From 6b8607cf3c9c3e9acd1603917dd54d56dc86a327 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Petr=C3=B4nio=20C=C3=A2ndido?= <petronio.candido@gmail.com>
Date: Tue, 2 Apr 2019 15:30:51 -0300
Subject: [PATCH] Updating documentiation

---
 docs/build/doctrees/environment.pickle        | Bin 2275178 -> 2282101 bytes
 docs/build/doctrees/pyFTS.benchmarks.doctree  | Bin 372841 -> 355511 bytes
 docs/build/doctrees/pyFTS.common.doctree      | Bin 392100 -> 418875 bytes
 docs/build/doctrees/pyFTS.hyperparam.doctree  | Bin 23000 -> 14941 bytes
 docs/build/doctrees/pyFTS.models.doctree      | Bin 239840 -> 245362 bytes
 .../doctrees/pyFTS.models.ensemble.doctree    | Bin 69333 -> 69359 bytes
 .../doctrees/pyFTS.models.incremental.doctree | Bin 47190 -> 48700 bytes
 .../pyFTS.models.multivariate.doctree         | Bin 119569 -> 134064 bytes
 .../_modules/pyFTS/benchmarks/benchmarks.html | 162 +--------------
 .../html/_modules/pyFTS/common/Util.html      | 190 ++++++++++++++++++
 .../html/_modules/pyFTS/data/artificial.html  |   2 +-
 .../pyFTS/models/ensemble/ensemble.html       |  20 +-
 .../html/_modules/pyFTS/models/hofts.html     |  19 +-
 .../html/_modules/pyFTS/models/ifts.html      |   6 +-
 .../incremental/IncrementalEnsemble.html      |  37 ++--
 .../pyFTS/models/incremental/TimeVariant.html |   1 +
 .../pyFTS/models/multivariate/flrg.html       |  13 +-
 .../pyFTS/models/multivariate/mvfts.html      |  48 ++++-
 .../pyFTS/models/multivariate/wmvfts.html     |  19 +-
 docs/build/html/genindex.html                 |  38 ++--
 docs/build/html/objects.inv                   | Bin 6461 -> 6453 bytes
 docs/build/html/py-modindex.html              |   5 -
 docs/build/html/pyFTS.benchmarks.html         |  53 -----
 docs/build/html/pyFTS.common.html             | 116 ++++++++++-
 docs/build/html/pyFTS.html                    |   2 +-
 docs/build/html/pyFTS.hyperparam.html         |  26 +--
 docs/build/html/pyFTS.models.ensemble.html    |   2 +-
 docs/build/html/pyFTS.models.html             |  34 +++-
 docs/build/html/pyFTS.models.incremental.html |   6 +
 .../build/html/pyFTS.models.multivariate.html |  85 ++++++++
 docs/build/html/searchindex.js                |   2 +-
 pyFTS/common/Util.py                          |  36 ++++
 32 files changed, 630 insertions(+), 292 deletions(-)

diff --git a/docs/build/doctrees/environment.pickle b/docs/build/doctrees/environment.pickle
index 737870261fd569ef5eda5f7b97f0eff4dc4ce3ad..f7e04f0ba31ee487610e82d8441d103809fbb6a9 100644
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diff --git a/docs/build/doctrees/pyFTS.common.doctree b/docs/build/doctrees/pyFTS.common.doctree
index dcefe67520ee701f547a22862e852874ae22900b..c2780e42894c3436d2a782cbecb63dc717a1d9c9 100644
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diff --git a/docs/build/doctrees/pyFTS.hyperparam.doctree b/docs/build/doctrees/pyFTS.hyperparam.doctree
index 8a7a957d9a8ef7012e609a089e169b4032dce95e..08ce869e589fd988e902af4ef04c5c14b35fafa1 100644
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diff --git a/docs/build/doctrees/pyFTS.models.doctree b/docs/build/doctrees/pyFTS.models.doctree
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diff --git a/docs/build/doctrees/pyFTS.models.ensemble.doctree b/docs/build/doctrees/pyFTS.models.ensemble.doctree
index 608253ff9c320268ad5409d942cc5948046d669e..ec5eada4b63dfde9dd9b585e9f5878f6fc7c3a5f 100644
GIT binary patch
delta 90
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delta 55
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diff --git a/docs/build/doctrees/pyFTS.models.incremental.doctree b/docs/build/doctrees/pyFTS.models.incremental.doctree
index 124e2137c4831eddf55181db70e1e369135bf096..59c84bc01239b98a37effcab99dfe7a7966e265c 100644
GIT binary patch
delta 1247
zcmb7EZ){Ul9NoKPd35jHtxFh=ZliyYWgTnUjwZ5zY>ROT%oU2vk;Q^*czStRJMG#y
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delta 846
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diff --git a/docs/build/doctrees/pyFTS.models.multivariate.doctree b/docs/build/doctrees/pyFTS.models.multivariate.doctree
index 366c79ccdb0289f732de156b952355d3fa708f1c..bb8bf0965d692c40fcd96b538a5544ea952c730f 100644
GIT binary patch
delta 15193
zcmb_jdz_8c`nMLD*<)t*-1p4hGqd;H_S_goB;+!ZN$w75CSov*mk@(<l#HXY6=K$~
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diff --git a/docs/build/html/_modules/pyFTS/benchmarks/benchmarks.html b/docs/build/html/_modules/pyFTS/benchmarks/benchmarks.html
index 12e4d83..60c966c 100644
--- a/docs/build/html/_modules/pyFTS/benchmarks/benchmarks.html
+++ b/docs/build/html/_modules/pyFTS/benchmarks/benchmarks.html
@@ -84,13 +84,11 @@
 <span class="kn">import</span> <span class="nn">traceback</span>
 
 <span class="kn">import</span> <span class="nn">matplotlib</span> <span class="k">as</span> <span class="nn">plt</span>
-<span class="kn">import</span> <span class="nn">matplotlib.cm</span> <span class="k">as</span> <span class="nn">cmx</span>
-<span class="kn">import</span> <span class="nn">matplotlib.colors</span> <span class="k">as</span> <span class="nn">pltcolors</span>
+
 <span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
 <span class="kn">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">mpl_toolkits.mplot3d</span> <span class="k">import</span> <span class="n">Axes3D</span>
 
-<span class="kn">from</span> <span class="nn">pyFTS.probabilistic</span> <span class="k">import</span> <span class="n">ProbabilityDistribution</span>
 <span class="kn">from</span> <span class="nn">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>
@@ -100,12 +98,6 @@
 <span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">Util</span> <span class="k">as</span> <span class="n">cUtil</span>
 <span class="c1"># from sklearn.cross_validation import KFold</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">matplotlib</span> <span class="k">import</span> <span class="n">rc</span>
-
-<span class="c1">#rc(&#39;font&#39;,**{&#39;family&#39;:&#39;sans-serif&#39;,&#39;sans-serif&#39;:[&#39;Helvetica&#39;]})</span>
-<span class="c1">## for Palatino and other serif fonts use:</span>
-<span class="c1">#rc(&#39;font&#39;,**{&#39;family&#39;:&#39;serif&#39;,&#39;serif&#39;:[&#39;Palatino&#39;]})</span>
-<span class="c1">#rc(&#39;text&#39;, usetex=True)</span>
 
 <span class="n">colors</span> <span class="o">=</span> <span class="p">[</span><span class="s1">&#39;grey&#39;</span><span class="p">,</span> <span class="s1">&#39;darkgrey&#39;</span><span class="p">,</span> <span class="s1">&#39;rosybrown&#39;</span><span class="p">,</span> <span class="s1">&#39;maroon&#39;</span><span class="p">,</span> <span class="s1">&#39;red&#39;</span><span class="p">,</span><span class="s1">&#39;orange&#39;</span><span class="p">,</span> <span class="s1">&#39;gold&#39;</span><span class="p">,</span> <span class="s1">&#39;yellow&#39;</span><span class="p">,</span> <span class="s1">&#39;olive&#39;</span><span class="p">,</span> <span class="s1">&#39;green&#39;</span><span class="p">,</span>
           <span class="s1">&#39;darkgreen&#39;</span><span class="p">,</span> <span class="s1">&#39;cyan&#39;</span><span class="p">,</span> <span class="s1">&#39;lightblue&#39;</span><span class="p">,</span><span class="s1">&#39;blue&#39;</span><span class="p">,</span> <span class="s1">&#39;darkblue&#39;</span><span class="p">,</span> <span class="s1">&#39;purple&#39;</span><span class="p">,</span> <span class="s1">&#39;darkviolet&#39;</span> <span class="p">]</span>
@@ -292,10 +284,10 @@
         <span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">&quot;Type parameter has a unkown value!&quot;</span><span class="p">)</span>
 
