperparam.html#pyFTS.hyperparam.GridSearch.execute">[docs]</a><span class="k">def</span> <span class="nf">execute</span><span class="p">(</span><span class="n">hyperparams</span><span class="p">,</span> <span class="n">datasetname</span><span class="p">,</span> <span class="n">train</span><span class="p">,</span> <span class="n">test</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
+
+    <span class="n">nodes</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;nodes&#39;</span><span class="p">,[</span><span class="s1">&#39;127.0.0.1&#39;</span><span class="p">])</span>
+
+    <span class="n">individuals</span> <span class="o">=</span> <span class="p">[]</span>
+
+    <span class="k">if</span> <span class="s1">&#39;lags&#39;</span> <span class="ow">in</span> <span class="n">hyperparams</span><span class="p">:</span>
+        <span class="n">lags</span> <span class="o">=</span> <span class="n">hyperparams</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">&#39;lags&#39;</span><span class="p">)</span>
+    <span class="k">else</span><span class="p">:</span>
+        <span class="n">lags</span> <span class="o">=</span> <span class="p">[</span><span class="n">k</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">50</span><span class="p">)]</span>
+
+    <span class="n">keys_sorted</span> <span class="o">=</span> <span class="p">[</span><span class="n">k</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">hyperparams</span><span class="o">.</span><span class="n">keys</span><span class="p">())]</span>
+
+    <span class="n">index</span> <span class="o">=</span> <span class="p">{}</span>
+    <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">keys_sorted</span><span class="p">)):</span>
+        <span class="n">index</span><span class="p">[</span><span class="n">keys_sorted</span><span class="p">[</span><span class="n">k</span><span class="p">]]</span> <span class="o">=</span> <span class="n">k</span>
+
+    <span class="n">hp_values</span> <span class="o">=</span> <span class="p">[</span>
+        <span class="p">[</span><span class="n">v</span> <span class="k">for</span> <span class="n">v</span> <span class="ow">in</span> <span class="n">hyperparams</span><span class="p">[</span><span class="n">hp</span><span class="p">]]</span>
+        <span class="k">for</span> <span class="n">hp</span> <span class="ow">in</span> <span class="n">keys_sorted</span>
+    <span class="p">]</span>
+
+    <span class="k">for</span> <span class="n">instance</span> <span class="ow">in</span> <span class="n">product</span><span class="p">(</span><span class="o">*</span><span class="n">hp_values</span><span class="p">):</span>
+        <span class="n">partitions</span> <span class="o">=</span> <span class="n">instance</span><span class="p">[</span><span class="n">index</span><span class="p">[</span><span class="s1">&#39;partitions&#39;</span><span class="p">]]</span>
+        <span class="n">partitioner</span> <span class="o">=</span> <span class="n">instance</span><span class="p">[</span><span class="n">index</span><span class="p">[</span><span class="s1">&#39;partitioner&#39;</span><span class="p">]]</span>
+        <span class="n">mf</span> <span class="o">=</span> <span class="n">instance</span><span class="p">[</span><span class="n">index</span><span class="p">[</span><span class="s1">&#39;mf&#39;</span><span class="p">]]</span>
+        <span class="n">alpha_cut</span> <span class="o">=</span> <span class="n">instance</span><span class="p">[</span><span class="n">index</span><span class="p">[</span><span class="s1">&#39;alpha&#39;</span><span class="p">]]</span>
+        <span class="n">order</span> <span class="o">=</span> <span class="n">instance</span><span class="p">[</span><span class="n">index</span><span class="p">[</span><span class="s1">&#39;order&#39;</span><span class="p">]]</span>
+        <span class="k">for</span> <span class="n">lag1</span> <span class="ow">in</span> <span class="n">lags</span><span class="p">:</span> <span class="c1"># o é o lag1</span>
+            <span class="n">_lags</span> <span class="o">=</span> <span class="p">[</span><span class="n">lag1</span><span class="p">]</span>
+            <span class="k">if</span> <span class="n">order</span> <span class="o">&gt;</span> <span class="mi">1</span><span class="p">:</span>
+                <span class="k">for</span> <span class="n">lag2</span> <span class="ow">in</span> <span class="n">lags</span><span class="p">:</span>  <span class="c1"># o é o lag1</span>
+                    <span class="n">_lags2</span> <span class="o">=</span> <span class="p">[</span><span class="n">lag1</span><span class="p">,</span> <span class="n">lag1</span><span class="o">+</span><span class="n">lag2</span><span class="p">]</span>
+                    <span class="k">if</span> <span class="n">order</span> <span class="o">&gt;</span> <span class="mi">2</span><span class="p">:</span>
+                        <span class="k">for</span> <span class="n">lag3</span> <span class="ow">in</span> <span class="n">lags</span><span class="p">:</span>  <span class="c1"># o é o lag1</span>
+                            <span class="n">_lags3</span> <span class="o">=</span> <span class="p">[</span><span class="n">lag1</span><span class="p">,</span> <span class="n">lag1</span> <span class="o">+</span> <span class="n">lag2</span><span class="p">,</span> <span class="n">lag1</span> <span class="o">+</span> <span class="n">lag2</span><span class="o">+</span><span class="n">lag3</span> <span class="p">]</span>
+                            <span class="n">individuals</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">dict_individual</span><span class="p">(</span><span class="n">mf</span><span class="p">,</span> <span class="n">partitioner</span><span class="p">,</span> <span class="n">partitions</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="n">_lags3</span><span class="p">,</span> <span class="n">alpha_cut</span><span class="p">))</span>
+                    <span class="k">else</span><span class="p">:</span>
+                        <span class="n">individuals</span><span class="o">.</span><span class="n">append</span><span class="p">(</span>
+                            <span class="n">dict_individual</span><span class="p">(</span><span class="n">mf</span><span class="p">,</span> <span class="n">partitioner</span><span class="p">,</span> <span class="n">partitions</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="n">_lags2</span><span class="p">,</span> <span class="n">alpha_cut</span><span class="p">))</span>
+            <span class="k">else</span><span class="p">:</span>
+                <span class="n">individuals</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">dict_individual</span><span class="p">(</span><span class="n">mf</span><span class="p">,</span> <span class="n">partitioner</span><span class="p">,</span> <span class="n">partitions</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="n">_lags</span><span class="p">,</span> <span class="n">alpha_cut</span><span class="p">))</span>
+
+
+    <span class="n">cluster</span><span class="p">,</span> <span class="n">http_server</span> <span class="o">=</span> <span class="n">Util</span><span class="o">.</span><span class="n">start_dispy_cluster</span><span class="p">(</span><span class="n">metodo_cluster</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="n">nodes</span><span class="p">)</span>
+
+    <span class="n">jobs</span> <span class="o">=</span> <span class="p">[]</span>
+
+    <span class="k">for</span> <span class="n">ind</span> <span class="ow">in</span> <span class="n">individuals</span><span class="p">:</span>
+        <span class="n">job</span> <span class="o">=</span> <span class="n">cluster</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">ind</span><span class="p">,</span> <span class="n">train</span><span class="p">,</span> <span class="n">test</span><span class="p">)</span>
+        <span class="n">jobs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">job</span><span class="p">)</span>
+
+
+    <span class="n">conn</span> <span class="o">=</span> <span class="n">hUtil</span><span class="o">.</span><span class="n">open_hyperparam_db</span><span class="p">(</span><span class="s1">&#39;hyperparam.db&#39;</span><span class="p">)</span>
+
+    <span class="k">for</span> <span class="n">job</span> <span class="ow">in</span> <span class="n">jobs</span><span class="p">:</span>
+        <span class="n">result</span><span class="p">,</span> <span class="n">rmse</span> <span class="o">=</span> <span class="n">job</span><span class="p">()</span>
+        <span class="k">if</span> <span class="n">job</span><span class="o">.</span><span class="n">status</span> <span class="o">==</span> <span class="n">dispy</span><span class="o">.</span><span class="n">DispyJob</span><span class="o">.</span><span class="n">Finished</span> <span class="ow">and</span> <span class="n">result</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="nb">print</span><span class="p">(</span><span class="n">result</span><span class="p">)</span>
+
+            <span class="n">record</span> <span class="o">=</span> <span class="p">(</span><span class="n">datasetname</span><span class="p">,</span> <span class="s1">&#39;GridSearch&#39;</span><span class="p">,</span> <span class="s1">&#39;HOFTS&#39;</span><span class="p">,</span> <span class="kc">None</span><span class="p">,</span> <span class="n">result</span><span class="p">[</span><span class="s1">&#39;mf&#39;</span><span class="p">],</span>
+                      <span class="n">result</span><span class="p">[</span><span class="s1">&#39;order&#39;</span><span class="p">],</span> <span class="n">result</span><span class="p">[</span><span class="s1">&#39;partitioner&#39;</span><span class="p">],</span> <span class="n">result</span><span class="p">[</span><span class="s1">&#39;npart&#39;</span><span class="p">],</span>
+                      <span class="n">result</span><span class="p">[</span><span class="s1">&#39;alpha&#39;</span><span class="p">],</span> <span class="nb">str</span><span class="p">(</span><span class="n">result</span><span class="p">[</span><span class="s1">&#39;lags&#39;</span><span class="p">]),</span> <span class="s1">&#39;rmse&#39;</span><span class="p">,</span> <span class="n">rmse</span><span class="p">)</span>
+
+            <span class="n">hUtil</span><span class="o">.</span><span class="n">insert_hyperparam</span><span class="p">(</span><span class="n">record</span><span class="p">,</span> <span class="n">conn</span><span class="p">)</span>
+
+        <span class="k">else</span><span class="p">:</span>
+            <span class="nb">print</span><span class="p">(</span><span class="n">job</span><span class="o">.</span><span class="n">exception</span><span class="p">)</span>
+            <span class="nb">print</span><span class="p">(</span><span class="n">job</span><span class="o">.</span><span class="n">stdout</span><span class="p">)</span>
+
+    <span class="n">Util</span><span class="o">.</span><span class="n">stop_dispy_cluster</span><span class="p">(</span><span class="n">cluster</span><span class="p">,</span> <span class="n">http_server</span><span class="p">)</span></div>
+</pre></div>
+
+          </div>
+        </div>
+      </div>
+      <div class="clearer"></div>
+    </div>
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+        <li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.2.3 documentation</a> &#187;</li>
+          <li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li> 
+      </ul>
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+    <div class="footer" role="contentinfo">
+        &#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
+      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 1.7.2.
+    </div>
+  </body>
+</html>

docs/build/html/_modules/pyFTS/hyperparam/Util.html

@@ -0,0 +1,169 @@
+
+
+<!doctype html>
+
+<html xmlns="http://www.w3.org/1999/xhtml">
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+    <meta http-equiv="X-UA-Compatible" content="IE=Edge" />
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+    <title>pyFTS.hyperparam.Util &#8212; pyFTS 1.2.3 documentation</title>
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+            
+  <h1>Source code for pyFTS.hyperparam.Util</h1><div class="highlight"><pre>
+<span></span><span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">Common facilities for hyperparameter tunning</span>
+<span class="sd">&quot;&quot;&quot;</span>
+
+<span class="kn">import</span> <span class="nn">sqlite3</span>
+
+<div class="viewcode-block" id="open_hyperparam_db"><a class="viewcode-back" href="../../../pyFTS.hyperparam.html#pyFTS.hyperparam.Util.open_hyperparam_db">[docs]</a><span class="k">def</span> <span class="nf">open_hyperparam_db</span><span class="p">(</span><span class="n">name</span><span class="p">):</span>
+    <span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Open a connection with a Sqlite database designed to store benchmark results.</span>
+
+<span class="sd">    :param name: database filenem</span>
+<span class="sd">    :return: a sqlite3 database connection</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+    <span class="n">conn</span> <span class="o">=</span> <span class="n">sqlite3</span><span class="o">.</span><span class="n">connect</span><span class="p">(</span><span class="n">name</span><span class="p">)</span>
+
+    <span class="c1">#performance optimizations</span>
+    <span class="n">conn</span><span class="o">.</span><span class="n">execute</span><span class="p">(</span><span class="s2">&quot;PRAGMA journal_mode = WAL&quot;</span><span class="p">)</span>
+    <span class="n">conn</span><span class="o">.</span><span class="n">execute</span><span class="p">(</span><span class="s2">&quot;PRAGMA synchronous = NORMAL&quot;</span><span class="p">)</span>
+
+    <span class="n">create_hyperparam_tables</span><span class="p">(</span><span class="n">conn</span><span class="p">)</span>
+    <span class="k">return</span> <span class="n">conn</span></div>
+
+
+<div class="viewcode-block" id="create_hyperparam_tables"><a class="viewcode-back" href="../../../pyFTS.hyperparam.html#pyFTS.hyperparam.Util.create_hyperparam_tables">[docs]</a><span class="k">def</span> <span class="nf">create_hyperparam_tables</span><span class="p">(</span><span class="n">conn</span><span class="p">):</span>
+    <span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Create a sqlite3 table designed to store benchmark results.</span>
+
+<span class="sd">    :param conn: a sqlite3 database connection</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+    <span class="n">c</span> <span class="o">=</span> <span class="n">conn</span><span class="o">.</span><span class="n">cursor</span><span class="p">()</span>
+
+    <span class="n">c</span><span class="o">.</span><span class="n">execute</span><span class="p">(</span><span class="s1">&#39;&#39;&#39;CREATE TABLE if not exists hyperparam(</span>
+<span class="s1">                 ID integer primary key, Date int, Dataset text, Tag text, </span>
+<span class="s1">                 Model text, Transformation text, mf text, &#39;Order&#39; int, </span>
+<span class="s1">                 Partitioner text, Partitions int, alpha real, lags text, </span>
+<span class="s1">                 Measure text, Value real)&#39;&#39;&#39;</span><span class="p">)</span>
+
+    <span class="n">conn</span><span class="o">.</span><span class="n">commit</span><span class="p">()</span></div>
+
+
+<div class="viewcode-block" id="insert_hyperparam"><a class="viewcode-back" href="../../../pyFTS.hyperparam.html#pyFTS.hyperparam.Util.insert_hyperparam">[docs]</a><span class="k">def</span> <span class="nf">insert_hyperparam</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">conn</span><span class="p">):</span>
+    <span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Insert benchmark data on database</span>
+
+<span class="sd">    :param data: a tuple with the benchmark data with format:</span>
+
+<span class="sd">    Dataset: Identify on which dataset the dataset was performed</span>
+<span class="sd">    Tag: a user defined word that indentify a benchmark set</span>
+<span class="sd">    Model: FTS model</span>
+<span class="sd">    Transformation: The name of data transformation, if one was used</span>
+<span class="sd">    mf: membership function</span>
+<span class="sd">    Order: the order of the FTS method</span>
+<span class="sd">    Partitioner: UoD partitioning scheme</span>
+<span class="sd">    Partitions: Number of partitions</span>
+<span class="sd">    alpha: alpha cut</span>
+<span class="sd">    lags: lags</span>
+<span class="sd">    Measure: accuracy measure</span>
+<span class="sd">    Value: the measure value</span>
+
+<span class="sd">    :param conn: a sqlite3 database connection</span>
+<span class="sd">    :return:</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+    <span class="n">c</span> <span class="o">=</span> <span class="n">conn</span><span class="o">.</span><span class="n">cursor</span><span class="p">()</span>
+
+    <span class="n">c</span><span class="o">.</span><span class="n">execute</span><span class="p">(</span><span class="s2">&quot;INSERT INTO hyperparam(Date, Dataset, Tag, Model, &quot;</span>
+              <span class="o">+</span> <span class="s2">&quot;Transformation, mf, &#39;Order&#39;, Partitioner, Partitions, &quot;</span>
+              <span class="o">+</span> <span class="s2">&quot;alpha, lags, Measure, Value) &quot;</span>
+              <span class="o">+</span> <span class="s2">&quot;VALUES(datetime(&#39;now&#39;),?,?,?,?,?,?,?,?,?,?,?,?)&quot;</span><span class="p">,</span> <span class="n">data</span><span class="p">)</span>
+    <span class="n">conn</span><span class="o">.</span><span class="n">commit</span><span class="p">()</span></div>
+</pre></div>
+
+          </div>
+        </div>
+      </div>
+      <div class="clearer"></div>
+    </div>
+    <div class="related" role="navigation" aria-label="related navigation">
+      <h3>Navigation</h3>
+      <ul>
+        <li class="right" style="margin-right: 10px">
+          <a href="../../../genindex.html" title="General Index"
+             >index</a></li>
+        <li class="right" >
+          <a href="../../../py-modindex.html" title="Python Module Index"
+             >modules</a> |</li>
+        <li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.2.3 documentation</a> &#187;</li>
+          <li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li> 
+      </ul>
+    </div>
+    <div class="footer" role="contentinfo">
+        &#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
+      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 1.7.2.
+    </div>
+  </body>
+</html>

docs/build/html/_modules/pyFTS/models/hofts.html

@@ -110,6 +110,48 @@
         <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
 
 
+<div class="viewcode-block" id="WeightedHighOrderFLRG"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFLRG">[docs]</a><span class="k">class</span> <span class="nc">WeightedHighOrderFLRG</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">):</span>
+    <span class="sd">&quot;&quot;&quot;Weighted High Order Fuzzy Logical Relationship Group&quot;&quot;&quot;</span>
+
+    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
+        <span class="nb">super</span><span class="p">(</span><span class="n">WeightedHighOrderFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="p">[]</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">{}</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="o">=</span> <span class="mf">0.0</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">strlhs</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="o">=</span> <span class="kc">None</span>
+
+<div class="viewcode-block" id="WeightedHighOrderFLRG.append_rhs"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFLRG.append_rhs">[docs]</a>    <span class="k">def</span> <span class="nf">append_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">fset</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
+        <span class="k">if</span> <span class="n">fset</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">:</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">fset</span><span class="p">]</span> <span class="o">=</span> <span class="mf">1.0</span>
+        <span class="k">else</span><span class="p">:</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">fset</span><span class="p">]</span> <span class="o">+=</span> <span class="mf">1.0</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="o">+=</span> <span class="mf">1.0</span></div>
+
+<div class="viewcode-block" id="WeightedHighOrderFLRG.append_lhs"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFLRG.append_lhs">[docs]</a>    <span class="k">def</span> <span class="nf">append_lhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">c</span><span class="p">):</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">c</span><span class="p">)</span></div>
+
+<div class="viewcode-block" id="WeightedHighOrderFLRG.weights"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFLRG.weights">[docs]</a>    <span class="k">def</span> <span class="nf">weights</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
+        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()])</span>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">w</span></div>
+
+<div class="viewcode-block" id="WeightedHighOrderFLRG.get_midpoint"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFLRG.get_midpoint">[docs]</a>    <span class="k">def</span> <span class="nf">get_midpoint</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
+        <span class="n">mp</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">sets</span><span class="p">[</span><span class="n">c</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span> <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()])</span>
+        <span class="k">return</span> <span class="n">mp</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">weights</span><span class="p">())</span></div>
+
+    <span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
+        <span class="n">_str</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
+        <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
+            <span class="n">_str</span> <span class="o">+=</span> <span class="s2">&quot;, &quot;</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">_str</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="k">else</span> <span class="s2">&quot;&quot;</span>
+            <span class="n">_str</span> <span class="o">+=</span> <span class="n">k</span> <span class="o">+</span> <span class="s2">&quot; (&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">count</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span> <span class="o">+</span> <span class="s2">&quot;)&quot;</span>
+
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="o">+</span> <span class="s2">&quot; -&gt; &quot;</span> <span class="o">+</span> <span class="n">_str</span>
+
+    <span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
+        <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div>
+
+
 <div class="viewcode-block" id="HighOrderFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.HighOrderFTS">[docs]</a><span class="k">class</span> <span class="nc">HighOrderFTS</span><span class="p">(</span><span class="n">fts</span><span class="o">.</span><span class="n">FTS</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;Conventional High Order Fuzzy Time Series&quot;&quot;&quot;</span>
     <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
@@ -137,13 +179,19 @@
             <span class="bp">self</span><span class="o">.</span><span class="n">lags</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="o">+</span><span class="mi">1</span><span class="p">)</span></div>
 