     <span class="k">if</span> <span class="n">distributed</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="kn">import</span> <span class="nn">pyFTS.distributed.dispy</span> <span class="k">as</span> <span class="nn">dispy</span>
 
         <span class="n">nodes</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;nodes&quot;</span><span class="p">,</span> <span class="p">[</span><span class="s1">&#39;127.0.0.1&#39;</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">cUtil</span><span class="o">.</span><span class="n">start_dispy_cluster</span><span class="p">(</span><span class="n">experiment_method</span><span class="p">,</span> <span class="n">nodes</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">dispy</span><span class="o">.</span><span class="n">start_dispy_cluster</span><span class="p">(</span><span class="n">experiment_method</span><span class="p">,</span> <span class="n">nodes</span><span class="p">)</span>
 
     <span class="n">jobs</span> <span class="o">=</span> <span class="p">[]</span>
 
@@ -380,7 +372,7 @@
             <span class="k">if</span> <span class="n">progress</span><span class="p">:</span>
                 <span class="n">progressbar</span><span class="o">.</span><span class="n">update</span><span class="p">(</span><span class="mi">1</span><span class="p">)</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">job</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="k">if</span> <span class="n">job</span><span class="o">.</span><span class="n">status</span> <span class="o">==</span> <span class="n">dispy</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">job</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
                 <span class="n">tmp</span> <span class="o">=</span> <span class="n">job</span><span class="o">.</span><span class="n">result</span>
                 <span class="n">synthesis_method</span><span class="p">(</span><span class="n">dataset</span><span class="p">,</span> <span class="n">tag</span><span class="p">,</span> <span class="n">tmp</span><span class="p">,</span> <span class="n">conn</span><span class="p">)</span>
             <span class="k">else</span><span class="p">:</span>
@@ -391,7 +383,7 @@
 
         <span class="n">cluster</span><span class="o">.</span><span class="n">wait</span><span class="p">()</span>  <span class="c1"># wait for all jobs to finish</span>
 
-        <span class="n">cUtil</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>
+        <span class="n">dispy</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>
 
     <span class="n">conn</span><span class="o">.</span><span class="n">close</span><span class="p">()</span></div>
 
@@ -755,145 +747,11 @@
 
 
 
-<div class="viewcode-block" id="plot_compared_intervals_ahead"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.plot_compared_intervals_ahead">[docs]</a><span class="k">def</span> <span class="nf">plot_compared_intervals_ahead</span><span class="p">(</span><span class="n">original</span><span class="p">,</span> <span class="n">models</span><span class="p">,</span> <span class="n">colors</span><span class="p">,</span> <span class="n">distributions</span><span class="p">,</span> <span class="n">time_from</span><span class="p">,</span> <span class="n">time_to</span><span class="p">,</span> <span class="n">intervals</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
-                               <span class="n">save</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">file</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">tam</span><span class="o">=</span><span class="p">[</span><span class="mi">20</span><span class="p">,</span> <span class="mi">5</span><span class="p">],</span> <span class="n">resolution</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
-                               <span class="n">cmap</span><span class="o">=</span><span class="s1">&#39;Blues&#39;</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="mf">1.5</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;</span>
-<span class="sd">    Plot the forecasts of several one step ahead models, by point or by interval</span>
-
-<span class="sd">    :param original: Original time series data (list)</span>
-<span class="sd">    :param models: List of models to compare</span>
-<span class="sd">    :param colors: List of models colors</span>
-<span class="sd">    :param distributions: True to plot a distribution</span>
-<span class="sd">    :param time_from: index of data poit to start the ahead forecasting</span>
-<span class="sd">    :param time_to: number of steps ahead to forecast</span>
-<span class="sd">    :param interpol: Fill space between distribution plots</span>
-<span class="sd">    :param save: Save the picture on file</span>
-<span class="sd">    :param file: Filename to save the picture</span>
-<span class="sd">    :param tam: Size of the picture</span>
-<span class="sd">    :param resolution: </span>
-<span class="sd">    :param cmap: Color map to be used on distribution plot </span>
-<span class="sd">    :param option: Distribution type to be passed for models</span>
-<span class="sd">    :return: </span>
-<span class="sd">    &quot;&quot;&quot;</span>
-    <span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="n">tam</span><span class="p">)</span>
-    <span class="n">ax</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">111</span><span class="p">)</span>
-
-    <span class="n">cm</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="n">cmap</span><span class="p">)</span>
-    <span class="n">cNorm</span> <span class="o">=</span> <span class="n">pltcolors</span><span class="o">.</span><span class="n">Normalize</span><span class="p">(</span><span class="n">vmin</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">vmax</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
-    <span class="n">scalarMap</span> <span class="o">=</span> <span class="n">cmx</span><span class="o">.</span><span class="n">ScalarMappable</span><span class="p">(</span><span class="n">norm</span><span class="o">=</span><span class="n">cNorm</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="n">cm</span><span class="p">)</span>
-
-    <span class="k">if</span> <span class="n">resolution</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> <span class="n">resolution</span> <span class="o">=</span> <span class="p">(</span><span class="nb">max</span><span class="p">(</span><span class="n">original</span><span class="p">)</span> <span class="o">-</span> <span class="nb">min</span><span class="p">(</span><span class="n">original</span><span class="p">))</span> <span class="o">/</span> <span class="mi">100</span>
-
-    <span class="n">mi</span> <span class="o">=</span> <span class="p">[]</span>
-    <span class="n">ma</span> <span class="o">=</span> <span class="p">[]</span>
-
-    <span class="k">for</span> <span class="n">count</span><span class="p">,</span> <span class="n">fts</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">models</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
-        <span class="k">if</span> <span class="n">fts</span><span class="o">.</span><span class="n">has_probability_forecasting</span> <span class="ow">and</span> <span class="n">distributions</span><span class="p">[</span><span class="n">count</span><span class="p">]:</span>
-            <span class="n">density</span> <span class="o">=</span> <span class="n">fts</span><span class="o">.</span><span class="n">forecast_ahead_distribution</span><span class="p">(</span><span class="n">original</span><span class="p">[</span><span class="n">time_from</span> <span class="o">-</span> <span class="n">fts</span><span class="o">.</span><span class="n">order</span><span class="p">:</span><span class="n">time_from</span><span class="p">],</span> <span class="n">time_to</span><span class="p">,</span>
-                                                      <span class="n">resolution</span><span class="o">=</span><span class="n">resolution</span><span class="p">)</span>
-
-            <span class="c1">#plot_density_scatter(ax, cmap, density, fig, resolution, time_from, time_to)</span>
-            <span class="n">plot_density_rectange</span><span class="p">(</span><span class="n">ax</span><span class="p">,</span> <span class="n">cm</span><span class="p">,</span> <span class="n">density</span><span class="p">,</span> <span class="n">fig</span><span class="p">,</span> <span class="n">resolution</span><span class="p">,</span> <span class="n">time_from</span><span class="p">,</span> <span class="n">time_to</span><span class="p">)</span>
-
-        <span class="k">if</span> <span class="n">fts</span><span class="o">.</span><span class="n">has_interval_forecasting</span> <span class="ow">and</span> <span class="n">intervals</span><span class="p">:</span>
-            <span class="n">forecasts</span> <span class="o">=</span> <span class="n">fts</span><span class="o">.</span><span class="n">forecast_ahead_interval</span><span class="p">(</span><span class="n">original</span><span class="p">[</span><span class="n">time_from</span> <span class="o">-</span> <span class="n">fts</span><span class="o">.</span><span class="n">order</span><span class="p">:</span><span class="n">time_from</span><span class="p">],</span> <span class="n">time_to</span><span class="p">)</span>
-            <span class="n">lower</span> <span class="o">=</span> <span class="p">[</span><span class="n">kk</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="n">forecasts</span><span class="p">]</span>
-            <span class="n">upper</span> <span class="o">=</span> <span class="p">[</span><span class="n">kk</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="n">forecasts</span><span class="p">]</span>
-            <span class="n">mi</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">min</span><span class="p">(</span><span class="n">lower</span><span class="p">))</span>
-            <span class="n">ma</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">max</span><span class="p">(</span><span class="n">upper</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">time_from</span> <span class="o">-</span> <span class="n">fts</span><span class="o">.</span><span class="n">order</span><span class="p">):</span>
-                <span class="n">lower</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
-                <span class="n">upper</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
-            <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">lower</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="n">colors</span><span class="p">[</span><span class="n">count</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="n">fts</span><span class="o">.</span><span class="n">shortname</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="n">linewidth</span><span class="p">)</span>
-            <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">upper</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="n">colors</span><span class="p">[</span><span class="n">count</span><span class="p">],</span> <span class="n">linewidth</span><span class="o">=</span><span class="n">linewidth</span><span class="o">*</span><span class="mf">1.5</span><span class="p">)</span>
-
-    <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">original</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;black&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;Original&quot;</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="n">linewidth</span><span class="o">*</span><span class="mf">1.5</span><span class="p">)</span>
-    <span class="n">handles0</span><span class="p">,</span> <span class="n">labels0</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">get_legend_handles_labels</span><span class="p">()</span>
-    <span class="k">if</span> <span class="kc">True</span> <span class="ow">in</span> <span class="n">distributions</span><span class="p">:</span>
-        <span class="n">lgd</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">handles0</span><span class="p">,</span> <span class="n">labels0</span><span class="p">,</span> <span class="n">loc</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
-    <span class="k">else</span><span class="p">:</span>
-        <span class="n">lgd</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">handles0</span><span class="p">,</span> <span class="n">labels0</span><span class="p">,</span> <span class="n">loc</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">bbox_to_anchor</span><span class="o">=</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">))</span>
-    <span class="n">_mi</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">mi</span><span class="p">)</span>
-    <span class="k">if</span> <span class="n">_mi</span> <span class="o">&lt;</span> <span class="mi">0</span><span class="p">:</span>
-        <span class="n">_mi</span> <span class="o">*=</span> <span class="mf">1.1</span>
-    <span class="k">else</span><span class="p">:</span>
-        <span class="n">_mi</span> <span class="o">*=</span> <span class="mf">0.9</span>
-    <span class="n">_ma</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">ma</span><span class="p">)</span>
-    <span class="k">if</span> <span class="n">_ma</span> <span class="o">&lt;</span> <span class="mi">0</span><span class="p">:</span>
-        <span class="n">_ma</span> <span class="o">*=</span> <span class="mf">0.9</span>
-    <span class="k">else</span><span class="p">:</span>
-        <span class="n">_ma</span> <span class="o">*=</span> <span class="mf">1.1</span>
-
-    <span class="n">ax</span><span class="o">.</span><span class="n">set_ylim</span><span class="p">([</span><span class="n">_mi</span><span class="p">,</span> <span class="n">_ma</span><span class="p">])</span>
-    <span class="n">ax</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;F(T)&#39;</span><span class="p">)</span>
-    <span class="n">ax</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">&#39;T&#39;</span><span class="p">)</span>
-    <span class="n">ax</span><span class="o">.</span><span class="n">set_xlim</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">original</span><span class="p">)])</span>
-
-    <span class="n">cUtil</span><span class="o">.</span><span class="n">show_and_save_image</span><span class="p">(</span><span class="n">fig</span><span class="p">,</span> <span class="n">file</span><span class="p">,</span> <span class="n">save</span><span class="p">,</span> <span class="n">lgd</span><span class="o">=</span><span class="n">lgd</span><span class="p">)</span></div>
 