 <div class="viewcode-block" id="HighOrderFTS.generate_lhs_flrg"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.HighOrderFTS.generate_lhs_flrg">[docs]</a>    <span class="k">def</span> <span class="nf">generate_lhs_flrg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sample</span><span class="p">,</span> <span class="n">explain</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
+
+        <span class="n">nsample</span> <span class="o">=</span> <span class="p">[</span><span class="n">FuzzySet</span><span class="o">.</span><span class="n">fuzzyfy</span><span class="p">(</span><span class="n">k</span><span class="p">,</span> <span class="n">partitioner</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;sets&quot;</span><span class="p">,</span> <span class="n">alpha_cut</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">alpha_cut</span><span class="p">)</span>
+                   <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">sample</span><span class="p">]</span>
+
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrg_fuzzyfied</span><span class="p">(</span><span class="n">nsample</span><span class="p">,</span> <span class="n">explain</span><span class="p">)</span></div>
+
+<div class="viewcode-block" id="HighOrderFTS.generate_lhs_flrg_fuzzyfied"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.HighOrderFTS.generate_lhs_flrg_fuzzyfied">[docs]</a>    <span class="k">def</span> <span class="nf">generate_lhs_flrg_fuzzyfied</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sample</span><span class="p">,</span> <span class="n">explain</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
         <span class="n">lags</span> <span class="o">=</span> <span class="p">{}</span>
 
         <span class="n">flrgs</span> <span class="o">=</span> <span class="p">[]</span>
 
         <span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">o</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">lags</span><span class="p">):</span>
-            <span class="n">lhs</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">fuzzyfy</span><span class="p">(</span><span class="n">sample</span><span class="p">[</span><span class="n">o</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">partitioner</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;sets&quot;</span><span class="p">,</span> <span class="n">alpha_cut</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">alpha_cut</span><span class="p">)</span>
+            <span class="n">lags</span><span class="p">[</span><span class="n">ct</span><span class="p">]</span> <span class="o">=</span> <span class="n">sample</span><span class="p">[</span><span class="n">o</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
-            <span class="n">lags</span><span class="p">[</span><span class="n">ct</span><span class="p">]</span> <span class="o">=</span> <span class="n">lhs</span>
 
             <span class="k">if</span> <span class="n">explain</span><span class="p">:</span>
                 <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\t</span><span class="s2"> (Lag </span><span class="si">{}</span><span class="s2">) </span><span class="si">{}</span><span class="s2"> -&gt; </span><span class="si">{}</span><span class="s2"> </span><span class="se">\n</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">o</span><span class="p">,</span> <span class="n">sample</span><span class="p">[</span><span class="n">o</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">lhs</span><span class="p">))</span>
@@ -167,24 +215,51 @@
 <div class="viewcode-block" id="HighOrderFTS.generate_flrg"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.HighOrderFTS.generate_flrg">[docs]</a>    <span class="k">def</span> <span class="nf">generate_flrg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
         <span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
         <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
+            <span class="n">lags</span> <span class="o">=</span> <span class="p">{}</span>
+
             <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dump</span><span class="p">:</span> <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;FLR: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">k</span><span class="p">))</span>
 
             <span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
+            <span class="nb">print</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
 
             <span class="n">rhs</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">fuzzyfy</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">k</span><span class="p">],</span> <span class="n">partitioner</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s2">&quot;sets&quot;</span><span class="p">,</span> <span class="n">alpha_cut</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">alpha_cut</span><span class="p">)</span>
 
             <span class="n">flrgs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrg</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
 
             <span class="k">for</span> <span class="n">flrg</span> <span class="ow">in</span> <span class="n">flrgs</span><span class="p">:</span>
+                <span class="nb">print</span><span class="p">(</span><span class="s1">&#39;key&#39;</span><span class="p">,</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">())</span>
                 <span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
                     <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span> <span class="o">=</span> <span class="n">flrg</span><span class="p">;</span>
 
                 <span class="k">for</span> <span class="n">st</span> <span class="ow">in</span> <span class="n">rhs</span><span class="p">:</span>
                     <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">st</span><span class="p">)</span></div>
 
+<div class="viewcode-block" id="HighOrderFTS.generate_flrg_fuzzyfied"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.HighOrderFTS.generate_flrg_fuzzyfied">[docs]</a>    <span class="k">def</span> <span class="nf">generate_flrg_fuzzyfied</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
+        <span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
+        <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="n">l</span><span class="p">):</span>
+            <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">dump</span><span class="p">:</span> <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;FLR: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">k</span><span class="p">))</span>
+
+            <span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
+
+
+            <span class="n">rhs</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">k</span><span class="p">]</span>
+
+            <span class="n">flrgs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrg_fuzzyfied</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
+
+            <span class="k">for</span> <span class="n">flrg</span> <span class="ow">in</span> <span class="n">flrgs</span><span class="p">:</span>
+
+                <span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
+                    <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span> <span class="o">=</span> <span class="n">flrg</span>
+
+                <span class="k">for</span> <span class="n">st</span> <span class="ow">in</span> <span class="n">rhs</span><span class="p">:</span>
+                    <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">st</span><span class="p">)</span></div>
+
 <div class="viewcode-block" id="HighOrderFTS.train"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.HighOrderFTS.train">[docs]</a>    <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">configure_lags</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">generate_flrg</span><span class="p">(</span><span class="n">data</span><span class="p">)</span></div>
+        <span class="k">if</span> <span class="ow">not</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;fuzzyfied&#39;</span><span class="p">,</span><span class="kc">False</span><span class="p">):</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">generate_flrg</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
+        <span class="k">else</span><span class="p">:</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">generate_flrg_fuzzyfied</span><span class="p">(</span><span class="n">data</span><span class="p">)</span></div>
 
 <div class="viewcode-block" id="HighOrderFTS.forecast"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.HighOrderFTS.forecast">[docs]</a>    <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
 
@@ -202,7 +277,10 @@
             <span class="k">if</span> <span class="n">explain</span><span class="p">:</span>
                 <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Fuzzyfication </span><span class="se">\n</span><span class="s2">&quot;</span><span class="p">)</span>
 
-            <span class="n">flrgs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrg</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">k</span><span class="p">],</span> <span class="n">explain</span><span class="p">)</span>
+            <span class="k">if</span> <span class="ow">not</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;fuzzyfied&#39;</span><span class="p">,</span> <span class="kc">False</span><span class="p">):</span>
+                <span class="n">flrgs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrg</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">k</span><span class="p">],</span> <span class="n">explain</span><span class="p">)</span>
+            <span class="k">else</span><span class="p">:</span>
+                <span class="n">flrgs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrg_fuzzyfied</span><span class="p">(</span><span class="n">ndata</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">k</span><span class="p">],</span> <span class="n">explain</span><span class="p">)</span>
 
             <span class="k">if</span> <span class="n">explain</span><span class="p">:</span>
                 <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Rules:</span><span class="se">\n</span><span class="s2">&quot;</span><span class="p">)</span>
@@ -212,16 +290,15 @@
 
                 <span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
                     <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
-                        <span class="n">mp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]]</span><span class="o">.</span><span class="n">centroid</span>
+                        <span class="n">mp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]]</span><span class="o">.</span><span class="n">centroid</span>
                         <span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mp</span><span class="p">)</span>
 
                         <span class="k">if</span> <span class="n">explain</span><span class="p">:</span>
                             <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\t</span><span class="s2"> </span><span class="si">{}</span><span class="s2"> -&gt; </span><span class="si">{}</span><span class="s2"> (Naïve)</span><span class="se">\t</span><span class="s2"> Midpoint: </span><span class="si">{}</span><span class="se">\n</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">),</span> <span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span>
                                                                                             <span class="n">mp</span><span class="p">))</span>
-
                 <span class="k">else</span><span class="p">:</span>
                     <span class="n">flrg</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span>
-                    <span class="n">mp</span> <span class="o">=</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
+                    <span class="n">mp</span> <span class="o">=</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
                     <span class="n">tmp</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mp</span><span class="p">)</span>
 
                     <span class="k">if</span> <span class="n">explain</span><span class="p">:</span>
@@ -234,6 +311,41 @@
                 <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;Deffuzyfied value: </span><span class="si">{}</span><span class="s2"> </span><span class="se">\n</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">final</span><span class="p">))</span>
 
         <span class="k">return</span> <span class="n">ret</span></div></div>
+
+
+<div class="viewcode-block" id="WeightedHighOrderFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFTS">[docs]</a><span class="k">class</span> <span class="nc">WeightedHighOrderFTS</span><span class="p">(</span><span class="n">HighOrderFTS</span><span class="p">):</span>
+    <span class="sd">&quot;&quot;&quot;Weighted High Order Fuzzy Time Series&quot;&quot;&quot;</span>
+    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
+        <span class="nb">super</span><span class="p">(</span><span class="n">WeightedHighOrderFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Weighted High Order FTS&quot;</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">&quot;WHOFTS&quot;</span>
+
+<div class="viewcode-block" id="WeightedHighOrderFTS.generate_lhs_flrg_fuzzyfied"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFTS.generate_lhs_flrg_fuzzyfied">[docs]</a>    <span class="k">def</span> <span class="nf">generate_lhs_flrg_fuzzyfied</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sample</span><span class="p">,</span> <span class="n">explain</span><span class="o">=</span><span class="kc">False</span><span class="p">):</span>
+        <span class="n">lags</span> <span class="o">=</span> <span class="p">{}</span>
+
+        <span class="n">flrgs</span> <span class="o">=</span> <span class="p">[]</span>
+
+        <span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">o</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">lags</span><span class="p">):</span>
+            <span class="n">lags</span><span class="p">[</span><span class="n">ct</span><span class="p">]</span> <span class="o">=</span> <span class="n">sample</span><span class="p">[</span><span class="n">o</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
+
+            <span class="k">if</span> <span class="n">explain</span><span class="p">:</span>
+                <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;</span><span class="se">\t</span><span class="s2"> (Lag </span><span class="si">{}</span><span class="s2">) </span><span class="si">{}</span><span class="s2"> -&gt; </span><span class="si">{}</span><span class="s2"> </span><span class="se">\n</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">o</span><span class="p">,</span> <span class="n">sample</span><span class="p">[</span><span class="n">o</span><span class="o">-</span><span class="mi">1</span><span class="p">],</span> <span class="n">lhs</span><span class="p">))</span>
+
+        <span class="n">root</span> <span class="o">=</span> <span class="n">tree</span><span class="o">.</span><span class="n">FLRGTreeNode</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
+
+        <span class="n">tree</span><span class="o">.</span><span class="n">build_tree_without_order</span><span class="p">(</span><span class="n">root</span><span class="p">,</span> <span class="n">lags</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
+
+        <span class="c1"># Trace the possible paths</span>
+        <span class="k">for</span> <span class="n">p</span> <span class="ow">in</span> <span class="n">root</span><span class="o">.</span><span class="n">paths</span><span class="p">():</span>
+            <span class="n">flrg</span> <span class="o">=</span> <span class="n">WeightedHighOrderFLRG</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">)</span>
+            <span class="n">path</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">reversed</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">filter</span><span class="p">(</span><span class="kc">None</span><span class="o">.</span><span class="fm">__ne__</span><span class="p">,</span> <span class="n">p</span><span class="p">))))</span>
+
+            <span class="k">for</span> <span class="n">lhs</span> <span class="ow">in</span> <span class="n">path</span><span class="p">:</span>
+                <span class="n">flrg</span><span class="o">.</span><span class="n">append_lhs</span><span class="p">(</span><span class="n">lhs</span><span class="p">)</span>
+
+            <span class="n">flrgs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">flrg</span><span class="p">)</span>
+
+        <span class="k">return</span> <span class="n">flrgs</span></div></div>
 </pre></div>
 
           </div>

docs/build/html/_modules/pyFTS/models/multivariate/cmvfts.html

@@ -0,0 +1,183 @@
+
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+            
+  <h1>Source code for pyFTS.models.multivariate.cmvfts</h1><div class="highlight"><pre>
+<span></span>
+<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">flrg</span>
+<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span>
+<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="k">import</span> <span class="n">mvfts</span><span class="p">,</span> <span class="n">grid</span><span class="p">,</span> <span class="n">common</span>
+
+
+<div class="viewcode-block" id="ClusteredMVFTS"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS">[docs]</a><span class="k">class</span> <span class="nc">ClusteredMVFTS</span><span class="p">(</span><span class="n">mvfts</span><span class="o">.</span><span class="n">MVFTS</span><span class="p">):</span>
+    <span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Meta model for multivariate, high order, clustered multivariate FTS</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
+        <span class="nb">super</span><span class="p">(</span><span class="n">ClusteredMVFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
+
+        <span class="bp">self</span><span class="o">.</span><span class="n">cluster_method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;cluster_method&#39;</span><span class="p">,</span> <span class="n">grid</span><span class="o">.</span><span class="n">GridCluster</span><span class="p">)</span>
+        <span class="sd">&quot;&quot;&quot;The cluster method to be called when a new model is build&quot;&quot;&quot;</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">cluster_params</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;cluster_params&#39;</span><span class="p">,</span> <span class="p">{})</span>
+        <span class="sd">&quot;&quot;&quot;The cluster method parameters&quot;&quot;&quot;</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">cluster</span> <span class="o">=</span> <span class="kc">None</span>
+        <span class="sd">&quot;&quot;&quot;The most recent trained clusterer&quot;&quot;&quot;</span>
+
+        <span class="bp">self</span><span class="o">.</span><span class="n">fts_method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;fts_method&#39;</span><span class="p">,</span> <span class="n">hofts</span><span class="o">.</span><span class="n">WeightedHighOrderFTS</span><span class="p">)</span>
+        <span class="sd">&quot;&quot;&quot;The FTS method to be called when a new model is build&quot;&quot;&quot;</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">fts_params</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;fts_params&#39;</span><span class="p">,</span> <span class="p">{})</span>
+        <span class="sd">&quot;&quot;&quot;The FTS method specific parameters&quot;&quot;&quot;</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="o">=</span> <span class="kc">None</span>
+        <span class="sd">&quot;&quot;&quot;The most recent trained model&quot;&quot;&quot;</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">knn</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;knn&#39;</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>
+
+        <span class="bp">self</span><span class="o">.</span><span class="n">is_high_order</span> <span class="o">=</span> <span class="kc">True</span>
+
+        <span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;order&quot;</span><span class="p">,</span> <span class="mi">2</span><span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">lags</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;lags&quot;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">alpha_cut</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;alpha_cut&#39;</span><span class="p">,</span> <span class="mf">0.25</span><span class="p">)</span>
+
+        <span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">&quot;ClusteredMVFTS&quot;</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Clustered Multivariate FTS&quot;</span>
+
+<div class="viewcode-block" id="ClusteredMVFTS.fuzzyfy"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.fuzzyfy">[docs]</a>    <span class="k">def</span> <span class="nf">fuzzyfy</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span><span class="n">data</span><span class="p">):</span>
+        <span class="n">ndata</span> <span class="o">=</span> <span class="p">[]</span>
+        <span class="k">for</span> <span class="n">ct</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">index</span><span class="p">)</span><span class="o">+</span><span class="mi">1</span><span class="p">):</span>
+            <span class="n">ix</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">index</span><span class="p">[</span><span class="n">ct</span> <span class="o">-</span> <span class="mi">1</span><span class="p">]</span>
+            <span class="n">data_point</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">format_data</span><span class="p">(</span><span class="n">data</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">ix</span><span class="p">])</span>
+            <span class="n">ndata</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">common</span><span class="o">.</span><span class="n">fuzzyfy_instance_clustered</span><span class="p">(</span><span class="n">data_point</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">cluster</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">alpha_cut</span><span class="p">))</span>
+
+        <span class="k">return</span> <span class="n">ndata</span></div>
+
+
+<div class="viewcode-block" id="ClusteredMVFTS.train"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.train">[docs]</a>    <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
+
+        <span class="bp">self</span><span class="o">.</span><span class="n">cluster</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">cluster_method</span><span class="p">(</span><span class="n">data</span><span class="o">=</span><span class="n">data</span><span class="p">,</span> <span class="n">mvfts</span><span class="o">=</span><span class="bp">self</span><span class="p">,</span> <span class="n">neighbors</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">knn</span><span class="p">)</span>
+
+        <span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">fts_method</span><span class="p">(</span><span class="n">partitioner</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">cluster</span><span class="p">,</span> <span class="o">**</span><span class="bp">self</span><span class="o">.</span><span class="n">fts_params</span><span class="p">)</span>
+        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">is_high_order</span><span class="p">:</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">fts_method</span><span class="p">(</span><span class="n">partitioner</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">cluster</span><span class="p">,</span>
+                                                            <span class="n">order</span><span class="o">=</span><span class="bp">self</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="o">**</span><span class="bp">self</span><span class="o">.</span><span class="n">fts_params</span><span class="p">)</span>
+
+        <span class="n">ndata</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">fuzzyfy</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
+
+        <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="n">fuzzyfied</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span></div>
+
+<div class="viewcode-block" id="ClusteredMVFTS.forecast"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast">[docs]</a>    <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
+
+        <span class="n">ndata</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">fuzzyfy</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
+
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">forecast</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="n">fuzzyfied</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div>
+
+    <span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
+        <span class="sd">&quot;&quot;&quot;String representation of the model&quot;&quot;&quot;</span>
+
+        <span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">shortname</span> <span class="o">+</span> <span class="s2">&quot;:</span><span class="se">\n</span><span class="s2">&quot;</span>
+        <span class="k">for</span> <span class="n">r</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
+            <span class="n">tmp</span> <span class="o">=</span> <span class="n">tmp</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">r</span><span class="p">])</span> <span class="o">+</span> <span class="s2">&quot;</span><span class="se">\n</span><span class="s2">&quot;</span>
+        <span class="k">return</span> <span class="n">tmp</span>
+
+    <span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
+        <span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">        The length (number of rules) of the model</span>
+
+<span class="sd">        :return: number of rules</span>
+<span class="sd">        &quot;&quot;&quot;</span>
+        <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">model</span><span class="p">)</span></div>
+
+</pre></div>
+
+          </div>
+        </div>
+      </div>
+      <div class="clearer"></div>
+    </div>
+    <div class="related" role="navigation" aria-label="related navigation">
+      <h3>Navigation</h3>
+      <ul>
+        <li class="right" style="margin-right: 10px">
+          <a href="../../../../genindex.html" title="General Index"
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+          <a href="../../../../py-modindex.html" title="Python Module Index"
+             >modules</a> |</li>
+        <li class="nav-item nav-item-0"><a href="../../../../index.html">pyFTS 1.2.3 documentation</a> &#187;</li>
+          <li class="nav-item nav-item-1"><a href="../../../index.html" >Module code</a> &#187;</li> 
+      </ul>
+    </div>
+    <div class="footer" role="contentinfo">
+        &#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
+      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 1.7.2.
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+  </body>
+</html>