 
 
-<div class="viewcode-block" id="plot_density_rectange"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.plot_density_rectange">[docs]</a><span class="k">def</span> <span class="nf">plot_density_rectange</span><span class="p">(</span><span class="n">ax</span><span class="p">,</span> <span class="n">cmap</span><span class="p">,</span> <span class="n">density</span><span class="p">,</span> <span class="n">fig</span><span class="p">,</span> <span class="n">resolution</span><span class="p">,</span> <span class="n">time_from</span><span class="p">,</span> <span class="n">time_to</span><span class="p">):</span>
-    <span class="sd">&quot;&quot;&quot;</span>
-<span class="sd">    Auxiliar function to plot_compared_intervals_ahead</span>
-<span class="sd">    &quot;&quot;&quot;</span>
-    <span class="kn">from</span> <span class="nn">matplotlib.patches</span> <span class="k">import</span> <span class="n">Rectangle</span>
-    <span class="kn">from</span> <span class="nn">matplotlib.collections</span> <span class="k">import</span> <span class="n">PatchCollection</span>
-    <span class="n">patches</span> <span class="o">=</span> <span class="p">[]</span>
-    <span class="n">colors</span> <span class="o">=</span> <span class="p">[]</span>
-    <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">density</span><span class="o">.</span><span class="n">index</span><span class="p">:</span>
-        <span class="k">for</span> <span class="n">y</span> <span class="ow">in</span> <span class="n">density</span><span class="o">.</span><span class="n">columns</span><span class="p">:</span>
-            <span class="n">s</span> <span class="o">=</span> <span class="n">Rectangle</span><span class="p">((</span><span class="n">time_from</span> <span class="o">+</span> <span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">),</span> <span class="mi">1</span><span class="p">,</span> <span class="n">resolution</span><span class="p">,</span> <span class="n">fill</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">lw</span> <span class="o">=</span> <span class="mi">0</span><span class="p">)</span>
-            <span class="n">patches</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">s</span><span class="p">)</span>
-            <span class="n">colors</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">density</span><span class="p">[</span><span class="n">y</span><span class="p">][</span><span class="n">x</span><span class="p">]</span><span class="o">*</span><span class="mi">5</span><span class="p">)</span>
-    <span class="n">pc</span> <span class="o">=</span> <span class="n">PatchCollection</span><span class="p">(</span><span class="n">patches</span><span class="o">=</span><span class="n">patches</span><span class="p">,</span> <span class="n">match_original</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-    <span class="n">pc</span><span class="o">.</span><span class="n">set_clim</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span>
-    <span class="n">pc</span><span class="o">.</span><span class="n">set_cmap</span><span class="p">(</span><span class="n">cmap</span><span class="p">)</span>
-    <span class="n">pc</span><span class="o">.</span><span class="n">set_array</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">colors</span><span class="p">))</span>
-    <span class="n">ax</span><span class="o">.</span><span class="n">add_collection</span><span class="p">(</span><span class="n">pc</span><span class="p">)</span>
-    <span class="n">cb</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">pc</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">)</span>
-    <span class="n">cb</span><span class="o">.</span><span class="n">set_label</span><span class="p">(</span><span class="s1">&#39;Density&#39;</span><span class="p">)</span></div>
 
 
-<div class="viewcode-block" id="plot_distribution"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.plot_distribution">[docs]</a><span class="k">def</span> <span class="nf">plot_distribution</span><span class="p">(</span><span class="n">ax</span><span class="p">,</span> <span class="n">cmap</span><span class="p">,</span> <span class="n">probabilitydist</span><span class="p">,</span> <span class="n">fig</span><span class="p">,</span> <span class="n">time_from</span><span class="p">,</span> <span class="n">reference_data</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
-    <span class="kn">from</span> <span class="nn">matplotlib.patches</span> <span class="k">import</span> <span class="n">Rectangle</span>
-    <span class="kn">from</span> <span class="nn">matplotlib.collections</span> <span class="k">import</span> <span class="n">PatchCollection</span>
-    <span class="n">patches</span> <span class="o">=</span> <span class="p">[]</span>
-    <span class="n">colors</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">dt</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">probabilitydist</span><span class="p">):</span>
-        <span class="n">disp</span> <span class="o">=</span> <span class="mf">0.0</span>
-        <span class="k">if</span> <span class="n">reference_data</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
-            <span class="n">disp</span> <span class="o">=</span> <span class="n">reference_data</span><span class="p">[</span><span class="n">time_from</span><span class="o">+</span><span class="n">ct</span><span class="p">]</span>
-
-        <span class="k">for</span> <span class="n">y</span> <span class="ow">in</span> <span class="n">dt</span><span class="o">.</span><span class="n">bins</span><span class="p">:</span>
-            <span class="n">s</span> <span class="o">=</span> <span class="n">Rectangle</span><span class="p">((</span><span class="n">time_from</span><span class="o">+</span><span class="n">ct</span><span class="p">,</span> <span class="n">y</span><span class="o">+</span><span class="n">disp</span><span class="p">),</span> <span class="mi">1</span><span class="p">,</span> <span class="n">dt</span><span class="o">.</span><span class="n">resolution</span><span class="p">,</span> <span class="n">fill</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">lw</span> <span class="o">=</span> <span class="mi">0</span><span class="p">)</span>
-            <span class="n">patches</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">s</span><span class="p">)</span>
-            <span class="n">colors</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">dt</span><span class="o">.</span><span class="n">density</span><span class="p">(</span><span class="n">y</span><span class="p">))</span>
-    <span class="n">scale</span> <span class="o">=</span> <span class="n">Transformations</span><span class="o">.</span><span class="n">Scale</span><span class="p">()</span>
-    <span class="n">colors</span> <span class="o">=</span> <span class="n">scale</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">colors</span><span class="p">)</span>
-    <span class="n">pc</span> <span class="o">=</span> <span class="n">PatchCollection</span><span class="p">(</span><span class="n">patches</span><span class="o">=</span><span class="n">patches</span><span class="p">,</span> <span class="n">match_original</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
-    <span class="n">pc</span><span class="o">.</span><span class="n">set_clim</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span>
-    <span class="n">pc</span><span class="o">.</span><span class="n">set_cmap</span><span class="p">(</span><span class="n">cmap</span><span class="p">)</span>
-    <span class="n">pc</span><span class="o">.</span><span class="n">set_array</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">colors</span><span class="p">))</span>
-    <span class="n">ax</span><span class="o">.</span><span class="n">add_collection</span><span class="p">(</span><span class="n">pc</span><span class="p">)</span>
-    <span class="n">cb</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">pc</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">)</span>
-    <span class="n">cb</span><span class="o">.</span><span class="n">set_label</span><span class="p">(</span><span class="s1">&#39;Density&#39;</span><span class="p">)</span></div>
-
-
-<div class="viewcode-block" id="plot_interval"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.plot_interval">[docs]</a><span class="k">def</span> <span class="nf">plot_interval</span><span class="p">(</span><span class="n">axis</span><span class="p">,</span> <span class="n">intervals</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="n">label</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;red&#39;</span><span class="p">,</span> <span class="n">typeonlegend</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="s1">&#39;-&#39;</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
-    <span class="n">lower</span> <span class="o">=</span> <span class="p">[</span><span class="n">kk</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="n">intervals</span><span class="p">]</span>
-    <span class="n">upper</span> <span class="o">=</span> <span class="p">[</span><span class="n">kk</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="n">intervals</span><span class="p">]</span>
-    <span class="n">mi</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">lower</span><span class="p">)</span> <span class="o">*</span> <span class="mf">0.95</span>
-    <span class="n">ma</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">upper</span><span class="p">)</span> <span class="o">*</span> <span class="mf">1.05</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">order</span><span class="p">):</span>
-        <span class="n">lower</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
-        <span class="n">upper</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
-    <span class="k">if</span> <span class="n">typeonlegend</span><span class="p">:</span> <span class="n">label</span> <span class="o">+=</span> <span class="s2">&quot; (Interval)&quot;</span>
-    <span class="n">axis</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">lower</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="n">color</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">label</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="n">ls</span><span class="p">,</span><span class="n">linewidth</span><span class="o">=</span><span class="n">linewidth</span><span class="p">)</span>
-    <span class="n">axis</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">upper</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="n">color</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="n">ls</span><span class="p">,</span><span class="n">linewidth</span><span class="o">=</span><span class="n">linewidth</span><span class="p">)</span>
-    <span class="k">return</span> <span class="p">[</span><span class="n">mi</span><span class="p">,</span> <span class="n">ma</span><span class="p">]</span></div>
-
 
 <div class="viewcode-block" id="plot_point"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.plot_point">[docs]</a><span class="k">def</span> <span class="nf">plot_point</span><span class="p">(</span><span class="n">axis</span><span class="p">,</span> <span class="n">points</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="n">label</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;red&#39;</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="s1">&#39;-&#39;</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
     <span class="n">mi</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">points</span><span class="p">)</span> <span class="o">*</span> <span class="mf">0.95</span>
@@ -954,7 +812,7 @@
                     <span class="n">ls</span> <span class="o">=</span> <span class="s2">&quot;-&quot;</span>
                 <span class="k">else</span><span class="p">:</span>
                     <span class="n">ls</span> <span class="o">=</span> <span class="s2">&quot;--&quot;</span>
-                <span class="n">tmpmi</span><span class="p">,</span> <span class="n">tmpma</span> <span class="o">=</span> <span class="n">plot_interval</span><span class="p">(</span><span class="n">ax</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">,</span> <span class="n">fts</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">lbl</span><span class="p">,</span> <span class="n">typeonlegend</span><span class="o">=</span><span class="n">typeonlegend</span><span class="p">,</span>
+                <span class="n">tmpmi</span><span class="p">,</span> <span class="n">tmpma</span> <span class="o">=</span> <span class="n">Util</span><span class="o">.</span><span class="n">plot_interval</span><span class="p">(</span><span class="n">ax</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">,</span> <span class="n">fts</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">lbl</span><span class="p">,</span> <span class="n">typeonlegend</span><span class="o">=</span><span class="n">typeonlegend</span><span class="p">,</span>
                                              <span class="n">color</span><span class="o">=</span><span class="n">colors</span><span class="p">[</span><span class="n">count</span><span class="p">],</span> <span class="n">ls</span><span class="o">=</span><span class="n">ls</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="n">linewidth</span><span class="p">)</span>
                 <span class="n">mi</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmpmi</span><span class="p">)</span>
                 <span class="n">ma</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmpma</span><span class="p">)</span>
@@ -974,15 +832,7 @@
     <span class="c1">#Util.show_and_save_image(fig, file, save, lgd=legends)</span>
 
 
-<div class="viewcode-block" id="plot_probability_distributions"><a class="viewcode-back" href="../../../pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.plot_probability_distributions">[docs]</a><span class="k">def</span> <span class="nf">plot_probability_distributions</span><span class="p">(</span><span class="n">pmfs</span><span class="p">,</span> <span class="n">lcolors</span><span class="p">,</span> <span class="n">tam</span><span class="o">=</span><span class="p">[</span><span class="mi">15</span><span class="p">,</span> <span class="mi">7</span><span class="p">]):</span>
-    <span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="n">tam</span><span class="p">)</span>
-    <span class="n">ax</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">111</span><span class="p">)</span>
 
-    <span class="k">for</span> <span class="n">k</span><span class="p">,</span><span class="n">m</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">pmfs</span><span class="p">,</span><span class="n">start</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
-        <span class="n">m</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">ax</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="n">lcolors</span><span class="p">[</span><span class="n">k</span><span class="p">])</span>
-
-    <span class="n">handles0</span><span class="p">,</span> <span class="n">labels0</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">get_legend_handles_labels</span><span class="p">()</span>
-    <span class="n">ax</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">handles0</span><span class="p">,</span> <span class="n">labels0</span><span class="p">)</span></div>
 