docs/build/html/_modules/pyFTS/models/multivariate/common.html

@@ -74,13 +74,56 @@
   <h1>Source code for pyFTS.models.multivariate.common</h1><div class="highlight"><pre>
 <span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
 <span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
-<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span>
+<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">Composite</span>
+
+
+<div class="viewcode-block" id="MultivariateFuzzySet"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.common.MultivariateFuzzySet">[docs]</a><span class="k">class</span> <span class="nc">MultivariateFuzzySet</span><span class="p">(</span><span class="n">Composite</span><span class="o">.</span><span class="n">FuzzySet</span><span class="p">):</span>
+    <span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Multivariate Composite Fuzzy Set</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
+        <span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">        Create an empty composite fuzzy set</span>
+<span class="sd">        :param name: fuzzy set name</span>
+<span class="sd">        &quot;&quot;&quot;</span>
+        <span class="nb">super</span><span class="p">(</span><span class="n">MultivariateFuzzySet</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="p">{}</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">target_variable</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;target_variable&#39;</span><span class="p">,</span><span class="kc">None</span><span class="p">)</span>
+
+<div class="viewcode-block" id="MultivariateFuzzySet.append_set"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.common.MultivariateFuzzySet.append_set">[docs]</a>    <span class="k">def</span> <span class="nf">append_set</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">variable</span><span class="p">,</span> <span class="nb">set</span><span class="p">):</span>
+        <span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">        Appends a new fuzzy set from a new variable</span>
+
+<span class="sd">        :param variable: an multivariate.variable instance</span>
+<span class="sd">        :param set: an common.FuzzySet instance</span>
+<span class="sd">        &quot;&quot;&quot;</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">variable</span><span class="p">]</span> <span class="o">=</span> <span class="nb">set</span>
+
+        <span class="k">if</span> <span class="n">variable</span> <span class="o">==</span> <span class="bp">self</span><span class="o">.</span><span class="n">target_variable</span><span class="o">.</span><span class="n">name</span><span class="p">:</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">centroid</span> <span class="o">=</span> <span class="nb">set</span><span class="o">.</span><span class="n">centroid</span></div>
+
+<div class="viewcode-block" id="MultivariateFuzzySet.membership"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.common.MultivariateFuzzySet.membership">[docs]</a>    <span class="k">def</span> <span class="nf">membership</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
+        <span class="n">mv</span> <span class="o">=</span> <span class="p">[]</span>
+        <span class="k">for</span> <span class="n">var</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
+            <span class="n">data</span> <span class="o">=</span> <span class="n">x</span><span class="p">[</span><span class="n">var</span><span class="p">]</span>
+            <span class="n">mv</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">var</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">data</span><span class="p">))</span>
+        <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmin</span><span class="p">(</span><span class="n">mv</span><span class="p">)</span></div></div>
+
+
 
 <div class="viewcode-block" id="fuzzyfy_instance"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.common.fuzzyfy_instance">[docs]</a><span class="k">def</span> <span class="nf">fuzzyfy_instance</span><span class="p">(</span><span class="n">data_point</span><span class="p">,</span> <span class="n">var</span><span class="p">):</span>
     <span class="n">fsets</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">fuzzyfy</span><span class="p">(</span><span class="n">data_point</span><span class="p">,</span> <span class="n">var</span><span class="o">.</span><span class="n">partitioner</span><span class="p">,</span> <span class="n">mode</span><span class="o">=</span><span class="s1">&#39;sets&#39;</span><span class="p">,</span> <span class="n">method</span><span class="o">=</span><span class="s1">&#39;fuzzy&#39;</span><span class="p">,</span> <span class="n">alpha_cut</span><span class="o">=</span><span class="n">var</span><span class="o">.</span><span class="n">alpha_cut</span><span class="p">)</span>
     <span class="k">return</span> <span class="p">[(</span><span class="n">var</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="n">fs</span><span class="p">)</span> <span class="k">for</span> <span class="n">fs</span> <span class="ow">in</span> <span class="n">fsets</span><span class="p">]</span></div>
 
 
+<div class="viewcode-block" id="fuzzyfy_instance_clustered"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.common.fuzzyfy_instance_clustered">[docs]</a><span class="k">def</span> <span class="nf">fuzzyfy_instance_clustered</span><span class="p">(</span><span class="n">data_point</span><span class="p">,</span> <span class="n">cluster</span><span class="p">,</span> <span class="n">alpha_cut</span><span class="o">=</span><span class="mf">0.0</span><span class="p">):</span>
+    <span class="n">fsets</span> <span class="o">=</span> <span class="p">[]</span>
+    <span class="k">for</span> <span class="n">fset</span> <span class="ow">in</span> <span class="n">cluster</span><span class="o">.</span><span class="n">knn</span><span class="p">(</span><span class="n">data_point</span><span class="p">):</span>
+        <span class="k">if</span> <span class="n">cluster</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">fset</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">data_point</span><span class="p">)</span> <span class="o">&gt;</span> <span class="n">alpha_cut</span><span class="p">:</span>
+            <span class="n">fsets</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">fset</span><span class="p">)</span>
+    <span class="k">return</span> <span class="n">fsets</span></div>
+
+
 
 </pre></div>
 

docs/build/html/_modules/pyFTS/models/multivariate/mvfts.html

@@ -85,7 +85,7 @@
 <span class="sd">    Multivariate extension of Chen&#39;s ConventionalFTS method</span>
 <span class="sd">    &quot;&quot;&quot;</span>
     <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
-        <span class="nb">super</span><span class="p">(</span><span class="n">MVFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
+        <span class="nb">super</span><span class="p">(</span><span class="n">MVFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">explanatory_variables</span> <span class="o">=</span> <span class="p">[]</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">target_variable</span> <span class="o">=</span> <span class="kc">None</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span> <span class="o">=</span> <span class="p">{}</span>
@@ -187,15 +187,12 @@
             <span class="k">for</span> <span class="n">flr</span> <span class="ow">in</span> <span class="n">flrs</span><span class="p">:</span>
                 <span class="n">flrg</span> <span class="o">=</span> <span class="n">mvflrg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">(</span><span class="n">lhs</span><span class="o">=</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span>
                 <span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
-                    <span class="c1">#print(&#39;hit&#39;)</span>
                     <span class="n">mvs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mf">0.</span><span class="p">)</span>
                     <span class="n">mps</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="mf">0.</span><span class="p">)</span>
                 <span class="k">else</span><span class="p">:</span>
                     <span class="n">mvs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">get_membership</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">format_data</span><span class="p">(</span><span class="n">data_point</span><span class="p">),</span> <span class="bp">self</span><span class="o">.</span><span class="n">explanatory_variables</span><span class="p">))</span>
                     <span class="n">mps</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">get_midpoint</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">target_variable</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">))</span>
 
-            <span class="c1">#print(&#39;mv&#39;, mvs)</span>
-            <span class="c1">#print(&#39;mp&#39;, mps)</span>
             <span class="n">mv</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">mvs</span><span class="p">)</span>
             <span class="n">mp</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">mps</span><span class="p">)</span>
 
@@ -205,6 +202,44 @@
                                                            <span class="n">params</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">target_variable</span><span class="o">.</span><span class="n">data_label</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">)</span>
         <span class="k">return</span> <span class="n">ret</span></div>
 
+<div class="viewcode-block" id="MVFTS.forecast_ahead"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.forecast_ahead">[docs]</a>    <span class="k">def</span> <span class="nf">forecast_ahead</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
+        <span class="n">generators</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;generators&#39;</span><span class="p">,</span><span class="kc">None</span><span class="p">)</span>
+        <span class="n">start</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;start&#39;</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
+
+        <span class="k">if</span> <span class="n">generators</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="k">raise</span> <span class="ne">Exception</span><span class="p">(</span><span class="s1">&#39;You must provide parameter </span><span class="se">\&#39;</span><span class="s1">generators</span><span class="se">\&#39;</span><span class="s1">! generators is a dict where the keys&#39;</span> <span class="o">+</span>
+                            <span class="s1">&#39; are the variables names (except the target_variable) and the values are &#39;</span> <span class="o">+</span>
+                            <span class="s1">&#39;lambda functions that accept one value (the actual value of the variable) &#39;</span>
+                            <span class="s1">&#39; and return the next value.&#39;</span><span class="p">)</span>
+
+        <span class="n">ndata</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">apply_transformations</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
+
+        <span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
+        <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">steps</span><span class="p">):</span>
+            <span class="n">ix</span> <span class="o">=</span> <span class="n">ndata</span><span class="o">.</span><span class="n">index</span><span class="p">[</span><span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:]</span>
+            <span class="n">sample</span> <span class="o">=</span> <span class="n">ndata</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span>
+            <span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">forecast</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
+
+            <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">tmp</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)):</span>
+                <span class="n">tmp</span> <span class="o">=</span> <span class="n">tmp</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
+
+            <span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
+
+            <span class="n">last_data_point</span> <span class="o">=</span> <span class="n">sample</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">sample</span><span class="o">.</span><span class="n">index</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]]</span>
+
+            <span class="n">new_data_point</span> <span class="o">=</span> <span class="p">{}</span>
+
+            <span class="k">for</span> <span class="n">var</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">explanatory_variables</span><span class="p">:</span>
+                <span class="k">if</span> <span class="n">var</span><span class="o">.</span><span class="n">name</span> <span class="o">!=</span> <span class="bp">self</span><span class="o">.</span><span class="n">target_variable</span><span class="o">.</span><span class="n">name</span><span class="p">:</span>
+                    <span class="n">new_data_point</span><span class="p">[</span><span class="n">var</span><span class="o">.</span><span class="n">data_label</span><span class="p">]</span> <span class="o">=</span> <span class="n">generators</span><span class="p">[</span><span class="n">var</span><span class="o">.</span><span class="n">name</span><span class="p">](</span><span class="n">last_data_point</span><span class="p">[</span><span class="n">var</span><span class="o">.</span><span class="n">data_label</span><span class="p">])</span>
+
+            <span class="n">new_data_point</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">target_variable</span><span class="o">.</span><span class="n">data_label</span><span class="p">]</span> <span class="o">=</span> <span class="n">tmp</span>
+
+            <span class="n">ndata</span> <span class="o">=</span> <span class="n">ndata</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">new_data_point</span><span class="p">,</span> <span class="n">ignore_index</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+
+        <span class="k">return</span> <span class="n">ret</span></div>
+
+
 <div class="viewcode-block" id="MVFTS.clone_parameters"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.clone_parameters">[docs]</a>    <span class="k">def</span> <span class="nf">clone_parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">model</span><span class="p">):</span>
         <span class="nb">super</span><span class="p">(</span><span class="n">MVFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">clone_parameters</span><span class="p">(</span><span class="n">model</span><span class="p">)</span>
 

docs/build/html/_modules/pyFTS/models/multivariate/wmvfts.html

@@ -0,0 +1,168 @@
+
+
+<!doctype html>
+
+<html xmlns="http://www.w3.org/1999/xhtml">
+  <head>
+    <meta http-equiv="X-UA-Compatible" content="IE=Edge" />
+    <meta http-equiv="Content-Type" content="text/html; charset=utf-8" /><script type="text/javascript">
+
+      var _gaq = _gaq || [];
+      _gaq.push(['_setAccount', 'UA-55120145-3']);
+      _gaq.push(['_trackPageview']);
+
+      (function() {
+        var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
+        ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
+        var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
+      })();
+    </script>
+    <title>pyFTS.models.multivariate.wmvfts &#8212; pyFTS 1.2.3 documentation</title>
+    <link rel="stylesheet" href="../../../../_static/bizstyle.css" type="text/css" />
+    <link rel="stylesheet" href="../../../../_static/pygments.css" type="text/css" />
+    <script type="text/javascript" src="../../../../_static/documentation_options.js"></script>
+    <script type="text/javascript" src="../../../../_static/jquery.js"></script>
+    <script type="text/javascript" src="../../../../_static/underscore.js"></script>
+    <script type="text/javascript" src="../../../../_static/doctools.js"></script>
+    <script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script>
+    <script type="text/javascript" src="../../../../_static/bizstyle.js"></script>
+    <link rel="index" title="Index" href="../../../../genindex.html" />
+    <link rel="search" title="Search" href="../../../../search.html" />
+    <meta name="viewport" content="width=device-width,initial-scale=1.0">
+    <!--[if lt IE 9]>
+    <script type="text/javascript" src="_static/css3-mediaqueries.js"></script>
+    <![endif]-->
+  </head><body>
+    <div class="related" role="navigation" aria-label="related navigation">
+      <h3>Navigation</h3>
+      <ul>
+        <li class="right" style="margin-right: 10px">
+          <a href="../../../../genindex.html" title="General Index"
+             accesskey="I">index</a></li>
+        <li class="right" >
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+            
+  <h1>Source code for pyFTS.models.multivariate.wmvfts</h1><div class="highlight"><pre>
+<span></span><span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">fts</span><span class="p">,</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">Membership</span><span class="p">,</span> <span class="n">tree</span>
+<span class="kn">from</span> <span class="nn">pyFTS.partitioners</span> <span class="k">import</span> <span class="n">Grid</span>
+<span class="kn">from</span> <span class="nn">pyFTS.models.multivariate</span> <span class="k">import</span> <span class="n">mvfts</span><span class="p">,</span> <span class="n">FLR</span> <span class="k">as</span> <span class="n">MVFLR</span><span class="p">,</span> <span class="n">common</span><span class="p">,</span> <span class="n">flrg</span> <span class="k">as</span> <span class="n">mvflrg</span>
+
+<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="kn">import</span> <span class="nn">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
+
+
+<div class="viewcode-block" id="WeightedFLRG"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.wmvfts.WeightedFLRG">[docs]</a><span class="k">class</span> <span class="nc">WeightedFLRG</span><span class="p">(</span><span class="n">mvflrg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">):</span>
+    <span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Weighted Multivariate Fuzzy Logical Rule Group</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+
+    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
+        <span class="nb">super</span><span class="p">(</span><span class="n">WeightedFLRG</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;order&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;lhs&#39;</span><span class="p">,</span> <span class="p">{})</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span> <span class="o">=</span> <span class="p">{}</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="o">=</span> <span class="mf">0.0</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="o">=</span> <span class="kc">None</span>
+
+<div class="viewcode-block" id="WeightedFLRG.append_rhs"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.wmvfts.WeightedFLRG.append_rhs">[docs]</a>    <span class="k">def</span> <span class="nf">append_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">fset</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
+        <span class="k">if</span> <span class="n">fset</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">:</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">fset</span><span class="p">]</span> <span class="o">=</span> <span class="mf">1.0</span>
+        <span class="k">else</span><span class="p">:</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">fset</span><span class="p">]</span> <span class="o">+=</span> <span class="mf">1.0</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="o">+=</span> <span class="mf">1.0</span></div>
+
+<div class="viewcode-block" id="WeightedFLRG.weights"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.wmvfts.WeightedFLRG.weights">[docs]</a>    <span class="k">def</span> <span class="nf">weights</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
+        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">w</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">c</span><span class="p">]</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">count</span> <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()])</span>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">w</span></div>
+
+<div class="viewcode-block" id="WeightedFLRG.get_midpoint"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_midpoint">[docs]</a>    <span class="k">def</span> <span class="nf">get_midpoint</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
+        <span class="n">mp</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">sets</span><span class="p">[</span><span class="n">c</span><span class="p">]</span><span class="o">.</span><span class="n">centroid</span> <span class="k">for</span> <span class="n">c</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()])</span>
+        <span class="k">return</span> <span class="n">mp</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">weights</span><span class="p">())</span></div>
+
+
+    <span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
+        <span class="n">_str</span> <span class="o">=</span> <span class="s2">&quot;&quot;</span>
+        <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
+            <span class="n">_str</span> <span class="o">+=</span> <span class="s2">&quot;, &quot;</span> <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">_str</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span> <span class="k">else</span> <span class="s2">&quot;&quot;</span>
+            <span class="n">_str</span> <span class="o">+=</span> <span class="n">k</span> <span class="o">+</span> <span class="s2">&quot; (&quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">count</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span> <span class="o">+</span> <span class="s2">&quot;)&quot;</span>
+
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="o">+</span> <span class="s2">&quot; -&gt; &quot;</span> <span class="o">+</span> <span class="n">_str</span></div>
+
+
+<div class="viewcode-block" id="WeightedMVFTS"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.wmvfts.WeightedMVFTS">[docs]</a><span class="k">class</span> <span class="nc">WeightedMVFTS</span><span class="p">(</span><span class="n">mvfts</span><span class="o">.</span><span class="n">MVFTS</span><span class="p">):</span>
+    <span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Weighted Multivariate FTS</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
+        <span class="nb">super</span><span class="p">(</span><span class="n">WeightedMVFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">order</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">explanatory_variables</span> <span class="o">=</span> <span class="p">[]</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">target_variable</span> <span class="o">=</span> <span class="kc">None</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span> <span class="o">=</span> <span class="p">{}</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">is_multivariate</span> <span class="o">=</span> <span class="kc">True</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">&quot;WeightedMVFTS&quot;</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">&quot;Weighted Multivariate FTS&quot;</span>
+
+<div class="viewcode-block" id="WeightedMVFTS.generate_flrg"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.generate_flrg">[docs]</a>    <span class="k">def</span> <span class="nf">generate_flrg</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">flrs</span><span class="p">):</span>
+        <span class="k">for</span> <span class="n">flr</span> <span class="ow">in</span> <span class="n">flrs</span><span class="p">:</span>
+            <span class="n">flrg</span> <span class="o">=</span> <span class="n">WeightedFLRG</span><span class="p">(</span><span class="n">lhs</span><span class="o">=</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span>
+
+            <span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
+                <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span> <span class="o">=</span> <span class="n">flrg</span>
+
+            <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span><span class="o">.</span><span class="n">append_rhs</span><span class="p">(</span><span class="n">flr</span><span class="o">.</span><span class="n">RHS</span><span class="p">)</span></div></div>
+</pre></div>
+
+          </div>
+        </div>
+      </div>
+      <div class="clearer"></div>
+    </div>
+    <div class="related" role="navigation" aria-label="related navigation">
+      <h3>Navigation</h3>
+      <ul>
+        <li class="right" style="margin-right: 10px">
+          <a href="../../../../genindex.html" title="General Index"
+             >index</a></li>
+        <li class="right" >
+          <a href="../../../../py-modindex.html" title="Python Module Index"
+             >modules</a> |</li>
+        <li class="nav-item nav-item-0"><a href="../../../../index.html">pyFTS 1.2.3 documentation</a> &#187;</li>
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+      </ul>
+    </div>
+    <div class="footer" role="contentinfo">
+        &#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
+      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 1.7.2.
+    </div>
+  </body>
+</html>

docs/build/html/_modules/pyFTS/models/seasonal/common.html

@@ -163,10 +163,9 @@
 
     <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">datepart</span><span class="p">,</span> <span class="n">name</span><span class="p">,</span> <span class="n">mf</span><span class="p">,</span> <span class="n">parameters</span><span class="p">,</span> <span class="n">centroid</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">1.0</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
         <span class="nb">super</span><span class="p">(</span><span class="n">FuzzySet</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">name</span><span class="p">,</span> <span class="n">mf</span><span class="p">,</span> <span class="n">parameters</span><span class="p">,</span> <span class="n">centroid</span><span class="p">,</span> <span class="n">alpha</span><span class="p">,</span>
-                                       <span class="nb">type</span><span class="o">=</span><span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;type&#39;</span><span class="p">,</span> <span class="s1">&#39;seasonal&#39;</span><span class="p">),</span>
                                        <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">datepart</span> <span class="o">=</span> <span class="n">datepart</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">=</span> <span class="s1">&#39;seasonal&#39;</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;type&#39;</span><span class="p">,</span> <span class="s1">&#39;seasonal&#39;</span><span class="p">)</span>
 