 
 
diff --git a/docs/build/html/_modules/pyFTS/common/Util.html b/docs/build/html/_modules/pyFTS/common/Util.html
index c506c4d..b58221c 100644
--- a/docs/build/html/_modules/pyFTS/common/Util.html
+++ b/docs/build/html/_modules/pyFTS/common/Util.html
@@ -80,9 +80,199 @@
 <span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
 <span class="kn">import</span> <span class="nn">dill</span>
 <span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
+<span class="kn">import</span> <span class="nn">matplotlib.cm</span> <span class="k">as</span> <span class="nn">cmx</span>
+<span class="kn">import</span> <span class="nn">matplotlib.colors</span> <span class="k">as</span> <span class="nn">pltcolors</span>
+<span class="kn">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>
+
+
+
+
+<div class="viewcode-block" id="plot_compared_intervals_ahead"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.plot_compared_intervals_ahead">[docs]</a><span class="k">def</span> <span class="nf">plot_compared_intervals_ahead</span><span class="p">(</span><span class="n">original</span><span class="p">,</span> <span class="n">models</span><span class="p">,</span> <span class="n">colors</span><span class="p">,</span> <span class="n">distributions</span><span class="p">,</span> <span class="n">time_from</span><span class="p">,</span> <span class="n">time_to</span><span class="p">,</span> <span class="n">intervals</span> <span class="o">=</span> <span class="kc">True</span><span class="p">,</span>
+                               <span class="n">save</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">file</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">tam</span><span class="o">=</span><span class="p">[</span><span class="mi">20</span><span class="p">,</span> <span class="mi">5</span><span class="p">],</span> <span class="n">resolution</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span>
+                               <span class="n">cmap</span><span class="o">=</span><span class="s1">&#39;Blues&#39;</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="mf">1.5</span><span class="p">):</span>
+    <span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Plot the forecasts of several one step ahead models, by point or by interval</span>
+
+<span class="sd">    :param original: Original time series data (list)</span>
+<span class="sd">    :param models: List of models to compare</span>
+<span class="sd">    :param colors: List of models colors</span>
+<span class="sd">    :param distributions: True to plot a distribution</span>
+<span class="sd">    :param time_from: index of data poit to start the ahead forecasting</span>
+<span class="sd">    :param time_to: number of steps ahead to forecast</span>
+<span class="sd">    :param interpol: Fill space between distribution plots</span>
+<span class="sd">    :param save: Save the picture on file</span>
+<span class="sd">    :param file: Filename to save the picture</span>
+<span class="sd">    :param tam: Size of the picture</span>
+<span class="sd">    :param resolution:</span>
+<span class="sd">    :param cmap: Color map to be used on distribution plot</span>
+<span class="sd">    :param option: Distribution type to be passed for models</span>
+<span class="sd">    :return:</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+    <span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="n">tam</span><span class="p">)</span>
+    <span class="n">ax</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">111</span><span class="p">)</span>
+
+    <span class="n">cm</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">get_cmap</span><span class="p">(</span><span class="n">cmap</span><span class="p">)</span>
+    <span class="n">cNorm</span> <span class="o">=</span> <span class="n">pltcolors</span><span class="o">.</span><span class="n">Normalize</span><span class="p">(</span><span class="n">vmin</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="n">vmax</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
+    <span class="n">scalarMap</span> <span class="o">=</span> <span class="n">cmx</span><span class="o">.</span><span class="n">ScalarMappable</span><span class="p">(</span><span class="n">norm</span><span class="o">=</span><span class="n">cNorm</span><span class="p">,</span> <span class="n">cmap</span><span class="o">=</span><span class="n">cm</span><span class="p">)</span>
+
+    <span class="k">if</span> <span class="n">resolution</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span> <span class="n">resolution</span> <span class="o">=</span> <span class="p">(</span><span class="nb">max</span><span class="p">(</span><span class="n">original</span><span class="p">)</span> <span class="o">-</span> <span class="nb">min</span><span class="p">(</span><span class="n">original</span><span class="p">))</span> <span class="o">/</span> <span class="mi">100</span>
+
+    <span class="n">mi</span> <span class="o">=</span> <span class="p">[]</span>
+    <span class="n">ma</span> <span class="o">=</span> <span class="p">[]</span>
+
+    <span class="k">for</span> <span class="n">count</span><span class="p">,</span> <span class="n">fts</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">models</span><span class="p">,</span> <span class="n">start</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
+        <span class="k">if</span> <span class="n">fts</span><span class="o">.</span><span class="n">has_probability_forecasting</span> <span class="ow">and</span> <span class="n">distributions</span><span class="p">[</span><span class="n">count</span><span class="p">]:</span>
+            <span class="n">density</span> <span class="o">=</span> <span class="n">fts</span><span class="o">.</span><span class="n">forecast_ahead_distribution</span><span class="p">(</span><span class="n">original</span><span class="p">[</span><span class="n">time_from</span> <span class="o">-</span> <span class="n">fts</span><span class="o">.</span><span class="n">order</span><span class="p">:</span><span class="n">time_from</span><span class="p">],</span> <span class="n">time_to</span><span class="p">,</span>
+                                                      <span class="n">resolution</span><span class="o">=</span><span class="n">resolution</span><span class="p">)</span>
+
+            <span class="c1">#plot_density_scatter(ax, cmap, density, fig, resolution, time_from, time_to)</span>
+            <span class="n">plot_density_rectange</span><span class="p">(</span><span class="n">ax</span><span class="p">,</span> <span class="n">cm</span><span class="p">,</span> <span class="n">density</span><span class="p">,</span> <span class="n">fig</span><span class="p">,</span> <span class="n">resolution</span><span class="p">,</span> <span class="n">time_from</span><span class="p">,</span> <span class="n">time_to</span><span class="p">)</span>
+
+        <span class="k">if</span> <span class="n">fts</span><span class="o">.</span><span class="n">has_interval_forecasting</span> <span class="ow">and</span> <span class="n">intervals</span><span class="p">:</span>
+            <span class="n">forecasts</span> <span class="o">=</span> <span class="n">fts</span><span class="o">.</span><span class="n">forecast_ahead_interval</span><span class="p">(</span><span class="n">original</span><span class="p">[</span><span class="n">time_from</span> <span class="o">-</span> <span class="n">fts</span><span class="o">.</span><span class="n">order</span><span class="p">:</span><span class="n">time_from</span><span class="p">],</span> <span class="n">time_to</span><span class="p">)</span>
+            <span class="n">lower</span> <span class="o">=</span> <span class="p">[</span><span class="n">kk</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="n">forecasts</span><span class="p">]</span>
+            <span class="n">upper</span> <span class="o">=</span> <span class="p">[</span><span class="n">kk</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="n">forecasts</span><span class="p">]</span>
+            <span class="n">mi</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">min</span><span class="p">(</span><span class="n">lower</span><span class="p">))</span>
+            <span class="n">ma</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">max</span><span class="p">(</span><span class="n">upper</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">time_from</span> <span class="o">-</span> <span class="n">fts</span><span class="o">.</span><span class="n">order</span><span class="p">):</span>
+                <span class="n">lower</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
+                <span class="n">upper</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
+            <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">lower</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="n">colors</span><span class="p">[</span><span class="n">count</span><span class="p">],</span> <span class="n">label</span><span class="o">=</span><span class="n">fts</span><span class="o">.</span><span class="n">shortname</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="n">linewidth</span><span class="p">)</span>
+            <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">upper</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="n">colors</span><span class="p">[</span><span class="n">count</span><span class="p">],</span> <span class="n">linewidth</span><span class="o">=</span><span class="n">linewidth</span><span class="o">*</span><span class="mf">1.5</span><span class="p">)</span>
+
+    <span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">original</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;black&#39;</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="s2">&quot;Original&quot;</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="n">linewidth</span><span class="o">*</span><span class="mf">1.5</span><span class="p">)</span>
+    <span class="n">handles0</span><span class="p">,</span> <span class="n">labels0</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">get_legend_handles_labels</span><span class="p">()</span>
+    <span class="k">if</span> <span class="kc">True</span> <span class="ow">in</span> <span class="n">distributions</span><span class="p">:</span>
+        <span class="n">lgd</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">handles0</span><span class="p">,</span> <span class="n">labels0</span><span class="p">,</span> <span class="n">loc</span><span class="o">=</span><span class="mi">2</span><span class="p">)</span>
+    <span class="k">else</span><span class="p">:</span>
+        <span class="n">lgd</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">handles0</span><span class="p">,</span> <span class="n">labels0</span><span class="p">,</span> <span class="n">loc</span><span class="o">=</span><span class="mi">2</span><span class="p">,</span> <span class="n">bbox_to_anchor</span><span class="o">=</span><span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mi">1</span><span class="p">))</span>
+    <span class="n">_mi</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">mi</span><span class="p">)</span>
+    <span class="k">if</span> <span class="n">_mi</span> <span class="o">&lt;</span> <span class="mi">0</span><span class="p">:</span>
+        <span class="n">_mi</span> <span class="o">*=</span> <span class="mf">1.1</span>
+    <span class="k">else</span><span class="p">:</span>
+        <span class="n">_mi</span> <span class="o">*=</span> <span class="mf">0.9</span>
+    <span class="n">_ma</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">ma</span><span class="p">)</span>
+    <span class="k">if</span> <span class="n">_ma</span> <span class="o">&lt;</span> <span class="mi">0</span><span class="p">:</span>
+        <span class="n">_ma</span> <span class="o">*=</span> <span class="mf">0.9</span>
+    <span class="k">else</span><span class="p">:</span>
+        <span class="n">_ma</span> <span class="o">*=</span> <span class="mf">1.1</span>
+
+    <span class="n">ax</span><span class="o">.</span><span class="n">set_ylim</span><span class="p">([</span><span class="n">_mi</span><span class="p">,</span> <span class="n">_ma</span><span class="p">])</span>
+    <span class="n">ax</span><span class="o">.</span><span class="n">set_ylabel</span><span class="p">(</span><span class="s1">&#39;F(T)&#39;</span><span class="p">)</span>
+    <span class="n">ax</span><span class="o">.</span><span class="n">set_xlabel</span><span class="p">(</span><span class="s1">&#39;T&#39;</span><span class="p">)</span>
+    <span class="n">ax</span><span class="o">.</span><span class="n">set_xlim</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="nb">len</span><span class="p">(</span><span class="n">original</span><span class="p">)])</span>
+
+    <span class="n">show_and_save_image</span><span class="p">(</span><span class="n">fig</span><span class="p">,</span> <span class="n">file</span><span class="p">,</span> <span class="n">save</span><span class="p">,</span> <span class="n">lgd</span><span class="o">=</span><span class="n">lgd</span><span class="p">)</span></div>
+
+
+
+<div class="viewcode-block" id="plot_density_rectange"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.plot_density_rectange">[docs]</a><span class="k">def</span> <span class="nf">plot_density_rectange</span><span class="p">(</span><span class="n">ax</span><span class="p">,</span> <span class="n">cmap</span><span class="p">,</span> <span class="n">density</span><span class="p">,</span> <span class="n">fig</span><span class="p">,</span> <span class="n">resolution</span><span class="p">,</span> <span class="n">time_from</span><span class="p">,</span> <span class="n">time_to</span><span class="p">):</span>
+    <span class="sd">&quot;&quot;&quot;</span>
+<span class="sd">    Auxiliar function to plot_compared_intervals_ahead</span>
+<span class="sd">    &quot;&quot;&quot;</span>