 <div class="viewcode-block" id="FuzzySet.transform"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.common.FuzzySet.transform">[docs]</a>    <span class="k">def</span> <span class="nf">transform</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">x</span><span class="p">):</span>
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="s1">&#39;seasonal&#39;</span><span class="p">:</span>

docs/build/html/_modules/pyFTS/models/seasonal/partitioner.html

@@ -104,6 +104,8 @@
             <span class="bp">self</span><span class="o">.</span><span class="n">min</span> <span class="o">=</span> <span class="n">tmp</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">max</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="o">.</span><span class="n">value</span> <span class="o">+</span> <span class="n">tmp</span>
 
+        <span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;type&#39;</span><span class="p">,</span><span class="s1">&#39;seasonal&#39;</span><span class="p">)</span>
+
         <span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">build</span><span class="p">(</span><span class="kc">None</span><span class="p">)</span>
 
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">setnames</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
@@ -114,7 +116,7 @@
 <div class="viewcode-block" id="TimeGridPartitioner.build"><a class="viewcode-back" href="../../../../pyFTS.models.seasonal.html#pyFTS.models.seasonal.partitioner.TimeGridPartitioner.build">[docs]</a>    <span class="k">def</span> <span class="nf">build</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
         <span class="n">sets</span> <span class="o">=</span> <span class="p">{}</span>
 
-        <span class="n">kwargs</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;variable&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">variable</span><span class="p">}</span>
+        <span class="n">kwargs</span> <span class="o">=</span> <span class="p">{</span><span class="s1">&#39;variable&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">variable</span><span class="p">,</span> <span class="s1">&#39;type&#39;</span><span class="p">:</span> <span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="p">}</span>
 
         <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">season</span> <span class="o">==</span> <span class="n">DateTime</span><span class="o">.</span><span class="n">year</span><span class="p">:</span>
             <span class="n">dlen</span> <span class="o">=</span> <span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">min</span><span class="p">)</span>
@@ -128,7 +130,7 @@
             <span class="n">set_name</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_name</span><span class="p">(</span><span class="n">count</span><span class="p">)</span>
             <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">membership_function</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">:</span>
                 <span class="k">if</span> <span class="n">c</span> <span class="o">==</span> <span class="bp">self</span><span class="o">.</span><span class="n">min</span><span class="p">:</span>
-                    <span class="n">tmp</span> <span class="o">=</span> <span class="n">Composite</span><span class="p">(</span><span class="n">set_name</span><span class="p">,</span> <span class="n">superset</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+                    <span class="n">tmp</span> <span class="o">=</span> <span class="n">Composite</span><span class="p">(</span><span class="n">set_name</span><span class="p">,</span> <span class="n">superset</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
                     <span class="n">tmp</span><span class="o">.</span><span class="n">append_set</span><span class="p">(</span><span class="n">FuzzySet</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="p">,</span> <span class="n">set_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">,</span>
                                             <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="o">.</span><span class="n">value</span> <span class="o">-</span> <span class="n">pl2</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="o">.</span><span class="n">value</span><span class="p">,</span>
                                              <span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="o">.</span><span class="n">value</span> <span class="o">+</span> <span class="mf">0.0000001</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="o">.</span><span class="n">value</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=.</span><span class="mi">5</span><span class="p">,</span>
@@ -139,7 +141,7 @@
                     <span class="n">tmp</span><span class="o">.</span><span class="n">centroid</span> <span class="o">=</span> <span class="n">c</span>
                     <span class="n">sets</span><span class="p">[</span><span class="n">set_name</span><span class="p">]</span> <span class="o">=</span> <span class="n">tmp</span>
                 <span class="k">elif</span> <span class="n">c</span> <span class="o">==</span> <span class="bp">self</span><span class="o">.</span><span class="n">max</span> <span class="o">-</span> <span class="n">partlen</span><span class="p">:</span>
-                    <span class="n">tmp</span> <span class="o">=</span> <span class="n">Composite</span><span class="p">(</span><span class="n">set_name</span><span class="p">,</span> <span class="n">superset</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+                    <span class="n">tmp</span> <span class="o">=</span> <span class="n">Composite</span><span class="p">(</span><span class="n">set_name</span><span class="p">,</span> <span class="n">superset</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
                     <span class="n">tmp</span><span class="o">.</span><span class="n">append_set</span><span class="p">(</span><span class="n">FuzzySet</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">season</span><span class="p">,</span> <span class="n">set_name</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">,</span>
                                             <span class="p">[</span><span class="mf">0.0000001</span><span class="p">,</span> <span class="mf">0.0</span><span class="p">,</span>
                                              <span class="n">pl2</span><span class="p">],</span> <span class="mf">0.0</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=.</span><span class="mi">5</span><span class="p">,</span>

docs/build/html/_modules/pyFTS/partitioners/Entropy.html

@@ -114,7 +114,7 @@
 
 <div class="viewcode-block" id="bestSplit"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.Entropy.bestSplit">[docs]</a><span class="k">def</span> <span class="nf">bestSplit</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="n">npart</span><span class="p">):</span>
     <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span> <span class="o">&lt;</span> <span class="mi">2</span><span class="p">:</span>
-        <span class="k">return</span> <span class="kc">None</span>
+        <span class="k">return</span> <span class="p">[]</span>
     <span class="n">count</span> <span class="o">=</span> <span class="mi">1</span>
     <span class="n">ndata</span> <span class="o">=</span> <span class="nb">list</span><span class="p">(</span><span class="nb">set</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">data</span><span class="p">)</span><span class="o">.</span><span class="n">flatten</span><span class="p">()))</span>
     <span class="n">ndata</span><span class="o">.</span><span class="n">sort</span><span class="p">()</span>

docs/build/html/_modules/pyFTS/partitioners/partitioner.html

@@ -101,7 +101,9 @@
         <span class="sd">&quot;&quot;&quot;data transformation to be applied on data&quot;&quot;&quot;</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;indexer&#39;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">variable</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;variable&#39;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
+        <span class="sd">&quot;&quot;&quot;In a multivariate context, the variable that contains this partitioner&quot;&quot;&quot;</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;type&#39;</span><span class="p">,</span> <span class="s1">&#39;common&#39;</span><span class="p">)</span>
+        <span class="sd">&quot;&quot;&quot;The type of fuzzy sets that are generated by this partitioner&quot;&quot;&quot;</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span> <span class="o">=</span> <span class="kc">None</span>
 
         <span class="k">if</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;preprocess&#39;</span><span class="p">,</span><span class="kc">True</span><span class="p">):</span>

docs/build/html/_sources/pyFTS.hyperparam.rst.txt

@@ -0,0 +1,31 @@
+pyFTS.hyperparam package
+========================
+
+Module contents
+---------------
+
+.. automodule:: pyFTS.hyperparam
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+Submodules
+----------
+
+pyFTS.hyperparam.Util module
+-----------------------------
+
+.. automodule:: pyFTS.hyperparam.Util
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+pyFTS.hyperparam.GridSearch module
+----------------------------------
+
+.. automodule:: pyFTS.hyperparam.GridSearch
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
+

docs/build/html/_sources/pyFTS.models.multivariate.rst.txt

@@ -29,6 +29,14 @@ pyFTS.models.multivariate.common module
     :undoc-members:
     :show-inheritance:
 
+pyFTS.models.multivariate.variable module
+-----------------------------------------
+
+.. automodule:: pyFTS.models.multivariate.variable
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
 pyFTS.models.multivariate.flrg module
 -------------------------------------
 
@@ -45,18 +53,18 @@ pyFTS.models.multivariate.mvfts module
     :undoc-members:
     :show-inheritance:
     
-pyFTS.models.multivariate.variable module
------------------------------------------
-
-.. automodule:: pyFTS.models.multivariate.variable
-    :members:
-    :undoc-members:
-    :show-inheritance:
-    
 pyFTS.models.multivariate.wmvfts module
---------------------------------------
+---------------------------------------
 
-.. automodule:: pyFTS.models.multivariate.mvfts
+.. automodule:: pyFTS.models.multivariate.wmvfts
+    :members:
+    :undoc-members:
+    :show-inheritance:
+    
+pyFTS.models.multivariate.cmvfts module
+---------------------------------------
+
+.. automodule:: pyFTS.models.multivariate.cmvfts
     :members:
     :undoc-members:
     :show-inheritance:

docs/build/html/_sources/pyFTS.partitioners.rst.txt

@@ -61,7 +61,7 @@ pyFTS.partitioners.Huarng module
     :show-inheritance:
 
 pyFTS.partitioners.Singleton module
---------------------------------
+-----------------------------------
 
 .. automodule:: pyFTS.partitioners.Singleton
     :members:

docs/build/html/_sources/pyFTS.rst.txt

@@ -9,6 +9,7 @@ Subpackages
     pyFTS.benchmarks
     pyFTS.common
     pyFTS.data
+    pyFTS.hyperparam
     pyFTS.models
     pyFTS.partitioners
     pyFTS.probabilistic

docs/build/html/genindex.html

@@ -139,6 +139,8 @@
       <li><a href="pyFTS.models.html#pyFTS.models.hofts.HighOrderFLRG.append_lhs">append_lhs() (pyFTS.models.hofts.HighOrderFLRG method)</a>
 
       <ul>
+        <li><a href="pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFLRG.append_lhs">(pyFTS.models.hofts.WeightedHighOrderFLRG method)</a>
+</li>
         <li><a href="pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.HighOrderNonstationaryFLRG.append_lhs">(pyFTS.models.nonstationary.cvfts.HighOrderNonstationaryFLRG method)</a>
 </li>
         <li><a href="pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.honsfts.HighOrderNonStationaryFLRG.append_lhs">(pyFTS.models.nonstationary.honsfts.HighOrderNonStationaryFLRG method)</a>
@@ -152,10 +154,14 @@
         <li><a href="pyFTS.models.html#pyFTS.models.chen.ConventionalFLRG.append_rhs">(pyFTS.models.chen.ConventionalFLRG method)</a>
 </li>
         <li><a href="pyFTS.models.html#pyFTS.models.hofts.HighOrderFLRG.append_rhs">(pyFTS.models.hofts.HighOrderFLRG method)</a>
+</li>
+        <li><a href="pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFLRG.append_rhs">(pyFTS.models.hofts.WeightedHighOrderFLRG method)</a>
 </li>
         <li><a href="pyFTS.models.html#pyFTS.models.ismailefendi.ImprovedWeightedFLRG.append_rhs">(pyFTS.models.ismailefendi.ImprovedWeightedFLRG method)</a>
 </li>
         <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.flrg.FLRG.append_rhs">(pyFTS.models.multivariate.flrg.FLRG method)</a>
+</li>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.wmvfts.WeightedFLRG.append_rhs">(pyFTS.models.multivariate.wmvfts.WeightedFLRG method)</a>
 </li>
         <li><a href="pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.HighOrderNonstationaryFLRG.append_rhs">(pyFTS.models.nonstationary.cvfts.HighOrderNonstationaryFLRG method)</a>
 </li>
@@ -177,10 +183,14 @@
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="pyFTS.common.html#pyFTS.common.Composite.FuzzySet.append_set">append_set() (pyFTS.common.Composite.FuzzySet method)</a>
+
+      <ul>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.common.MultivariateFuzzySet.append_set">(pyFTS.models.multivariate.common.MultivariateFuzzySet method)</a>
 </li>
+      </ul></li>
       <li><a href="pyFTS.common.html#pyFTS.common.fts.FTS.append_transformation">append_transformation() (pyFTS.common.fts.FTS method)</a>
 </li>
-      <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.append_variable">append_variable() (pyFTS.models.multivariate.mvfts.MVFTS method)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.append_variable">[1]</a>
+      <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.append_variable">append_variable() (pyFTS.models.multivariate.mvfts.MVFTS method)</a>
 </li>
       <li><a href="pyFTS.common.html#pyFTS.common.tree.FLRGTreeNode.appendChild">appendChild() (pyFTS.common.tree.FLRGTreeNode method)</a>
 </li>
@@ -205,7 +215,7 @@
       <li><a href="pyFTS.common.html#pyFTS.common.fts.FTS.apply_transformations">apply_transformations() (pyFTS.common.fts.FTS method)</a>
 
       <ul>
-        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.apply_transformations">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.apply_transformations">[1]</a>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.apply_transformations">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>
 </li>
         <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.variable.Variable.apply_transformations">(pyFTS.models.multivariate.variable.Variable method)</a>
 </li>
@@ -323,17 +333,25 @@
       <li><a href="pyFTS.common.html#pyFTS.common.fts.FTS.clone_parameters">clone_parameters() (pyFTS.common.fts.FTS method)</a>
 
       <ul>
-        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.clone_parameters">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.clone_parameters">[1]</a>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.clone_parameters">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>
 </li>
       </ul></li>
+      <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.cluster">cluster (pyFTS.models.multivariate.cmvfts.ClusteredMVFTS attribute)</a>
+</li>
+      <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.cluster_method">cluster_method (pyFTS.models.multivariate.cmvfts.ClusteredMVFTS attribute)</a>
+</li>
+      <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.cluster_params">cluster_params (pyFTS.models.multivariate.cmvfts.ClusteredMVFTS attribute)</a>
+</li>
+      <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS">ClusteredMVFTS (class in pyFTS.models.multivariate.cmvfts)</a>
+</li>
       <li><a href="pyFTS.partitioners.html#pyFTS.partitioners.CMeans.CMeansPartitioner">CMeansPartitioner (class in pyFTS.partitioners.CMeans)</a>
 </li>
+  </ul></td>
+  <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.ResidualAnalysis.compare_residuals">compare_residuals() (in module pyFTS.benchmarks.ResidualAnalysis)</a>
 </li>
       <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.compareModelsPlot">compareModelsPlot() (in module pyFTS.benchmarks.benchmarks)</a>
 </li>
-  </ul></td>
-  <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.compareModelsTable">compareModelsTable() (in module pyFTS.benchmarks.benchmarks)</a>
 </li>
       <li><a href="pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.nsfts.NonStationaryFTS.conditional_perturbation_factors">conditional_perturbation_factors() (pyFTS.models.nonstationary.nsfts.NonStationaryFTS method)</a>
@@ -367,6 +385,8 @@
       <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.coverage">coverage() (in module pyFTS.benchmarks.Measures)</a>
 </li>
       <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.Util.create_benchmark_tables">create_benchmark_tables() (in module pyFTS.benchmarks.Util)</a>
+</li>
+      <li><a href="pyFTS.hyperparam.html#pyFTS.hyperparam.Util.create_hyperparam_tables">create_hyperparam_tables() (in module pyFTS.hyperparam.Util)</a>
 </li>
       <li><a href="pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.crossentropy">crossentropy() (pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution method)</a>
 </li>
@@ -396,11 +416,13 @@
 </li>
       <li><a href="pyFTS.models.seasonal.html#pyFTS.models.seasonal.common.DateTime.day_of_year">day_of_year (pyFTS.models.seasonal.common.DateTime attribute)</a>
 </li>
-  </ul></td>
-  <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.density">density() (pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution method)</a>
 </li>
+  </ul></td>
+  <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="pyFTS.common.html#pyFTS.common.fts.FTS.detail">detail (pyFTS.common.fts.FTS attribute)</a>
+</li>
+      <li><a href="pyFTS.hyperparam.html#pyFTS.hyperparam.GridSearch.dict_individual">dict_individual() (in module pyFTS.hyperparam.GridSearch)</a>
 </li>
       <li><a href="pyFTS.common.html#pyFTS.common.Transformations.Differential">Differential (class in pyFTS.common.Transformations)</a>
 </li>
@@ -433,6 +455,8 @@
       <li><a href="pyFTS.partitioners.html#pyFTS.partitioners.Entropy.EntropyPartitioner">EntropyPartitioner (class in pyFTS.partitioners.Entropy)</a>
 </li>
       <li><a href="pyFTS.common.html#pyFTS.common.Util.enumerate2">enumerate2() (in module pyFTS.common.Util)</a>
+</li>
+      <li><a href="pyFTS.hyperparam.html#pyFTS.hyperparam.GridSearch.execute">execute() (in module pyFTS.hyperparam.GridSearch)</a>
 </li>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
@@ -523,7 +547,9 @@
 </li>
         <li><a href="pyFTS.models.html#pyFTS.models.ismailefendi.ImprovedWeightedFTS.forecast">(pyFTS.models.ismailefendi.ImprovedWeightedFTS method)</a>
 </li>
-        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.forecast">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.forecast">[1]</a>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast">(pyFTS.models.multivariate.cmvfts.ClusteredMVFTS method)</a>
+</li>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.forecast">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>
 </li>
         <li><a href="pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS.forecast">(pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS method)</a>
 </li>
@@ -549,6 +575,8 @@
       <li><a href="pyFTS.common.html#pyFTS.common.fts.FTS.forecast_ahead">forecast_ahead() (pyFTS.common.fts.FTS method)</a>
 
       <ul>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.forecast_ahead">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>
+</li>
         <li><a href="pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_ahead">(pyFTS.models.pwfts.ProbabilisticWeightedFTS method)</a>
 </li>
         <li><a href="pyFTS.models.seasonal.html#pyFTS.models.seasonal.cmsfts.ContextualMultiSeasonalFTS.forecast_ahead">(pyFTS.models.seasonal.cmsfts.ContextualMultiSeasonalFTS method)</a>
@@ -556,8 +584,6 @@
         <li><a href="pyFTS.models.seasonal.html#pyFTS.models.seasonal.msfts.MultiSeasonalFTS.forecast_ahead">(pyFTS.models.seasonal.msfts.MultiSeasonalFTS method)</a>
 </li>
       </ul></li>
-  </ul></td>
-  <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.arima.ARIMA.forecast_ahead_distribution">forecast_ahead_distribution() (pyFTS.benchmarks.arima.ARIMA method)</a>
 
       <ul>
@@ -570,6 +596,8 @@
         <li><a href="pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_ahead_distribution">(pyFTS.models.pwfts.ProbabilisticWeightedFTS method)</a>
 </li>
       </ul></li>
+  </ul></td>
+  <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.arima.ARIMA.forecast_ahead_interval">forecast_ahead_interval() (pyFTS.benchmarks.arima.ARIMA method)</a>
 
       <ul>
@@ -618,14 +646,22 @@
         <li><a href="pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.forecast_interval">(pyFTS.models.pwfts.ProbabilisticWeightedFTS method)</a>
 </li>
       </ul></li>
-      <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.format_data">format_data() (pyFTS.models.multivariate.mvfts.MVFTS method)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.format_data">[1]</a>
+      <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.format_data">format_data() (pyFTS.models.multivariate.mvfts.MVFTS method)</a>
 </li>
       <li><a href="pyFTS.common.html#pyFTS.common.fts.FTS">FTS (class in pyFTS.common.fts)</a>
 </li>
       <li><a href="pyFTS.models.incremental.html#pyFTS.models.incremental.Retrainer.Retrainer.fts_method">fts_method (pyFTS.models.incremental.Retrainer.Retrainer attribute)</a>
+
+      <ul>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.fts_method">(pyFTS.models.multivariate.cmvfts.ClusteredMVFTS attribute)</a>
 </li>
+      </ul></li>
       <li><a href="pyFTS.models.incremental.html#pyFTS.models.incremental.Retrainer.Retrainer.fts_params">fts_params (pyFTS.models.incremental.Retrainer.Retrainer attribute)</a>
+
+      <ul>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.fts_params">(pyFTS.models.multivariate.cmvfts.ClusteredMVFTS attribute)</a>
 </li>
+      </ul></li>
       <li><a href="pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.common.fuzzify">fuzzify() (in module pyFTS.models.nonstationary.common)</a>
 </li>
       <li><a href="pyFTS.common.html#pyFTS.common.fts.FTS.fuzzy">fuzzy() (pyFTS.common.fts.FTS method)</a>
@@ -635,13 +671,19 @@
       <li><a href="pyFTS.partitioners.html#pyFTS.partitioners.FCM.fuzzy_distance">fuzzy_distance() (in module pyFTS.partitioners.FCM)</a>
 </li>
       <li><a href="pyFTS.common.html#pyFTS.common.FuzzySet.fuzzyfy">fuzzyfy() (in module pyFTS.common.FuzzySet)</a>
+
+      <ul>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.fuzzyfy">(pyFTS.models.multivariate.cmvfts.ClusteredMVFTS method)</a>
 </li>
+      </ul></li>
       <li><a href="pyFTS.common.html#pyFTS.common.FuzzySet.fuzzyfy_instance">fuzzyfy_instance() (in module pyFTS.common.FuzzySet)</a>
 
       <ul>
         <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.common.fuzzyfy_instance">(in module pyFTS.models.multivariate.common)</a>
 </li>
       </ul></li>
+      <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.common.fuzzyfy_instance_clustered">fuzzyfy_instance_clustered() (in module pyFTS.models.multivariate.common)</a>
+</li>
       <li><a href="pyFTS.common.html#pyFTS.common.FuzzySet.fuzzyfy_instances">fuzzyfy_instances() (in module pyFTS.common.FuzzySet)</a>
 </li>
       <li><a href="pyFTS.common.html#pyFTS.common.FuzzySet.fuzzyfy_series">fuzzyfy_series() (in module pyFTS.common.FuzzySet)</a>
@@ -677,7 +719,9 @@
       <ul>
         <li><a href="pyFTS.models.html#pyFTS.models.ismailefendi.ImprovedWeightedFTS.generate_flrg">(pyFTS.models.ismailefendi.ImprovedWeightedFTS method)</a>
 </li>
-        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_flrg">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_flrg">[1]</a>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_flrg">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>
+</li>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.generate_flrg">(pyFTS.models.multivariate.wmvfts.WeightedMVFTS method)</a>
 </li>
         <li><a href="pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS.generate_flrg">(pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS method)</a>
 </li>
@@ -698,7 +742,9 @@
       </ul></li>
       <li><a href="pyFTS.models.html#pyFTS.models.yu.WeightedFTS.generate_FLRG">generate_FLRG() (pyFTS.models.yu.WeightedFTS method)</a>
 </li>
-      <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_flrs">generate_flrs() (pyFTS.models.multivariate.mvfts.MVFTS method)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_flrs">[1]</a>
+      <li><a href="pyFTS.models.html#pyFTS.models.hofts.HighOrderFTS.generate_flrg_fuzzyfied">generate_flrg_fuzzyfied() (pyFTS.models.hofts.HighOrderFTS method)</a>
+</li>
+      <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_flrs">generate_flrs() (pyFTS.models.multivariate.mvfts.MVFTS method)</a>
 </li>
       <li><a href="pyFTS.data.html#pyFTS.data.artificial.generate_gaussian_linear">generate_gaussian_linear() (in module pyFTS.data.artificial)</a>
 </li>
@@ -712,7 +758,13 @@
         <li><a href="pyFTS.models.html#pyFTS.models.pwfts.ProbabilisticWeightedFTS.generate_lhs_flrg">(pyFTS.models.pwfts.ProbabilisticWeightedFTS method)</a>
 </li>
       </ul></li>
-      <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_lhs_flrs">generate_lhs_flrs() (pyFTS.models.multivariate.mvfts.MVFTS method)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_lhs_flrs">[1]</a>
+      <li><a href="pyFTS.models.html#pyFTS.models.hofts.HighOrderFTS.generate_lhs_flrg_fuzzyfied">generate_lhs_flrg_fuzzyfied() (pyFTS.models.hofts.HighOrderFTS method)</a>
+
+      <ul>
+        <li><a href="pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFTS.generate_lhs_flrg_fuzzyfied">(pyFTS.models.hofts.WeightedHighOrderFTS method)</a>
+</li>
+      </ul></li>
+      <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.generate_lhs_flrs">generate_lhs_flrs() (pyFTS.models.multivariate.mvfts.MVFTS method)</a>
 </li>
       <li><a href="pyFTS.common.html#pyFTS.common.FLR.generate_non_recurrent_flrs">generate_non_recurrent_flrs() (in module pyFTS.common.FLR)</a>
 </li>
@@ -897,6 +949,10 @@
       <li><a href="pyFTS.common.html#pyFTS.common.flrg.FLRG.get_midpoint">get_midpoint() (pyFTS.common.flrg.FLRG method)</a>
 
       <ul>
+        <li><a href="pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFLRG.get_midpoint">(pyFTS.models.hofts.WeightedHighOrderFLRG method)</a>
+</li>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_midpoint">(pyFTS.models.multivariate.wmvfts.WeightedFLRG method)</a>
+</li>
         <li><a href="pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.common.FuzzySet.get_midpoint">(pyFTS.models.nonstationary.common.FuzzySet method)</a>
 </li>
         <li><a href="pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.flrg.NonStationaryFLRG.get_midpoint">(pyFTS.models.nonstationary.flrg.NonStationaryFLRG method)</a>
@@ -921,6 +977,8 @@
       <li><a href="pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS.get_point">get_point() (pyFTS.models.ensemble.ensemble.EnsembleFTS method)</a>
 </li>
       <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.get_point_methods">get_point_methods() (in module pyFTS.benchmarks.benchmarks)</a>
+</li>
+      <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.get_point_multivariate_methods">get_point_multivariate_methods() (in module pyFTS.benchmarks.benchmarks)</a>
 </li>
       <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.Measures.get_point_statistics">get_point_statistics() (in module pyFTS.benchmarks.Measures)</a>
 </li>
@@ -1045,6 +1103,8 @@
       <li><a href="pyFTS.common.html#pyFTS.common.SortedCollection.SortedCollection.insert">insert() (pyFTS.common.SortedCollection.SortedCollection method)</a>
 </li>
       <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.Util.insert_benchmark">insert_benchmark() (in module pyFTS.benchmarks.Util)</a>
+</li>
+      <li><a href="pyFTS.hyperparam.html#pyFTS.hyperparam.Util.insert_hyperparam">insert_hyperparam() (in module pyFTS.hyperparam.Util)</a>
 </li>
       <li><a href="pyFTS.common.html#pyFTS.common.SortedCollection.SortedCollection.insert_right">insert_right() (pyFTS.common.SortedCollection.SortedCollection method)</a>
 </li>
@@ -1160,6 +1220,8 @@
         <li><a href="pyFTS.common.html#pyFTS.common.Composite.FuzzySet.membership">(pyFTS.common.Composite.FuzzySet method)</a>
 </li>
         <li><a href="pyFTS.common.html#pyFTS.common.FuzzySet.FuzzySet.membership">(pyFTS.common.FuzzySet.FuzzySet method)</a>
+</li>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.common.MultivariateFuzzySet.membership">(pyFTS.models.multivariate.common.MultivariateFuzzySet method)</a>
 </li>
         <li><a href="pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.common.FuzzySet.membership">(pyFTS.models.nonstationary.common.FuzzySet method)</a>
 </li>
@@ -1167,6 +1229,8 @@
       <li><a href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner.membership_function">membership_function (pyFTS.partitioners.partitioner.Partitioner attribute)</a>
 </li>
       <li><a href="pyFTS.common.html#pyFTS.common.fts.FTS.merge">merge() (pyFTS.common.fts.FTS method)</a>
+</li>
+      <li><a href="pyFTS.hyperparam.html#pyFTS.hyperparam.GridSearch.metodo_cluster">metodo_cluster() (in module pyFTS.hyperparam.GridSearch)</a>
 </li>
       <li><a href="pyFTS.common.html#pyFTS.common.FuzzySet.FuzzySet.mf">mf (pyFTS.common.FuzzySet.FuzzySet attribute)</a>
 </li>
@@ -1185,14 +1249,20 @@
       <li><a href="pyFTS.models.seasonal.html#pyFTS.models.seasonal.common.DateTime.minute_of_year">minute_of_year (pyFTS.models.seasonal.common.DateTime attribute)</a>
 </li>
       <li><a href="pyFTS.models.incremental.html#pyFTS.models.incremental.Retrainer.Retrainer.model">model (pyFTS.models.incremental.Retrainer.Retrainer attribute)</a>
+
+      <ul>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.model">(pyFTS.models.multivariate.cmvfts.ClusteredMVFTS attribute)</a>
 </li>
+      </ul></li>
       <li><a href="pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS.models">models (pyFTS.models.ensemble.ensemble.EnsembleFTS attribute)</a>
 </li>
       <li><a href="pyFTS.models.seasonal.html#pyFTS.models.seasonal.common.DateTime.month">month (pyFTS.models.seasonal.common.DateTime attribute)</a>
 </li>
       <li><a href="pyFTS.models.seasonal.html#pyFTS.models.seasonal.msfts.MultiSeasonalFTS">MultiSeasonalFTS (class in pyFTS.models.seasonal.msfts)</a>
 </li>
-      <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS">MVFTS (class in pyFTS.models.multivariate.mvfts)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS">[1]</a>
+      <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.common.MultivariateFuzzySet">MultivariateFuzzySet (class in pyFTS.models.multivariate.common)</a>
+</li>
+      <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS">MVFTS (class in pyFTS.models.multivariate.mvfts)</a>
 </li>
   </ul></td>
 </tr></table>
@@ -1229,17 +1299,19 @@
 <table style="width: 100%" class="indextable genindextable"><tr>
   <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.Util.open_benchmark_db">open_benchmark_db() (in module pyFTS.benchmarks.Util)</a>
+</li>
+      <li><a href="pyFTS.hyperparam.html#pyFTS.hyperparam.Util.open_hyperparam_db">open_hyperparam_db() (in module pyFTS.hyperparam.Util)</a>
 </li>
       <li><a href="pyFTS.models.html#pyFTS.models.song.ConventionalFTS.operation_matrix">operation_matrix() (pyFTS.models.song.ConventionalFTS method)</a>
 </li>
+  </ul></td>
+  <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="pyFTS.common.html#pyFTS.common.flrg.FLRG.order">order (pyFTS.common.flrg.FLRG attribute)</a>
 
       <ul>
         <li><a href="pyFTS.common.html#pyFTS.common.fts.FTS.order">(pyFTS.common.fts.FTS attribute)</a>
 </li>
       </ul></li>
-  </ul></td>
-  <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="pyFTS.common.html#pyFTS.common.fts.FTS.original_max">original_max (pyFTS.common.fts.FTS attribute)</a>
 </li>
       <li><a href="pyFTS.common.html#pyFTS.common.fts.FTS.original_min">original_min (pyFTS.common.fts.FTS attribute)</a>
@@ -1432,12 +1504,12 @@
 </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>
 </li>
+  </ul></td>
+  <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="pyFTS.common.html#module-pyFTS.common.FLR">pyFTS.common.FLR (module)</a>
 </li>
       <li><a href="pyFTS.common.html#module-pyFTS.common.flrg">pyFTS.common.flrg (module)</a>
@@ -1503,6 +1575,12 @@
       <li><a href="pyFTS.data.html#module-pyFTS.data.sunspots">pyFTS.data.sunspots (module)</a>
 </li>
       <li><a href="pyFTS.data.html#module-pyFTS.data.TAIEX">pyFTS.data.TAIEX (module)</a>
+</li>
+      <li><a href="pyFTS.hyperparam.html#module-pyFTS.hyperparam">pyFTS.hyperparam (module)</a>
+</li>
+      <li><a href="pyFTS.hyperparam.html#module-pyFTS.hyperparam.GridSearch">pyFTS.hyperparam.GridSearch (module)</a>
+</li>
+      <li><a href="pyFTS.hyperparam.html#module-pyFTS.hyperparam.Util">pyFTS.hyperparam.Util (module)</a>
 </li>
       <li><a href="pyFTS.models.html#module-pyFTS.models">pyFTS.models (module)</a>
 </li>
@@ -1529,6 +1607,8 @@
       <li><a href="pyFTS.models.html#module-pyFTS.models.ismailefendi">pyFTS.models.ismailefendi (module)</a>
 </li>
       <li><a href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate">pyFTS.models.multivariate (module)</a>
+</li>
+      <li><a href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.cmvfts">pyFTS.models.multivariate.cmvfts (module)</a>
 </li>
       <li><a href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.common">pyFTS.models.multivariate.common (module)</a>
 </li>
@@ -1536,9 +1616,11 @@
 </li>
       <li><a href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.flrg">pyFTS.models.multivariate.flrg (module)</a>
 </li>
-      <li><a href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.mvfts">pyFTS.models.multivariate.mvfts (module)</a>, <a href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.mvfts">[1]</a>
+      <li><a href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.mvfts">pyFTS.models.multivariate.mvfts (module)</a>
 </li>
       <li><a href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.variable">pyFTS.models.multivariate.variable (module)</a>
+</li>
+      <li><a href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.wmvfts">pyFTS.models.multivariate.wmvfts (module)</a>
 </li>
       <li><a href="pyFTS.models.nonstationary.html#module-pyFTS.models.nonstationary">pyFTS.models.nonstationary (module)</a>
 </li>
@@ -1809,7 +1891,9 @@
 </li>
         <li><a href="pyFTS.models.html#pyFTS.models.ismailefendi.ImprovedWeightedFTS.train">(pyFTS.models.ismailefendi.ImprovedWeightedFTS method)</a>
 </li>
-        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.train">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>, <a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.train">[1]</a>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.train">(pyFTS.models.multivariate.cmvfts.ClusteredMVFTS method)</a>
+</li>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.train">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>
 </li>
         <li><a href="pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS.train">(pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS method)</a>
 </li>
@@ -1863,6 +1947,8 @@
       <li><a href="pyFTS.common.html#pyFTS.common.FuzzySet.FuzzySet.type">type (pyFTS.common.FuzzySet.FuzzySet attribute)</a>
 
       <ul>
+        <li><a href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner.type">(pyFTS.partitioners.partitioner.Partitioner attribute)</a>
+</li>
         <li><a href="pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.type">(pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution attribute)</a>
 </li>
       </ul></li>
@@ -1906,10 +1992,14 @@
   <td style="width: 33%; vertical-align: top;"><ul>
       <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.variable.Variable">Variable (class in pyFTS.models.multivariate.variable)</a>
 </li>
+      <li><a href="pyFTS.common.html#pyFTS.common.FuzzySet.FuzzySet.variable">variable (pyFTS.common.FuzzySet.FuzzySet attribute)</a>
+
+      <ul>
+        <li><a href="pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner.variable">(pyFTS.partitioners.partitioner.Partitioner attribute)</a>
+</li>
+      </ul></li>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="pyFTS.common.html#pyFTS.common.FuzzySet.FuzzySet.variable">variable (pyFTS.common.FuzzySet.FuzzySet attribute)</a>
-</li>
       <li><a href="pyFTS.models.html#pyFTS.models.pwfts.visualize_distributions">visualize_distributions() (in module pyFTS.models.pwfts)</a>
 </li>
   </ul></td>
@@ -1918,14 +2008,28 @@
 <h2 id="W">W</h2>
 <table style="width: 100%" class="indextable genindextable"><tr>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="pyFTS.models.html#pyFTS.models.yu.WeightedFLRG">WeightedFLRG (class in pyFTS.models.yu)</a>
+      <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.wmvfts.WeightedFLRG">WeightedFLRG (class in pyFTS.models.multivariate.wmvfts)</a>
+
+      <ul>
+        <li><a href="pyFTS.models.html#pyFTS.models.yu.WeightedFLRG">(class in pyFTS.models.yu)</a>
 </li>
+      </ul></li>
       <li><a href="pyFTS.models.html#pyFTS.models.yu.WeightedFTS">WeightedFTS (class in pyFTS.models.yu)</a>
+</li>
+      <li><a href="pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFLRG">WeightedHighOrderFLRG (class in pyFTS.models.hofts)</a>
+</li>
+      <li><a href="pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFTS">WeightedHighOrderFTS (class in pyFTS.models.hofts)</a>
+</li>
+      <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.wmvfts.WeightedMVFTS">WeightedMVFTS (class in pyFTS.models.multivariate.wmvfts)</a>
 </li>
       <li><a href="pyFTS.models.html#pyFTS.models.cheng.TrendWeightedFLRG.weights">weights() (pyFTS.models.cheng.TrendWeightedFLRG method)</a>
 