+    <span class="kn">from</span> <span class="nn">matplotlib.patches</span> <span class="k">import</span> <span class="n">Rectangle</span>
+    <span class="kn">from</span> <span class="nn">matplotlib.collections</span> <span class="k">import</span> <span class="n">PatchCollection</span>
+    <span class="n">patches</span> <span class="o">=</span> <span class="p">[]</span>
+    <span class="n">colors</span> <span class="o">=</span> <span class="p">[]</span>
+    <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">density</span><span class="o">.</span><span class="n">index</span><span class="p">:</span>
+        <span class="k">for</span> <span class="n">y</span> <span class="ow">in</span> <span class="n">density</span><span class="o">.</span><span class="n">columns</span><span class="p">:</span>
+            <span class="n">s</span> <span class="o">=</span> <span class="n">Rectangle</span><span class="p">((</span><span class="n">time_from</span> <span class="o">+</span> <span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">),</span> <span class="mi">1</span><span class="p">,</span> <span class="n">resolution</span><span class="p">,</span> <span class="n">fill</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">lw</span> <span class="o">=</span> <span class="mi">0</span><span class="p">)</span>
+            <span class="n">patches</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">s</span><span class="p">)</span>
+            <span class="n">colors</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">density</span><span class="p">[</span><span class="n">y</span><span class="p">][</span><span class="n">x</span><span class="p">]</span><span class="o">*</span><span class="mi">5</span><span class="p">)</span>
+    <span class="n">pc</span> <span class="o">=</span> <span class="n">PatchCollection</span><span class="p">(</span><span class="n">patches</span><span class="o">=</span><span class="n">patches</span><span class="p">,</span> <span class="n">match_original</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+    <span class="n">pc</span><span class="o">.</span><span class="n">set_clim</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span>
+    <span class="n">pc</span><span class="o">.</span><span class="n">set_cmap</span><span class="p">(</span><span class="n">cmap</span><span class="p">)</span>
+    <span class="n">pc</span><span class="o">.</span><span class="n">set_array</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">colors</span><span class="p">))</span>
+    <span class="n">ax</span><span class="o">.</span><span class="n">add_collection</span><span class="p">(</span><span class="n">pc</span><span class="p">)</span>
+    <span class="n">cb</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">pc</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">)</span>
+    <span class="n">cb</span><span class="o">.</span><span class="n">set_label</span><span class="p">(</span><span class="s1">&#39;Density&#39;</span><span class="p">)</span></div>
+
+
+<div class="viewcode-block" id="plot_probability_distributions"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.plot_probability_distributions">[docs]</a><span class="k">def</span> <span class="nf">plot_probability_distributions</span><span class="p">(</span><span class="n">pmfs</span><span class="p">,</span> <span class="n">lcolors</span><span class="p">,</span> <span class="n">tam</span><span class="o">=</span><span class="p">[</span><span class="mi">15</span><span class="p">,</span> <span class="mi">7</span><span class="p">]):</span>
+    <span class="n">fig</span> <span class="o">=</span> <span class="n">plt</span><span class="o">.</span><span class="n">figure</span><span class="p">(</span><span class="n">figsize</span><span class="o">=</span><span class="n">tam</span><span class="p">)</span>
+    <span class="n">ax</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">add_subplot</span><span class="p">(</span><span class="mi">111</span><span class="p">)</span>
+
+    <span class="k">for</span> <span class="n">k</span><span class="p">,</span><span class="n">m</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">pmfs</span><span class="p">,</span><span class="n">start</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
+        <span class="n">m</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">ax</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="n">lcolors</span><span class="p">[</span><span class="n">k</span><span class="p">])</span>
+
+    <span class="n">handles0</span><span class="p">,</span> <span class="n">labels0</span> <span class="o">=</span> <span class="n">ax</span><span class="o">.</span><span class="n">get_legend_handles_labels</span><span class="p">()</span>
+    <span class="n">ax</span><span class="o">.</span><span class="n">legend</span><span class="p">(</span><span class="n">handles0</span><span class="p">,</span> <span class="n">labels0</span><span class="p">)</span></div>
+
+<div class="viewcode-block" id="plot_distribution"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.plot_distribution">[docs]</a><span class="k">def</span> <span class="nf">plot_distribution</span><span class="p">(</span><span class="n">ax</span><span class="p">,</span> <span class="n">cmap</span><span class="p">,</span> <span class="n">probabilitydist</span><span class="p">,</span> <span class="n">fig</span><span class="p">,</span> <span class="n">time_from</span><span class="p">,</span> <span class="n">reference_data</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
+    <span class="sd">&#39;&#39;&#39;</span>
+<span class="sd">    Plot forecasted ProbabilityDistribution objects on a matplotlib axis</span>
+
+<span class="sd">    :param ax: matplotlib axis</span>
+<span class="sd">    :param cmap: matplotlib colormap name</span>
+<span class="sd">    :param probabilitydist: list of ProbabilityDistribution objects</span>
+<span class="sd">    :param fig: matplotlib figure</span>
+<span class="sd">    :param time_from: starting time (on x axis) to begin the plots</span>
+<span class="sd">    :param reference_data:</span>
+<span class="sd">    :return:</span>
+<span class="sd">    &#39;&#39;&#39;</span>
+    <span class="kn">from</span> <span class="nn">matplotlib.patches</span> <span class="k">import</span> <span class="n">Rectangle</span>
+    <span class="kn">from</span> <span class="nn">matplotlib.collections</span> <span class="k">import</span> <span class="n">PatchCollection</span>
+    <span class="n">patches</span> <span class="o">=</span> <span class="p">[]</span>
+    <span class="n">colors</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">dt</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">probabilitydist</span><span class="p">):</span>
+        <span class="n">disp</span> <span class="o">=</span> <span class="mf">0.0</span>
+        <span class="k">if</span> <span class="n">reference_data</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="n">disp</span> <span class="o">=</span> <span class="n">reference_data</span><span class="p">[</span><span class="n">time_from</span><span class="o">+</span><span class="n">ct</span><span class="p">]</span>
+
+        <span class="k">for</span> <span class="n">y</span> <span class="ow">in</span> <span class="n">dt</span><span class="o">.</span><span class="n">bins</span><span class="p">:</span>
+            <span class="n">s</span> <span class="o">=</span> <span class="n">Rectangle</span><span class="p">((</span><span class="n">time_from</span><span class="o">+</span><span class="n">ct</span><span class="p">,</span> <span class="n">y</span><span class="o">+</span><span class="n">disp</span><span class="p">),</span> <span class="mi">1</span><span class="p">,</span> <span class="n">dt</span><span class="o">.</span><span class="n">resolution</span><span class="p">,</span> <span class="n">fill</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="n">lw</span> <span class="o">=</span> <span class="mi">0</span><span class="p">)</span>
+            <span class="n">patches</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">s</span><span class="p">)</span>
+            <span class="n">colors</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">dt</span><span class="o">.</span><span class="n">density</span><span class="p">(</span><span class="n">y</span><span class="p">))</span>
+    <span class="n">scale</span> <span class="o">=</span> <span class="n">Transformations</span><span class="o">.</span><span class="n">Scale</span><span class="p">()</span>
+    <span class="n">colors</span> <span class="o">=</span> <span class="n">scale</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">colors</span><span class="p">)</span>
+    <span class="n">pc</span> <span class="o">=</span> <span class="n">PatchCollection</span><span class="p">(</span><span class="n">patches</span><span class="o">=</span><span class="n">patches</span><span class="p">,</span> <span class="n">match_original</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
+    <span class="n">pc</span><span class="o">.</span><span class="n">set_clim</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mi">1</span><span class="p">])</span>
+    <span class="n">pc</span><span class="o">.</span><span class="n">set_cmap</span><span class="p">(</span><span class="n">cmap</span><span class="p">)</span>
+    <span class="n">pc</span><span class="o">.</span><span class="n">set_array</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">colors</span><span class="p">))</span>
+    <span class="n">ax</span><span class="o">.</span><span class="n">add_collection</span><span class="p">(</span><span class="n">pc</span><span class="p">)</span>
+    <span class="n">cb</span> <span class="o">=</span> <span class="n">fig</span><span class="o">.</span><span class="n">colorbar</span><span class="p">(</span><span class="n">pc</span><span class="p">,</span> <span class="n">ax</span><span class="o">=</span><span class="n">ax</span><span class="p">)</span>
+    <span class="n">cb</span><span class="o">.</span><span class="n">set_label</span><span class="p">(</span><span class="s1">&#39;Density&#39;</span><span class="p">)</span></div>
+
+
+<div class="viewcode-block" id="plot_interval"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.plot_interval">[docs]</a><span class="k">def</span> <span class="nf">plot_interval</span><span class="p">(</span><span class="n">axis</span><span class="p">,</span> <span class="n">intervals</span><span class="p">,</span> <span class="n">order</span><span class="p">,</span> <span class="n">label</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s1">&#39;red&#39;</span><span class="p">,</span> <span class="n">typeonlegend</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="s1">&#39;-&#39;</span><span class="p">,</span> <span class="n">linewidth</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
+    <span class="sd">&#39;&#39;&#39;</span>
+<span class="sd">    Plot forecasted intervals on matplotlib</span>
+
+<span class="sd">    :param axis: matplotlib axis</span>
+<span class="sd">    :param intervals: list of forecasted intervals</span>
+<span class="sd">    :param order: order of the model that create the forecasts</span>
+<span class="sd">    :param label: figure label</span>
+<span class="sd">    :param color: matplotlib color name</span>
+<span class="sd">    :param typeonlegend:</span>
+<span class="sd">    :param ls: matplotlib line style</span>
+<span class="sd">    :param linewidth: matplotlib width</span>
+<span class="sd">    :return:</span>
+<span class="sd">    &#39;&#39;&#39;</span>
+    <span class="n">lower</span> <span class="o">=</span> <span class="p">[</span><span class="n">kk</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="n">intervals</span><span class="p">]</span>
+    <span class="n">upper</span> <span class="o">=</span> <span class="p">[</span><span class="n">kk</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="n">intervals</span><span class="p">]</span>
+    <span class="n">mi</span> <span class="o">=</span> <span class="nb">min</span><span class="p">(</span><span class="n">lower</span><span class="p">)</span> <span class="o">*</span> <span class="mf">0.95</span>
+    <span class="n">ma</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">upper</span><span class="p">)</span> <span class="o">*</span> <span class="mf">1.05</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">order</span><span class="p">):</span>
+        <span class="n">lower</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
+        <span class="n">upper</span><span class="o">.</span><span class="n">insert</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
+    <span class="k">if</span> <span class="n">typeonlegend</span><span class="p">:</span> <span class="n">label</span> <span class="o">+=</span> <span class="s2">&quot; (Interval)&quot;</span>
+    <span class="n">axis</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">lower</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="n">color</span><span class="p">,</span> <span class="n">label</span><span class="o">=</span><span class="n">label</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="n">ls</span><span class="p">,</span><span class="n">linewidth</span><span class="o">=</span><span class="n">linewidth</span><span class="p">)</span>
+    <span class="n">axis</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">upper</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="n">color</span><span class="p">,</span> <span class="n">ls</span><span class="o">=</span><span class="n">ls</span><span class="p">,</span><span class="n">linewidth</span><span class="o">=</span><span class="n">linewidth</span><span class="p">)</span>
+    <span class="k">return</span> <span class="p">[</span><span class="n">mi</span><span class="p">,</span> <span class="n">ma</span><span class="p">]</span></div>
 
 
 <div class="viewcode-block" id="plot_rules"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Util.plot_rules">[docs]</a><span class="k">def</span> <span class="nf">plot_rules</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">size</span><span class="o">=</span><span class="p">[</span><span class="mi">5</span><span class="p">,</span> <span class="mi">5</span><span class="p">],</span> <span class="n">axis</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">rules_by_axis</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="n">columns</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
+    <span class="sd">&#39;&#39;&#39;</span>
+<span class="sd">    Plot the FLRG rules of a FTS model on a matplotlib axis</span>
+
+<span class="sd">    :param model: FTS model</span>
+<span class="sd">    :param size: figure size</span>
+<span class="sd">    :param axis: matplotlib axis</span>
+<span class="sd">    :param rules_by_axis: number of rules plotted by column</span>
+<span class="sd">    :param columns: number of columns</span>
+<span class="sd">    :return:</span>
+<span class="sd">    &#39;&#39;&#39;</span>
     <span class="k">if</span> <span class="n">axis</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">rules_by_axis</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
         <span class="n">rows</span> <span class="o">=</span> <span class="mi">1</span>
     <span class="k">elif</span> <span class="n">axis</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="n">rules_by_axis</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
diff --git a/docs/build/html/_modules/pyFTS/data/artificial.html b/docs/build/html/_modules/pyFTS/data/artificial.html
index 9f8755f..f0fa2f3 100644
--- a/docs/build/html/_modules/pyFTS/data/artificial.html
+++ b/docs/build/html/_modules/pyFTS/data/artificial.html
@@ -373,7 +373,7 @@
 <div class="viewcode-block" id="random_walk"><a class="viewcode-back" href="../../../pyFTS.data.html#pyFTS.data.artificial.random_walk">[docs]</a><span class="k">def</span> <span class="nf">random_walk</span><span class="p">(</span><span class="n">n</span><span class="o">=</span><span class="mi">500</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="s1">&#39;gaussian&#39;</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    Simple random walk</span>
-<span class="sd">    </span>
+
 <span class="sd">    :param n: number of samples</span>
 <span class="sd">    :param type: &#39;gaussian&#39; or &#39;uniform&#39;</span>
 <span class="sd">    :return:</span>
diff --git a/docs/build/html/_modules/pyFTS/models/ensemble/ensemble.html b/docs/build/html/_modules/pyFTS/models/ensemble/ensemble.html
index ccd49ac..1f7587e 100644
--- a/docs/build/html/_modules/pyFTS/models/ensemble/ensemble.html
+++ b/docs/build/html/_modules/pyFTS/models/ensemble/ensemble.html
@@ -117,10 +117,9 @@
         <span class="bp">self</span><span class="o">.</span><span class="n">alpha</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;alpha&quot;</span><span class="p">,</span> <span class="mf">0.05</span><span class="p">)</span>
         <span class="sd">&quot;&quot;&quot;The quantiles &quot;&quot;&quot;</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">point_method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;point_method&#39;</span><span class="p">,</span> <span class="s1">&#39;mean&#39;</span><span class="p">)</span>
-        <span class="sd">&quot;&quot;&quot;The method used to mix the several model&#39;s forecasts into a unique point forecast. Options: mean, median, quantile&quot;&quot;&quot;</span>
+        <span class="sd">&quot;&quot;&quot;The method used to mix the several model&#39;s forecasts into a unique point forecast. Options: mean, median, quantile, exponential&quot;&quot;&quot;</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">interval_method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;interval_method&#39;</span><span class="p">,</span> <span class="s1">&#39;quantile&#39;</span><span class="p">)</span>
         <span class="sd">&quot;&quot;&quot;The method used to mix the several model&#39;s forecasts into a interval forecast. Options: quantile, extremum, normal&quot;&quot;&quot;</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">order</span> <span class="o">=</span> <span class="mi">1</span>
 