       <ul>
+        <li><a href="pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFLRG.weights">(pyFTS.models.hofts.WeightedHighOrderFLRG method)</a>
+</li>
         <li><a href="pyFTS.models.html#pyFTS.models.ismailefendi.ImprovedWeightedFLRG.weights">(pyFTS.models.ismailefendi.ImprovedWeightedFLRG method)</a>
+</li>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.wmvfts.WeightedFLRG.weights">(pyFTS.models.multivariate.wmvfts.WeightedFLRG method)</a>
 </li>
         <li><a href="pyFTS.models.html#pyFTS.models.sadaei.ExponentialyWeightedFLRG.weights">(pyFTS.models.sadaei.ExponentialyWeightedFLRG method)</a>
 </li>

docs/build/html/modules.html

@@ -153,6 +153,13 @@
 <li class="toctree-l4"><a class="reference internal" href="pyFTS.data.html#module-pyFTS.data.sunspots">Sunspots dataset</a></li>
 </ul>
 </li>
+<li class="toctree-l3"><a class="reference internal" href="pyFTS.hyperparam.html">pyFTS.hyperparam package</a><ul>
+<li class="toctree-l4"><a class="reference internal" href="pyFTS.hyperparam.html#module-pyFTS.hyperparam">Module contents</a></li>
+<li class="toctree-l4"><a class="reference internal" href="pyFTS.hyperparam.html#submodules">Submodules</a></li>
+<li class="toctree-l4"><a class="reference internal" href="pyFTS.hyperparam.html#module-pyFTS.hyperparam.Util">pyFTS.hyperparam.Util module</a></li>
+<li class="toctree-l4"><a class="reference internal" href="pyFTS.hyperparam.html#pyfts-hyperparam-gridsearch-module">pyFTS.hyperparam.GridSearch module</a></li>
+</ul>
+</li>
 <li class="toctree-l3"><a class="reference internal" href="pyFTS.models.html">pyFTS.models package</a><ul>
 <li class="toctree-l4"><a class="reference internal" href="pyFTS.models.html#module-pyFTS.models">Module contents</a></li>
 <li class="toctree-l4"><a class="reference internal" href="pyFTS.models.html#subpackages">Subpackages</a></li>

docs/build/html/py-modindex.html

@@ -310,6 +310,21 @@
        <td>&#160;&#160;&#160;
        <a href="pyFTS.data.html#module-pyFTS.data.TAIEX"><code class="xref">pyFTS.data.TAIEX</code></a></td><td>
        <em></em></td></tr>
+     <tr class="cg-1">
+       <td></td>
+       <td>&#160;&#160;&#160;
+       <a href="pyFTS.hyperparam.html#module-pyFTS.hyperparam"><code class="xref">pyFTS.hyperparam</code></a></td><td>
+       <em></em></td></tr>
+     <tr class="cg-1">
+       <td></td>
+       <td>&#160;&#160;&#160;
+       <a href="pyFTS.hyperparam.html#module-pyFTS.hyperparam.GridSearch"><code class="xref">pyFTS.hyperparam.GridSearch</code></a></td><td>
+       <em></em></td></tr>
+     <tr class="cg-1">
+       <td></td>
+       <td>&#160;&#160;&#160;
+       <a href="pyFTS.hyperparam.html#module-pyFTS.hyperparam.Util"><code class="xref">pyFTS.hyperparam.Util</code></a></td><td>
+       <em></em></td></tr>
      <tr class="cg-1">
        <td></td>
        <td>&#160;&#160;&#160;
@@ -375,6 +390,11 @@
        <td>&#160;&#160;&#160;
        <a href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate"><code class="xref">pyFTS.models.multivariate</code></a></td><td>
        <em></em></td></tr>
+     <tr class="cg-1">
+       <td></td>
+       <td>&#160;&#160;&#160;
+       <a href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.cmvfts"><code class="xref">pyFTS.models.multivariate.cmvfts</code></a></td><td>
+       <em></em></td></tr>
      <tr class="cg-1">
        <td></td>
        <td>&#160;&#160;&#160;
@@ -400,6 +420,11 @@
        <td>&#160;&#160;&#160;
        <a href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.variable"><code class="xref">pyFTS.models.multivariate.variable</code></a></td><td>
        <em></em></td></tr>
+     <tr class="cg-1">
+       <td></td>
+       <td>&#160;&#160;&#160;
+       <a href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.wmvfts"><code class="xref">pyFTS.models.multivariate.wmvfts</code></a></td><td>
+       <em></em></td></tr>
      <tr class="cg-1">
        <td></td>
        <td>&#160;&#160;&#160;

docs/build/html/pyFTS.benchmarks.html

@@ -167,6 +167,12 @@
 <dd><p>Return all FTS methods for point forecasting</p>
 </dd></dl>
 
+<dl class="function">
+<dt id="pyFTS.benchmarks.benchmarks.get_point_multivariate_methods">
+<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">get_point_multivariate_methods</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#get_point_multivariate_methods"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.get_point_multivariate_methods" title="Permalink to this definition">¶</a></dt>
+<dd><p>Return all multivariate FTS methods por point forecasting</p>
+</dd></dl>
+
 <dl class="function">
 <dt id="pyFTS.benchmarks.benchmarks.get_probabilistic_methods">
 <code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">get_probabilistic_methods</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#get_probabilistic_methods"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.get_probabilistic_methods" title="Permalink to this definition">¶</a></dt>

docs/build/html/pyFTS.common.html

@@ -125,7 +125,7 @@
 <p>Composite Fuzzy Sets</p>
 <dl class="class">
 <dt id="pyFTS.common.Composite.FuzzySet">
-<em class="property">class </em><code class="descclassname">pyFTS.common.Composite.</code><code class="descname">FuzzySet</code><span class="sig-paren">(</span><em>name</em>, <em>superset=False</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/Composite.html#FuzzySet"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.common.Composite.FuzzySet" title="Permalink to this definition">¶</a></dt>
+<em class="property">class </em><code class="descclassname">pyFTS.common.Composite.</code><code class="descname">FuzzySet</code><span class="sig-paren">(</span><em>name</em>, <em>superset=False</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/Composite.html#FuzzySet"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.common.Composite.FuzzySet" title="Permalink to this definition">¶</a></dt>
 <dd><p>Bases: <a class="reference internal" href="#pyFTS.common.FuzzySet.FuzzySet" title="pyFTS.common.FuzzySet.FuzzySet"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.FuzzySet.FuzzySet</span></code></a></p>
 <p>Composite Fuzzy Set</p>
 <dl class="method">
@@ -1611,7 +1611,7 @@ when the LHS pattern is identified on time t.</p>
 <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
 <li><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</li>
 <li><strong>steps</strong> – the number of steps ahead to forecast</li>
-<li><strong>kwargs</strong> – model specific parameters</li>
+<li><strong>start</strong> – in the multi step forecasting, the index of the data where to start forecasting</li>
 </ul>
 </td>
 </tr>
@@ -1851,6 +1851,9 @@ needed to forecast a single step ahead</p>
 <li><strong>distributed</strong> – boolean, indicate if the forecasting procedure will be distributed in a dispy cluster</li>
 <li><strong>nodes</strong> – a list with the dispy cluster nodes addresses</li>
 <li><strong>explain</strong> – try to explain, step by step, the one-step-ahead point forecasting result given the input data.</li>
+<li><strong>generators</strong> – for multivariate methods on multi step ahead forecasting, generators is a dict where the keys
+are the variables names (except the target_variable) and the values are lambda functions that
+accept one value (the actual value of the variable) and return the next value.</li>
 </ul>
 </td>
 </tr>

docs/build/html/pyFTS.html

@@ -165,6 +165,13 @@
 <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.hyperparam.html">pyFTS.hyperparam package</a><ul>
+<li class="toctree-l2"><a class="reference internal" href="pyFTS.hyperparam.html#module-pyFTS.hyperparam">Module contents</a></li>
+<li class="toctree-l2"><a class="reference internal" href="pyFTS.hyperparam.html#submodules">Submodules</a></li>
+<li class="toctree-l2"><a class="reference internal" href="pyFTS.hyperparam.html#module-pyFTS.hyperparam.Util">pyFTS.hyperparam.Util module</a></li>
+<li class="toctree-l2"><a class="reference internal" href="pyFTS.hyperparam.html#module-pyFTS.hyperparam.GridSearch">pyFTS.hyperparam.GridSearch module</a></li>
+</ul>
+</li>
 <li class="toctree-l1"><a class="reference internal" href="pyFTS.models.html">pyFTS.models package</a><ul>
 <li class="toctree-l2"><a class="reference internal" href="pyFTS.models.html#module-pyFTS.models">Module contents</a></li>
 <li class="toctree-l2"><a class="reference internal" href="pyFTS.models.html#subpackages">Subpackages</a><ul>
@@ -182,13 +189,15 @@
 </ul>
 </li>
 <li class="toctree-l3"><a class="reference internal" href="pyFTS.models.multivariate.html">pyFTS.models.multivariate package</a><ul>
+<li class="toctree-l4"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate">Module contents</a></li>
 <li class="toctree-l4"><a class="reference internal" href="pyFTS.models.multivariate.html#submodules">Submodules</a></li>
 <li class="toctree-l4"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.FLR">pyFTS.models.multivariate.FLR module</a></li>
 <li class="toctree-l4"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.common">pyFTS.models.multivariate.common module</a></li>
+<li class="toctree-l4"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.variable">pyFTS.models.multivariate.variable module</a></li>
 <li class="toctree-l4"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.flrg">pyFTS.models.multivariate.flrg module</a></li>
 <li class="toctree-l4"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.mvfts">pyFTS.models.multivariate.mvfts module</a></li>
-<li class="toctree-l4"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.variable">pyFTS.models.multivariate.variable module</a></li>
+<li class="toctree-l4"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.wmvfts">pyFTS.models.multivariate.wmvfts module</a></li>
-<li class="toctree-l4"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate">Module contents</a></li>
+<li class="toctree-l4"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.cmvfts">pyFTS.models.multivariate.cmvfts module</a></li>
 </ul>
 </li>
 <li class="toctree-l3"><a class="reference internal" href="pyFTS.models.nonstationary.html">pyFTS.models.nonstationary package</a><ul>
@@ -239,7 +248,7 @@
 <li class="toctree-l2"><a class="reference internal" href="pyFTS.partitioners.html#module-pyFTS.partitioners.FCM">pyFTS.partitioners.FCM module</a></li>
 <li class="toctree-l2"><a class="reference internal" href="pyFTS.partitioners.html#module-pyFTS.partitioners.Grid">pyFTS.partitioners.Grid module</a></li>
 <li class="toctree-l2"><a class="reference internal" href="pyFTS.partitioners.html#module-pyFTS.partitioners.Huarng">pyFTS.partitioners.Huarng module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="pyFTS.partitioners.html#pyfts-partitioners-singleton-module">pyFTS.partitioners.Singleton module</a></li>
+<li class="toctree-l2"><a class="reference internal" href="pyFTS.partitioners.html#module-pyFTS.partitioners.Singleton">pyFTS.partitioners.Singleton module</a></li>
 <li class="toctree-l2"><a class="reference internal" href="pyFTS.partitioners.html#module-pyFTS.partitioners.Util">pyFTS.partitioners.Util module</a></li>
 <li class="toctree-l2"><a class="reference internal" href="pyFTS.partitioners.html#module-pyFTS.partitioners.parallel_util">pyFTS.partitioners.parallel_util module</a></li>
 </ul>

docs/build/html/pyFTS.hyperparam.html

@@ -0,0 +1,236 @@
+
+
+<!doctype html>
+
+<html xmlns="http://www.w3.org/1999/xhtml">
+  <head>
+    <meta http-equiv="X-UA-Compatible" content="IE=Edge" />
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+        ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
+        var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
+      })();
+    </script>
+    <title>pyFTS.hyperparam package &#8212; pyFTS 1.2.3 documentation</title>
+    <link rel="stylesheet" href="_static/bizstyle.css" type="text/css" />
+    <link rel="stylesheet" href="_static/pygments.css" type="text/css" />
+    <script type="text/javascript" src="_static/documentation_options.js"></script>
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+    <script type="text/javascript" src="_static/doctools.js"></script>
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+    <script type="text/javascript" src="_static/bizstyle.js"></script>
+    <link rel="index" title="Index" href="genindex.html" />
+    <link rel="search" title="Search" href="search.html" />
+    <link rel="next" title="pyFTS.models package" href="pyFTS.models.html" />
+    <link rel="prev" title="pyFTS.data package" href="pyFTS.data.html" />
+    <meta name="viewport" content="width=device-width,initial-scale=1.0">
+    <!--[if lt IE 9]>
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+    <![endif]-->
+  </head><body>
+    <div class="related" role="navigation" aria-label="related navigation">
+      <h3>Navigation</h3>
+      <ul>
+        <li class="right" style="margin-right: 10px">
+          <a href="genindex.html" title="General Index"
+             accesskey="I">index</a></li>
+        <li class="right" >
+          <a href="py-modindex.html" title="Python Module Index"
+             >modules</a> |</li>
+        <li class="right" >
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+             accesskey="N">next</a> |</li>
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+             accesskey="P">previous</a> |</li>
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+          <li class="nav-item nav-item-2"><a href="pyFTS.html" accesskey="U">pyFTS package</a> &#187;</li> 
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+            <p class="logo"><a href="index.html">
+              <img class="logo" src="_static/logo_heading2.png" alt="Logo"/>
+            </a></p>
+  <h3><a href="index.html">Table Of Contents</a></h3>
+  <ul>
+<li><a class="reference internal" href="#">pyFTS.hyperparam package</a><ul>
+<li><a class="reference internal" href="#module-pyFTS.hyperparam">Module contents</a></li>
+<li><a class="reference internal" href="#submodules">Submodules</a></li>
+<li><a class="reference internal" href="#module-pyFTS.hyperparam.Util">pyFTS.hyperparam.Util module</a></li>
+<li><a class="reference internal" href="#module-pyFTS.hyperparam.GridSearch">pyFTS.hyperparam.GridSearch module</a></li>
+</ul>
+</li>
+</ul>
+
+  <h4>Previous topic</h4>
+  <p class="topless"><a href="pyFTS.data.html"
+                        title="previous chapter">pyFTS.data package</a></p>
+  <h4>Next topic</h4>
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+                        title="next chapter">pyFTS.models package</a></p>
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+    <h3>This Page</h3>
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+            rel="nofollow">Show Source</a></li>
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+  <h3>Quick search</h3>
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+        <div class="bodywrapper">
+          <div class="body" role="main">
+            
+  <div class="section" id="pyfts-hyperparam-package">
+<h1>pyFTS.hyperparam package<a class="headerlink" href="#pyfts-hyperparam-package" title="Permalink to this headline">¶</a></h1>
+<div class="section" id="module-pyFTS.hyperparam">
+<span id="module-contents"></span><h2>Module contents<a class="headerlink" href="#module-pyFTS.hyperparam" title="Permalink to this headline">¶</a></h2>
+</div>
+<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.hyperparam.Util">
+<span id="pyfts-hyperparam-util-module"></span><h2>pyFTS.hyperparam.Util module<a class="headerlink" href="#module-pyFTS.hyperparam.Util" title="Permalink to this headline">¶</a></h2>
+<p>Common facilities for hyperparameter tunning</p>
+<dl class="function">
+<dt id="pyFTS.hyperparam.Util.create_hyperparam_tables">
+<code class="descclassname">pyFTS.hyperparam.Util.</code><code class="descname">create_hyperparam_tables</code><span class="sig-paren">(</span><em>conn</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/hyperparam/Util.html#create_hyperparam_tables"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.hyperparam.Util.create_hyperparam_tables" title="Permalink to this definition">¶</a></dt>
+<dd><p>Create a sqlite3 table designed to store benchmark results.</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"><strong>conn</strong> – a sqlite3 database connection</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="function">
+<dt id="pyFTS.hyperparam.Util.insert_hyperparam">
+<code class="descclassname">pyFTS.hyperparam.Util.</code><code class="descname">insert_hyperparam</code><span class="sig-paren">(</span><em>data</em>, <em>conn</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/hyperparam/Util.html#insert_hyperparam"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.hyperparam.Util.insert_hyperparam" title="Permalink to this definition">¶</a></dt>
+<dd><p>Insert benchmark data on database</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"><strong>data</strong> – a tuple with the benchmark data with format:</td>
+</tr>
+</tbody>
+</table>
+<p>Dataset: Identify on which dataset the dataset was performed
+Tag: a user defined word that indentify a benchmark set
+Model: FTS model
+Transformation: The name of data transformation, if one was used
+mf: membership function
+Order: the order of the FTS method
+Partitioner: UoD partitioning scheme
+Partitions: Number of partitions
+alpha: alpha cut
+lags: lags
+Measure: accuracy measure
+Value: the measure value</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"><strong>conn</strong> – a sqlite3 database connection</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"></td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="function">
+<dt id="pyFTS.hyperparam.Util.open_hyperparam_db">
+<code class="descclassname">pyFTS.hyperparam.Util.</code><code class="descname">open_hyperparam_db</code><span class="sig-paren">(</span><em>name</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/hyperparam/Util.html#open_hyperparam_db"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.hyperparam.Util.open_hyperparam_db" title="Permalink to this definition">¶</a></dt>
+<dd><p>Open a connection with a Sqlite database designed to store benchmark results.</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"><strong>name</strong> – database filenem</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">a sqlite3 database connection</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+</div>
+<div class="section" id="module-pyFTS.hyperparam.GridSearch">
+<span id="pyfts-hyperparam-gridsearch-module"></span><h2>pyFTS.hyperparam.GridSearch module<a class="headerlink" href="#module-pyFTS.hyperparam.GridSearch" title="Permalink to this headline">¶</a></h2>
+<dl class="function">
+<dt id="pyFTS.hyperparam.GridSearch.dict_individual">
+<code class="descclassname">pyFTS.hyperparam.GridSearch.</code><code class="descname">dict_individual</code><span class="sig-paren">(</span><em>mf</em>, <em>partitioner</em>, <em>partitions</em>, <em>order</em>, <em>lags</em>, <em>alpha_cut</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/hyperparam/GridSearch.html#dict_individual"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.hyperparam.GridSearch.dict_individual" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="function">
+<dt id="pyFTS.hyperparam.GridSearch.execute">
+<code class="descclassname">pyFTS.hyperparam.GridSearch.</code><code class="descname">execute</code><span class="sig-paren">(</span><em>hyperparams</em>, <em>datasetname</em>, <em>train</em>, <em>test</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/hyperparam/GridSearch.html#execute"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.hyperparam.GridSearch.execute" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="function">
+<dt id="pyFTS.hyperparam.GridSearch.metodo_cluster">
+<code class="descclassname">pyFTS.hyperparam.GridSearch.</code><code class="descname">metodo_cluster</code><span class="sig-paren">(</span><em>individual</em>, <em>train</em>, <em>test</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/hyperparam/GridSearch.html#metodo_cluster"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.hyperparam.GridSearch.metodo_cluster" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+</div>
+</div>
+
+
+          </div>
+        </div>
+      </div>
+      <div class="clearer"></div>
+    </div>
+    <div class="related" role="navigation" aria-label="related navigation">
+      <h3>Navigation</h3>
+      <ul>
+        <li class="right" style="margin-right: 10px">
+          <a href="genindex.html" title="General Index"
+             >index</a></li>
+        <li class="right" >
+          <a href="py-modindex.html" title="Python Module Index"
+             >modules</a> |</li>
+        <li class="right" >
+          <a href="pyFTS.models.html" title="pyFTS.models package"
+             >next</a> |</li>
+        <li class="right" >
+          <a href="pyFTS.data.html" title="pyFTS.data package"
+             >previous</a> |</li>
+        <li class="nav-item nav-item-0"><a href="index.html">pyFTS 1.2.3 documentation</a> &#187;</li>
+          <li class="nav-item nav-item-1"><a href="modules.html" >pyFTS</a> &#187;</li>
+          <li class="nav-item nav-item-2"><a href="pyFTS.html" >pyFTS package</a> &#187;</li> 
+      </ul>
+    </div>
+    <div class="footer" role="contentinfo">
+        &#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
+      Created using <a href="http://sphinx-doc.org/">Sphinx</a> 1.7.2.
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+  </body>
+</html>

docs/build/html/pyFTS.models.html

@@ -29,7 +29,7 @@
     <link rel="index" title="Index" href="genindex.html" />
     <link rel="search" title="Search" href="search.html" />
     <link rel="next" title="pyFTS.models.ensemble package" href="pyFTS.models.ensemble.html" />
-    <link rel="prev" title="pyFTS.data package" href="pyFTS.data.html" />
+    <link rel="prev" title="pyFTS.hyperparam package" href="pyFTS.hyperparam.html" />
     <meta name="viewport" content="width=device-width,initial-scale=1.0">
     <!--[if lt IE 9]>
     <script type="text/javascript" src="_static/css3-mediaqueries.js"></script>
@@ -48,7 +48,7 @@
           <a href="pyFTS.models.ensemble.html" title="pyFTS.models.ensemble package"
              accesskey="N">next</a> |</li>
         <li class="right" >
-          <a href="pyFTS.data.html" title="pyFTS.data package"
+          <a href="pyFTS.hyperparam.html" title="pyFTS.hyperparam package"
              accesskey="P">previous</a> |</li>
         <li class="nav-item nav-item-0"><a href="index.html">pyFTS 1.2.3 documentation</a> &#187;</li>
           <li class="nav-item nav-item-1"><a href="modules.html" >pyFTS</a> &#187;</li>
@@ -81,8 +81,8 @@
 </ul>
 
   <h4>Previous topic</h4>
-  <p class="topless"><a href="pyFTS.data.html"
+  <p class="topless"><a href="pyFTS.hyperparam.html"
-                        title="previous chapter">pyFTS.data package</a></p>
+                        title="previous chapter">pyFTS.hyperparam package</a></p>
   <h4>Next topic</h4>
   <p class="topless"><a href="pyFTS.models.ensemble.html"
                         title="next chapter">pyFTS.models.ensemble package</a></p>
@@ -141,10 +141,11 @@
 <li class="toctree-l2"><a class="reference internal" href="pyFTS.models.multivariate.html#submodules">Submodules</a></li>
 <li class="toctree-l2"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.FLR">pyFTS.models.multivariate.FLR module</a></li>
 <li class="toctree-l2"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.common">pyFTS.models.multivariate.common module</a></li>
+<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.variable">pyFTS.models.multivariate.variable module</a></li>
 <li class="toctree-l2"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.flrg">pyFTS.models.multivariate.flrg module</a></li>
 <li class="toctree-l2"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.mvfts">pyFTS.models.multivariate.mvfts module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.variable">pyFTS.models.multivariate.variable module</a></li>
+<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.wmvfts">pyFTS.models.multivariate.wmvfts module</a></li>
-<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.multivariate.html#pyfts-models-multivariate-wmvfts-module">pyFTS.models.multivariate.wmvfts module</a></li>
+<li class="toctree-l2"><a class="reference internal" href="pyFTS.models.multivariate.html#module-pyFTS.models.multivariate.cmvfts">pyFTS.models.multivariate.cmvfts module</a></li>
 </ul>
 </li>
 <li class="toctree-l1"><a class="reference internal" href="pyFTS.models.nonstationary.html">pyFTS.models.nonstationary package</a><ul>
@@ -476,11 +477,21 @@ using Fuzzy Time Series. 2017 IEEE International Conference on Fuzzy Systems. DO
 <code class="descname">generate_flrg</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFTS.generate_flrg"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.generate_flrg" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
+<dl class="method">
+<dt id="pyFTS.models.hofts.HighOrderFTS.generate_flrg_fuzzyfied">
+<code class="descname">generate_flrg_fuzzyfied</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFTS.generate_flrg_fuzzyfied"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.generate_flrg_fuzzyfied" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
 <dl class="method">
 <dt id="pyFTS.models.hofts.HighOrderFTS.generate_lhs_flrg">
 <code class="descname">generate_lhs_flrg</code><span class="sig-paren">(</span><em>sample</em>, <em>explain=False</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFTS.generate_lhs_flrg"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.generate_lhs_flrg" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
+<dl class="method">
+<dt id="pyFTS.models.hofts.HighOrderFTS.generate_lhs_flrg_fuzzyfied">
+<code class="descname">generate_lhs_flrg_fuzzyfied</code><span class="sig-paren">(</span><em>sample</em>, <em>explain=False</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFTS.generate_lhs_flrg_fuzzyfied"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.generate_lhs_flrg_fuzzyfied" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
 <dl class="method">
 <dt id="pyFTS.models.hofts.HighOrderFTS.train">
 <code class="descname">train</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#HighOrderFTS.train"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.HighOrderFTS.train" title="Permalink to this definition">¶</a></dt>
@@ -501,6 +512,56 @@ using Fuzzy Time Series. 2017 IEEE International Conference on Fuzzy Systems. DO
 
 </dd></dl>
 
+<dl class="class">
+<dt id="pyFTS.models.hofts.WeightedHighOrderFLRG">
+<em class="property">class </em><code class="descclassname">pyFTS.models.hofts.</code><code class="descname">WeightedHighOrderFLRG</code><span class="sig-paren">(</span><em>order</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#WeightedHighOrderFLRG"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFLRG" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.flrg.FLRG" title="pyFTS.common.flrg.FLRG"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.flrg.FLRG</span></code></a></p>
+<p>Weighted High Order Fuzzy Logical Relationship Group</p>
+<dl class="method">
+<dt id="pyFTS.models.hofts.WeightedHighOrderFLRG.append_lhs">
+<code class="descname">append_lhs</code><span class="sig-paren">(</span><em>c</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#WeightedHighOrderFLRG.append_lhs"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFLRG.append_lhs" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="method">
+<dt id="pyFTS.models.hofts.WeightedHighOrderFLRG.append_rhs">
+<code class="descname">append_rhs</code><span class="sig-paren">(</span><em>fset</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#WeightedHighOrderFLRG.append_rhs"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFLRG.append_rhs" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="method">
+<dt id="pyFTS.models.hofts.WeightedHighOrderFLRG.get_midpoint">
+<code class="descname">get_midpoint</code><span class="sig-paren">(</span><em>sets</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#WeightedHighOrderFLRG.get_midpoint"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFLRG.get_midpoint" title="Permalink to this definition">¶</a></dt>
+<dd><p>Returns the midpoint value for the RHS fuzzy sets</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"><strong>sets</strong> – fuzzy sets</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">the midpoint value</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="method">
+<dt id="pyFTS.models.hofts.WeightedHighOrderFLRG.weights">
+<code class="descname">weights</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#WeightedHighOrderFLRG.weights"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFLRG.weights" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+</dd></dl>
+
+<dl class="class">
+<dt id="pyFTS.models.hofts.WeightedHighOrderFTS">
+<em class="property">class </em><code class="descclassname">pyFTS.models.hofts.</code><code class="descname">WeightedHighOrderFTS</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#WeightedHighOrderFTS"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.hofts.HighOrderFTS" title="pyFTS.models.hofts.HighOrderFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.hofts.HighOrderFTS</span></code></a></p>
+<p>Weighted High Order Fuzzy Time Series</p>
+<dl class="method">
+<dt id="pyFTS.models.hofts.WeightedHighOrderFTS.generate_lhs_flrg_fuzzyfied">
+<code class="descname">generate_lhs_flrg_fuzzyfied</code><span class="sig-paren">(</span><em>sample</em>, <em>explain=False</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/hofts.html#WeightedHighOrderFTS.generate_lhs_flrg_fuzzyfied"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFTS.generate_lhs_flrg_fuzzyfied" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+</dd></dl>
+
 </div>
 <div class="section" id="module-pyFTS.models.hwang">
 <span id="pyfts-models-hwang-module"></span><h2>pyFTS.models.hwang module<a class="headerlink" href="#module-pyFTS.models.hwang" title="Permalink to this headline">¶</a></h2>
@@ -831,7 +892,7 @@ US Dollar to Ringgit Malaysia,” Int. J. Comput. Intell. Appl., vol. 12, no. 1,
 <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
 <li><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</li>
 <li><strong>steps</strong> – the number of steps ahead to forecast</li>
-<li><strong>kwargs</strong> – model specific parameters</li>
+<li><strong>start</strong> – in the multi step forecasting, the index of the data where to start forecasting</li>
 </ul>
 </td>
 </tr>
@@ -1099,7 +1160,7 @@ refined exponentially weighted fuzzy time series and an improved harmony search,
           <a href="pyFTS.models.ensemble.html" title="pyFTS.models.ensemble package"
              >next</a> |</li>
         <li class="right" >
-          <a href="pyFTS.data.html" title="pyFTS.data package"
+          <a href="pyFTS.hyperparam.html" title="pyFTS.hyperparam package"
              >previous</a> |</li>
         <li class="nav-item nav-item-0"><a href="index.html">pyFTS 1.2.3 documentation</a> &#187;</li>
           <li class="nav-item nav-item-1"><a href="modules.html" >pyFTS</a> &#187;</li>

docs/build/html/pyFTS.models.multivariate.html

@@ -68,10 +68,11 @@
 <li><a class="reference internal" href="#submodules">Submodules</a></li>
 <li><a class="reference internal" href="#module-pyFTS.models.multivariate.FLR">pyFTS.models.multivariate.FLR module</a></li>
 <li><a class="reference internal" href="#module-pyFTS.models.multivariate.common">pyFTS.models.multivariate.common module</a></li>
+<li><a class="reference internal" href="#module-pyFTS.models.multivariate.variable">pyFTS.models.multivariate.variable module</a></li>
 <li><a class="reference internal" href="#module-pyFTS.models.multivariate.flrg">pyFTS.models.multivariate.flrg module</a></li>
 <li><a class="reference internal" href="#module-pyFTS.models.multivariate.mvfts">pyFTS.models.multivariate.mvfts module</a></li>
-<li><a class="reference internal" href="#module-pyFTS.models.multivariate.variable">pyFTS.models.multivariate.variable module</a></li>
+<li><a class="reference internal" href="#module-pyFTS.models.multivariate.wmvfts">pyFTS.models.multivariate.wmvfts module</a></li>
-<li><a class="reference internal" href="#pyfts-models-multivariate-wmvfts-module">pyFTS.models.multivariate.wmvfts module</a></li>
+<li><a class="reference internal" href="#module-pyFTS.models.multivariate.cmvfts">pyFTS.models.multivariate.cmvfts module</a></li>
 </ul>
 </li>
 </ul>
@@ -140,11 +141,111 @@
 </div>
 <div class="section" id="module-pyFTS.models.multivariate.common">
 <span id="pyfts-models-multivariate-common-module"></span><h2>pyFTS.models.multivariate.common module<a class="headerlink" href="#module-pyFTS.models.multivariate.common" title="Permalink to this headline">¶</a></h2>
+<dl class="class">
+<dt id="pyFTS.models.multivariate.common.MultivariateFuzzySet">
+<em class="property">class </em><code class="descclassname">pyFTS.models.multivariate.common.</code><code class="descname">MultivariateFuzzySet</code><span class="sig-paren">(</span><em>name</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/common.html#MultivariateFuzzySet"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.common.MultivariateFuzzySet" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.Composite.FuzzySet" title="pyFTS.common.Composite.FuzzySet"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.Composite.FuzzySet</span></code></a></p>
+<p>Multivariate Composite Fuzzy Set</p>
+<dl class="method">
+<dt id="pyFTS.models.multivariate.common.MultivariateFuzzySet.append_set">
+<code class="descname">append_set</code><span class="sig-paren">(</span><em>variable</em>, <em>set</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/common.html#MultivariateFuzzySet.append_set"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.common.MultivariateFuzzySet.append_set" title="Permalink to this definition">¶</a></dt>
+<dd><p>Appends a new fuzzy set from a new variable</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 last simple">
+<li><strong>variable</strong> – an multivariate.variable instance</li>
+<li><strong>set</strong> – an common.FuzzySet instance</li>
+</ul>
+</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="method">
+<dt id="pyFTS.models.multivariate.common.MultivariateFuzzySet.membership">
+<code class="descname">membership</code><span class="sig-paren">(</span><em>x</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/common.html#MultivariateFuzzySet.membership"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.common.MultivariateFuzzySet.membership" title="Permalink to this definition">¶</a></dt>
+<dd><p>Calculate the membership value of a given input</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"><strong>x</strong> – input value</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">membership value of x at this fuzzy set</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+</dd></dl>
+
 <dl class="function">
 <dt id="pyFTS.models.multivariate.common.fuzzyfy_instance">
 <code class="descclassname">pyFTS.models.multivariate.common.</code><code class="descname">fuzzyfy_instance</code><span class="sig-paren">(</span><em>data_point</em>, <em>var</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/common.html#fuzzyfy_instance"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.common.fuzzyfy_instance" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
+<dl class="function">
+<dt id="pyFTS.models.multivariate.common.fuzzyfy_instance_clustered">
+<code class="descclassname">pyFTS.models.multivariate.common.</code><code class="descname">fuzzyfy_instance_clustered</code><span class="sig-paren">(</span><em>data_point</em>, <em>cluster</em>, <em>alpha_cut=0.0</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/common.html#fuzzyfy_instance_clustered"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.common.fuzzyfy_instance_clustered" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+</div>
+<div class="section" id="module-pyFTS.models.multivariate.variable">
+<span id="pyfts-models-multivariate-variable-module"></span><h2>pyFTS.models.multivariate.variable module<a class="headerlink" href="#module-pyFTS.models.multivariate.variable" title="Permalink to this headline">¶</a></h2>
+<dl class="class">
+<dt id="pyFTS.models.multivariate.variable.Variable">
+<em class="property">class </em><code class="descclassname">pyFTS.models.multivariate.variable.</code><code class="descname">Variable</code><span class="sig-paren">(</span><em>name</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/variable.html#Variable"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable" title="Permalink to this definition">¶</a></dt>
+<dd><p>Bases: <a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.7)"><code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></a></p>
+<p>A variable of a fuzzy time series multivariate model. Each variable contains its own
+transformations and partitioners.</p>
+<dl class="attribute">
+<dt id="pyFTS.models.multivariate.variable.Variable.alias">
+<code class="descname">alias</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.alias" title="Permalink to this definition">¶</a></dt>
+<dd><p>A string with the alias of the variable</p>
+</dd></dl>
+
+<dl class="method">
+<dt id="pyFTS.models.multivariate.variable.Variable.apply_inverse_transformations">
+<code class="descname">apply_inverse_transformations</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/variable.html#Variable.apply_inverse_transformations"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.apply_inverse_transformations" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="method">
+<dt id="pyFTS.models.multivariate.variable.Variable.apply_transformations">
+<code class="descname">apply_transformations</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/variable.html#Variable.apply_transformations"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.apply_transformations" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
+<dl class="method">
+<dt id="pyFTS.models.multivariate.variable.Variable.build">
+<code class="descname">build</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/variable.html#Variable.build"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.build" title="Permalink to this definition">¶</a></dt>
+<dd><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"><strong>kwargs</strong> – </td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"></td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="attribute">
+<dt id="pyFTS.models.multivariate.variable.Variable.data_label">
+<code class="descname">data_label</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.data_label" title="Permalink to this definition">¶</a></dt>
+<dd><p>A string with the column name on DataFrame</p>
+</dd></dl>
+
+<dl class="attribute">
+<dt id="pyFTS.models.multivariate.variable.Variable.name">
+<code class="descname">name</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.name" title="Permalink to this definition">¶</a></dt>
+<dd><p>A string with the name of the variable</p>
+</dd></dl>
+
+</dd></dl>
+
 </div>
 <div class="section" id="module-pyFTS.models.multivariate.flrg">
 <span id="pyfts-models-multivariate-flrg-module"></span><h2>pyFTS.models.multivariate.flrg module<a class="headerlink" href="#module-pyFTS.models.multivariate.flrg" title="Permalink to this headline">¶</a></h2>
@@ -268,6 +369,28 @@
 </table>
 </dd></dl>
 
+<dl class="method">
+<dt id="pyFTS.models.multivariate.mvfts.MVFTS.forecast_ahead">
+<code class="descname">forecast_ahead</code><span class="sig-paren">(</span><em>data</em>, <em>steps</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.forecast_ahead"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.forecast_ahead" title="Permalink to this definition">¶</a></dt>
+<dd><p>Point forecast n steps ahead</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>data</strong> – time series data with the minimal length equal to the max_lag of the model</li>
+<li><strong>steps</strong> – the number of steps ahead to forecast</li>
+<li><strong>start</strong> – in the multi step forecasting, the index of the data where to start forecasting</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 with the forecasted values</p>
+</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
 <dl class="method">
 <dt id="pyFTS.models.multivariate.mvfts.MVFTS.format_data">
 <code class="descname">format_data</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.format_data"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.format_data" title="Permalink to this definition">¶</a></dt>
@@ -309,123 +432,82 @@
 </dd></dl>
 
 </div>
-<div class="section" id="module-pyFTS.models.multivariate.variable">
+<div class="section" id="module-pyFTS.models.multivariate.wmvfts">
-<span id="pyfts-models-multivariate-variable-module"></span><h2>pyFTS.models.multivariate.variable module<a class="headerlink" href="#module-pyFTS.models.multivariate.variable" title="Permalink to this headline">¶</a></h2>
+<span id="pyfts-models-multivariate-wmvfts-module"></span><h2>pyFTS.models.multivariate.wmvfts module<a class="headerlink" href="#module-pyFTS.models.multivariate.wmvfts" title="Permalink to this headline">¶</a></h2>
 <dl class="class">
-<dt id="pyFTS.models.multivariate.variable.Variable">
+<dt id="pyFTS.models.multivariate.wmvfts.WeightedFLRG">
-<em class="property">class </em><code class="descclassname">pyFTS.models.multivariate.variable.</code><code class="descname">Variable</code><span class="sig-paren">(</span><em>name</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/variable.html#Variable"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable" title="Permalink to this definition">¶</a></dt>
+<em class="property">class </em><code class="descclassname">pyFTS.models.multivariate.wmvfts.</code><code class="descname">WeightedFLRG</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/wmvfts.html#WeightedFLRG"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedFLRG" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference external" href="https://docs.python.org/3/library/functions.html#object" title="(in Python v3.7)"><code class="xref py py-class docutils literal notranslate"><span class="pre">object</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.multivariate.flrg.FLRG" title="pyFTS.models.multivariate.flrg.FLRG"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.multivariate.flrg.FLRG</span></code></a></p>
-<p>A variable of a fuzzy time series multivariate model. Each variable contains its own
+<p>Weighted Multivariate Fuzzy Logical Rule Group</p>
-transformations and partitioners.</p>
-<dl class="attribute">
-<dt id="pyFTS.models.multivariate.variable.Variable.alias">
-<code class="descname">alias</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.alias" title="Permalink to this definition">¶</a></dt>
-<dd><p>A string with the alias of the variable</p>
-</dd></dl>
-
 <dl class="method">
-<dt id="pyFTS.models.multivariate.variable.Variable.apply_inverse_transformations">
+<dt id="pyFTS.models.multivariate.wmvfts.WeightedFLRG.append_rhs">
-<code class="descname">apply_inverse_transformations</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/variable.html#Variable.apply_inverse_transformations"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.apply_inverse_transformations" title="Permalink to this definition">¶</a></dt>
+<code class="descname">append_rhs</code><span class="sig-paren">(</span><em>fset</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/wmvfts.html#WeightedFLRG.append_rhs"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedFLRG.append_rhs" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
 <dl class="method">
-<dt id="pyFTS.models.multivariate.variable.Variable.apply_transformations">
+<dt id="pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_midpoint">
-<code class="descname">apply_transformations</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/variable.html#Variable.apply_transformations"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.apply_transformations" title="Permalink to this definition">¶</a></dt>
+<code class="descname">get_midpoint</code><span class="sig-paren">(</span><em>sets</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/wmvfts.html#WeightedFLRG.get_midpoint"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_midpoint" title="Permalink to this definition">¶</a></dt>
-<dd></dd></dl>
+<dd><p>Returns the midpoint value for the RHS fuzzy sets</p>
-
+<table class="docutils field-list" frame="void" rules="none">
-<dl class="method">
-<dt id="pyFTS.models.multivariate.variable.Variable.build">
-<code class="descname">build</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/variable.html#Variable.build"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.build" title="Permalink to this definition">¶</a></dt>
-<dd><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"><strong>kwargs</strong> – </td>
+<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>sets</strong> – fuzzy sets</td>
 </tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"></td>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body">the midpoint value</td>
 </tr>
 </tbody>
 </table>
 </dd></dl>
 
-<dl class="attribute">
+<dl class="method">
-<dt id="pyFTS.models.multivariate.variable.Variable.data_label">
+<dt id="pyFTS.models.multivariate.wmvfts.WeightedFLRG.weights">
-<code class="descname">data_label</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.data_label" title="Permalink to this definition">¶</a></dt>
+<code class="descname">weights</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/wmvfts.html#WeightedFLRG.weights"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedFLRG.weights" title="Permalink to this definition">¶</a></dt>
-<dd><p>A string with the column name on DataFrame</p>
+<dd></dd></dl>
+
 </dd></dl>
 
-<dl class="attribute">
+<dl class="class">
-<dt id="pyFTS.models.multivariate.variable.Variable.name">
+<dt id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS">
-<code class="descname">name</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.models.multivariate.variable.Variable.name" title="Permalink to this definition">¶</a></dt>
+<em class="property">class </em><code class="descclassname">pyFTS.models.multivariate.wmvfts.</code><code class="descname">WeightedMVFTS</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/wmvfts.html#WeightedMVFTS"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS" title="Permalink to this definition">¶</a></dt>
-<dd><p>A string with the name of the variable</p>
+<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.multivariate.mvfts.MVFTS" title="pyFTS.models.multivariate.mvfts.MVFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.multivariate.mvfts.MVFTS</span></code></a></p>
-</dd></dl>
+<p>Weighted Multivariate FTS</p>
+<dl class="method">
+<dt id="pyFTS.models.multivariate.wmvfts.WeightedMVFTS.generate_flrg">
+<code class="descname">generate_flrg</code><span class="sig-paren">(</span><em>flrs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/wmvfts.html#WeightedMVFTS.generate_flrg"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedMVFTS.generate_flrg" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
 
 </dd></dl>
 
 </div>
-<div class="section" id="pyfts-models-multivariate-wmvfts-module">
+<div class="section" id="module-pyFTS.models.multivariate.cmvfts">
-<h2>pyFTS.models.multivariate.wmvfts module<a class="headerlink" href="#pyfts-models-multivariate-wmvfts-module" title="Permalink to this headline">¶</a></h2>
+<span id="pyfts-models-multivariate-cmvfts-module"></span><h2>pyFTS.models.multivariate.cmvfts module<a class="headerlink" href="#module-pyFTS.models.multivariate.cmvfts" title="Permalink to this headline">¶</a></h2>
-<span class="target" id="module-pyFTS.models.multivariate.mvfts"></span><dl class="class">
+<dl class="class">
-<dt>
+<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS">
-<em class="property">class </em><code class="descclassname">pyFTS.models.multivariate.mvfts.</code><code class="descname">MVFTS</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS"><span class="viewcode-link">[source]</span></a></dt>
+<em class="property">class </em><code class="descclassname">pyFTS.models.multivariate.cmvfts.</code><code class="descname">ClusteredMVFTS</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/cmvfts.html#ClusteredMVFTS"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS" title="Permalink to this definition">¶</a></dt>
-<dd><p>Bases: <a class="reference internal" href="pyFTS.common.html#pyFTS.common.fts.FTS" title="pyFTS.common.fts.FTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.common.fts.FTS</span></code></a></p>
+<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.multivariate.mvfts.MVFTS" title="pyFTS.models.multivariate.mvfts.MVFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.multivariate.mvfts.MVFTS</span></code></a></p>
-<p>Multivariate extension of Chen’s ConventionalFTS method</p>
+<p>Meta model for multivariate, high order, clustered multivariate FTS</p>
-<dl class="method">
+<dl class="attribute">
-<dt>
+<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.cluster">
-<code class="descname">append_variable</code><span class="sig-paren">(</span><em>var</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.append_variable"><span class="viewcode-link">[source]</span></a></dt>
+<code class="descname">cluster</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.cluster" title="Permalink to this definition">¶</a></dt>
-<dd><p>Append a new endogenous variable to the model</p>
+<dd><p>The most recent trained clusterer</p>
-<table class="docutils field-list" frame="void" rules="none">
+</dd></dl>
-<col class="field-name" />
+
-<col class="field-body" />
+<dl class="attribute">
-<tbody valign="top">
+<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.cluster_method">
-<tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><strong>var</strong> – variable object</td>
+<code class="descname">cluster_method</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.cluster_method" title="Permalink to this definition">¶</a></dt>
-</tr>
+<dd><p>The cluster method to be called when a new model is build</p>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"></td>
+</dd></dl>
-</tr>
+
-</tbody>
+<dl class="attribute">
-</table>
+<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.cluster_params">
+<code class="descname">cluster_params</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.cluster_params" title="Permalink to this definition">¶</a></dt>
+<dd><p>The cluster method parameters</p>
 </dd></dl>
 
 <dl class="method">
-<dt>
+<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast">
-<code class="descname">apply_transformations</code><span class="sig-paren">(</span><em>data</em>, <em>params=None</em>, <em>updateUoD=False</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.apply_transformations"><span class="viewcode-link">[source]</span></a></dt>
+<code class="descname">forecast</code><span class="sig-paren">(</span><em>ndata</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/cmvfts.html#ClusteredMVFTS.forecast"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.forecast" title="Permalink to this definition">¶</a></dt>
-<dd><p>Apply the data transformations for data preprocessing</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>data</strong> – input data</li>
-<li><strong>params</strong> – transformation parameters</li>
-<li><strong>updateUoD</strong> – </li>
-<li><strong>kwargs</strong> – </li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last">preprocessed data</p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt>
-<code class="descname">clone_parameters</code><span class="sig-paren">(</span><em>model</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.clone_parameters"><span class="viewcode-link">[source]</span></a></dt>
-<dd><p>Import the parameters values from other model</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"><strong>model</strong> – </td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
-<dl class="method">
-<dt>
-<code class="descname">forecast</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.forecast"><span class="viewcode-link">[source]</span></a></dt>
 <dd><p>Point forecast one step ahead</p>
 <table class="docutils field-list" frame="void" rules="none">
 <col class="field-name" />
@@ -444,29 +526,32 @@ transformations and partitioners.</p>
 </table>
 </dd></dl>
 
-<dl class="method">
+<dl class="attribute">
-<dt>
+<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.fts_method">
-<code class="descname">format_data</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.format_data"><span class="viewcode-link">[source]</span></a></dt>
+<code class="descname">fts_method</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.fts_method" title="Permalink to this definition">¶</a></dt>
-<dd></dd></dl>
+<dd><p>The FTS method to be called when a new model is build</p>
+</dd></dl>
+
+<dl class="attribute">
+<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.fts_params">
+<code class="descname">fts_params</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.fts_params" title="Permalink to this definition">¶</a></dt>
+<dd><p>The FTS method specific parameters</p>
+</dd></dl>
 
 <dl class="method">
-<dt>
+<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.fuzzyfy">
-<code class="descname">generate_flrg</code><span class="sig-paren">(</span><em>flrs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.generate_flrg"><span class="viewcode-link">[source]</span></a></dt>
+<code class="descname">fuzzyfy</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/cmvfts.html#ClusteredMVFTS.fuzzyfy"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.fuzzyfy" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
-<dl class="method">
+<dl class="attribute">
-<dt>
+<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.model">
-<code class="descname">generate_flrs</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.generate_flrs"><span class="viewcode-link">[source]</span></a></dt>
+<code class="descname">model</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.model" title="Permalink to this definition">¶</a></dt>
-<dd></dd></dl>
+<dd><p>The most recent trained model</p>
+</dd></dl>
 
 <dl class="method">
-<dt>
+<dt id="pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.train">
-<code class="descname">generate_lhs_flrs</code><span class="sig-paren">(</span><em>data</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.generate_lhs_flrs"><span class="viewcode-link">[source]</span></a></dt>
+<code class="descname">train</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/cmvfts.html#ClusteredMVFTS.train"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.cmvfts.ClusteredMVFTS.train" title="Permalink to this definition">¶</a></dt>
-<dd></dd></dl>
-
-<dl class="method">
-<dt>
-<code class="descname">train</code><span class="sig-paren">(</span><em>data</em>, <em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/mvfts.html#MVFTS.train"><span class="viewcode-link">[source]</span></a></dt>
 <dd><p>Method specific parameter fitting</p>
 <table class="docutils field-list" frame="void" rules="none">
 <col class="field-name" />

docs/build/html/pyFTS.models.seasonal.html

@@ -299,7 +299,7 @@
 <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
 <li><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</li>
 <li><strong>steps</strong> – the number of steps ahead to forecast</li>
-<li><strong>kwargs</strong> – model specific parameters</li>
+<li><strong>start</strong> – in the multi step forecasting, the index of the data where to start forecasting</li>
 </ul>
 </td>
 </tr>
@@ -525,7 +525,7 @@
 <tr class="field-odd field"><th class="field-name">Parameters:</th><td class="field-body"><ul class="first simple">
 <li><strong>data</strong> – time series data with the minimal length equal to the max_lag of the model</li>
 <li><strong>steps</strong> – the number of steps ahead to forecast</li>
-<li><strong>kwargs</strong> – model specific parameters</li>
+<li><strong>start</strong> – in the multi step forecasting, the index of the data where to start forecasting</li>
 </ul>
 </td>
 </tr>

docs/build/html/pyFTS.partitioners.html

@@ -71,7 +71,7 @@
 <li><a class="reference internal" href="#module-pyFTS.partitioners.FCM">pyFTS.partitioners.FCM module</a></li>
 <li><a class="reference internal" href="#module-pyFTS.partitioners.Grid">pyFTS.partitioners.Grid module</a></li>
 <li><a class="reference internal" href="#module-pyFTS.partitioners.Huarng">pyFTS.partitioners.Huarng module</a></li>
-<li><a class="reference internal" href="#pyfts-partitioners-singleton-module">pyFTS.partitioners.Singleton module</a></li>
+<li><a class="reference internal" href="#module-pyFTS.partitioners.Singleton">pyFTS.partitioners.Singleton module</a></li>
 <li><a class="reference internal" href="#module-pyFTS.partitioners.Util">pyFTS.partitioners.Util module</a></li>
 <li><a class="reference internal" href="#module-pyFTS.partitioners.parallel_util">pyFTS.partitioners.parallel_util module</a></li>
 </ul>
@@ -241,6 +241,12 @@
 <dd><p>data transformation to be applied on data</p>
 </dd></dl>
 
+<dl class="attribute">
+<dt id="pyFTS.partitioners.partitioner.Partitioner.type">
+<code class="descname">type</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.type" title="Permalink to this definition">¶</a></dt>
+<dd><p>The type of fuzzy sets that are generated by this partitioner</p>
+</dd></dl>
+
 <dl class="method">
 <dt id="pyFTS.partitioners.partitioner.Partitioner.upper_set">
 <code class="descname">upper_set</code><span class="sig-paren">(</span><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/partitioner.html#Partitioner.upper_set"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.upper_set" title="Permalink to this definition">¶</a></dt>
@@ -255,6 +261,12 @@
 </table>
 </dd></dl>
 
+<dl class="attribute">
+<dt id="pyFTS.partitioners.partitioner.Partitioner.variable">
+<code class="descname">variable</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.partitioners.partitioner.Partitioner.variable" title="Permalink to this definition">¶</a></dt>
+<dd><p>In a multivariate context, the variable that contains this partitioner</p>
+</dd></dl>
+
 </dd></dl>
 
 </div>
@@ -448,9 +460,9 @@ Fuzzy Sets Syst., vol. 123, no. 3, pp. 387–394, Nov. 2001.</p>
 </dd></dl>
 
 </div>
-<div class="section" id="pyfts-partitioners-singleton-module">
+<div class="section" id="module-pyFTS.partitioners.Singleton">
-<h2>pyFTS.partitioners.Singleton module<a class="headerlink" href="#pyfts-partitioners-singleton-module" title="Permalink to this headline">¶</a></h2>
+<span id="pyfts-partitioners-singleton-module"></span><h2>pyFTS.partitioners.Singleton module<a class="headerlink" href="#module-pyFTS.partitioners.Singleton" title="Permalink to this headline">¶</a></h2>
-<span class="target" id="module-pyFTS.partitioners.Singleton"></span><p>Even Length Grid Partitioner</p>
+<p>Even Length Grid Partitioner</p>
 <dl class="class">
 <dt id="pyFTS.partitioners.Singleton.SingletonPartitioner">
 <em class="property">class </em><code class="descclassname">pyFTS.partitioners.Singleton.</code><code class="descname">SingletonPartitioner</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/partitioners/Singleton.html#SingletonPartitioner"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.partitioners.Singleton.SingletonPartitioner" title="Permalink to this definition">¶</a></dt>

docs/pyFTS.models.multivariate.rst

@@ -29,6 +29,14 @@ pyFTS.models.multivariate.common module
     :undoc-members:
     :show-inheritance:
 
+pyFTS.models.multivariate.variable module
+-----------------------------------------
+
+.. automodule:: pyFTS.models.multivariate.variable
+    :members:
+    :undoc-members:
+    :show-inheritance:
+
 pyFTS.models.multivariate.flrg module
 -------------------------------------
 
@@ -45,18 +53,18 @@ pyFTS.models.multivariate.mvfts module
     :undoc-members:
     :show-inheritance:
     
-pyFTS.models.multivariate.variable module
------------------------------------------
-
-.. automodule:: pyFTS.models.multivariate.variable
-    :members:
-    :undoc-members:
-    :show-inheritance:
-    
 pyFTS.models.multivariate.wmvfts module
---------------------------------------
+---------------------------------------
 
-.. automodule:: pyFTS.models.multivariate.mvfts
+.. automodule:: pyFTS.models.multivariate.wmvfts
+    :members:
+    :undoc-members:
+    :show-inheritance:
+    
+pyFTS.models.multivariate.cmvfts module
+---------------------------------------
+
+.. automodule:: pyFTS.models.multivariate.cmvfts
     :members:
     :undoc-members:
     :show-inheritance:

docs/pyFTS.partitioners.rst

@@ -61,7 +61,7 @@ pyFTS.partitioners.Huarng module
     :show-inheritance:
 
 pyFTS.partitioners.Singleton module
---------------------------------
+-----------------------------------
 
 .. automodule:: pyFTS.partitioners.Singleton
     :members:

docs/pyFTS.rst

@@ -9,6 +9,7 @@ Subpackages
     pyFTS.benchmarks
     pyFTS.common
     pyFTS.data
+    pyFTS.hyperparam
     pyFTS.models
     pyFTS.partitioners
     pyFTS.probabilistic

pyFTS/common/fts.py

@@ -94,6 +94,9 @@ class FTS(object):
         :keyword distributed: boolean, indicate if the forecasting procedure will be distributed in a dispy cluster
         :keyword nodes: a list with the dispy cluster nodes addresses
         :keyword explain: try to explain, step by step, the one-step-ahead point forecasting result given the input data.
+        :keyword generators: for multivariate methods on multi step ahead forecasting, generators is a dict where the keys
+                            are the variables names (except the target_variable) and the values are lambda functions that
+                            accept one value (the actual value of the variable) and return the next value.
 
         :return: a numpy array with the forecasted data
         """
@@ -187,10 +190,12 @@ class FTS(object):
 
         :param data: time series data with the minimal length equal to the max_lag of the model
         :param steps: the number of steps ahead to forecast
-        :param kwargs: model specific parameters
+        :keyword start: in the multi step forecasting, the index of the data where to start forecasting
         :return: a list with the forecasted values
         """
 
+
+
         if isinstance(data, np.ndarray):
             data = data.tolist()
 

pyFTS/models/multivariate/mvfts.py

@@ -130,6 +130,7 @@ class MVFTS(fts.FTS):
 
     def forecast_ahead(self, data, steps, **kwargs):
         generators = kwargs.get('generators',None)
+        start = kwargs.get('start', 0)
 
         if generators is None:
             raise Exception('You must provide parameter \'generators\'! generators is a dict where the keys' +