 <div class="viewcode-block" id="EnsembleFTS.append_model"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS.append_model">[docs]</a>    <span class="k">def</span> <span class="nf">append_model</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">model</span><span class="p">):</span>
         <span class="sd">&quot;&quot;&quot;</span>
@@ -137,8 +136,12 @@
             <span class="bp">self</span><span class="o">.</span><span class="n">is_multivariate</span> <span class="o">=</span> <span class="kc">True</span>
 
         <span class="k">if</span> <span class="n">model</span><span class="o">.</span><span class="n">has_seasonality</span><span class="p">:</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">has_seasonality</span> <span class="o">=</span> <span class="kc">True</span></div>
+            <span class="bp">self</span><span class="o">.</span><span class="n">has_seasonality</span> <span class="o">=</span> <span class="kc">True</span>
 
+        <span class="k">if</span> <span class="n">model</span><span class="o">.</span><span class="n">original_min</span> <span class="o">&lt;</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_min</span><span class="p">:</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">original_min</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">original_min</span>
+        <span class="k">elif</span> <span class="n">model</span><span class="o">.</span><span class="n">original_max</span> <span class="o">&gt;</span> <span class="bp">self</span><span class="o">.</span><span class="n">original_max</span><span class="p">:</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">original_max</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">original_max</span></div>
 
 <div class="viewcode-block" id="EnsembleFTS.train"><a class="viewcode-back" href="../../../../pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS.train">[docs]</a>    <span class="k">def</span> <span class="nf">train</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
         <span class="k">pass</span></div>
@@ -154,9 +157,9 @@
                     <span class="n">data</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_data</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
 
                 <span class="n">sample</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="o">-</span><span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">:]</span>
-                <span class="n">forecast</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">forecast</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
+                <span class="n">forecast</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
                 <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">forecast</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">))</span> <span class="ow">and</span> <span class="nb">len</span><span class="p">(</span><span class="n">forecast</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
-                    <span class="n">forecast</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">forecast</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
+                    <span class="n">forecast</span> <span class="o">=</span> <span class="n">forecast</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span>
                 <span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">forecast</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span><span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">))</span> <span class="ow">and</span> <span class="nb">len</span><span class="p">(</span><span class="n">forecast</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
                     <span class="n">forecast</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span>
             <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">forecast</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
@@ -173,6 +176,13 @@
         <span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">point_method</span> <span class="o">==</span> <span class="s1">&#39;quantile&#39;</span><span class="p">:</span>
             <span class="n">alpha</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s2">&quot;alpha&quot;</span><span class="p">,</span><span class="mf">0.05</span><span class="p">)</span>
             <span class="n">ret</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">percentile</span><span class="p">(</span><span class="n">forecasts</span><span class="p">,</span> <span class="n">alpha</span><span class="o">*</span><span class="mi">100</span><span class="p">)</span>
+        <span class="k">elif</span> <span class="bp">self</span><span class="o">.</span><span class="n">point_method</span> <span class="o">==</span> <span class="s1">&#39;exponential&#39;</span><span class="p">:</span>
+            <span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">models</span><span class="p">)</span>
+            <span class="k">if</span> <span class="n">l</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
+                <span class="k">return</span> <span class="n">forecasts</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
+            <span class="n">w</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="o">-</span><span class="p">(</span><span class="n">l</span> <span class="o">-</span> <span class="n">k</span><span class="p">))</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">l</span><span class="p">)])</span>
+            <span class="n">w</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">nansum</span><span class="p">(</span><span class="n">w</span><span class="p">)</span>
+            <span class="n">ret</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nansum</span><span class="p">([</span><span class="n">w</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="o">*</span> <span class="n">forecasts</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">l</span><span class="p">)])</span>
 
         <span class="k">return</span> <span class="n">ret</span></div>
 
diff --git a/docs/build/html/_modules/pyFTS/models/hofts.html b/docs/build/html/_modules/pyFTS/models/hofts.html
index cc14f55..28585bb 100644
--- a/docs/build/html/_modules/pyFTS/models/hofts.html
+++ b/docs/build/html/_modules/pyFTS/models/hofts.html
@@ -140,8 +140,23 @@
         <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">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">midpoint</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="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="bp">self</span><span class="o">.</span><span class="n">midpoint</span> <span class="o">=</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>
+
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">midpoint</span></div>
+
+<div class="viewcode-block" id="WeightedHighOrderFLRG.get_lower"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFLRG.get_lower">[docs]</a>    <span class="k">def</span> <span class="nf">get_lower</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
+        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">lower</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="n">lw</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">s</span><span class="p">]</span><span class="o">.</span><span class="n">lower</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()])</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">lower</span> <span class="o">=</span> <span class="n">lw</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>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">lower</span></div>
+
+<div class="viewcode-block" id="WeightedHighOrderFLRG.get_upper"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFLRG.get_upper">[docs]</a>    <span class="k">def</span> <span class="nf">get_upper</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
+        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">upper</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="n">up</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">s</span><span class="p">]</span><span class="o">.</span><span class="n">upper</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()])</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">upper</span> <span class="o">=</span> <span class="n">up</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>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">upper</span></div>
 
     <span class="k">def</span> <span class="nf">__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>
diff --git a/docs/build/html/_modules/pyFTS/models/ifts.html b/docs/build/html/_modules/pyFTS/models/ifts.html
index 90b8359..32ce37c 100644
--- a/docs/build/html/_modules/pyFTS/models/ifts.html
+++ b/docs/build/html/_modules/pyFTS/models/ifts.html
@@ -87,7 +87,7 @@
 <span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="k">import</span> <span class="n">hofts</span>
 
 
-<div class="viewcode-block" id="IntervalFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ifts.IntervalFTS">[docs]</a><span class="k">class</span> <span class="nc">IntervalFTS</span><span class="p">(</span><span class="n">hofts</span><span class="o">.</span><span class="n">HighOrderFTS</span><span class="p">):</span>
+<div class="viewcode-block" id="IntervalFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ifts.IntervalFTS">[docs]</a><span class="k">class</span> <span class="nc">IntervalFTS</span><span class="p">(</span><span class="n">hofts</span><span class="o">.</span><span class="n">WeightedHighOrderFTS</span><span class="p">):</span>
     <span class="sd">&quot;&quot;&quot;</span>
 <span class="sd">    High Order Interval Fuzzy Time Series</span>
 <span class="sd">    &quot;&quot;&quot;</span>
@@ -117,9 +117,9 @@
         <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="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
                 <span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()]</span>
-                <span class="n">ret</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
+                <span class="n">ret</span> <span class="o">=</span> <span class="n">tmp</span><span class="o">.</span><span class="n">get_lower</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
             <span class="k">else</span><span class="p">:</span>
-                <span class="n">ret</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]]</span><span class="o">.</span><span class="n">lower</span>
+                <span class="n">ret</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">lower</span>
         <span class="k">return</span> <span class="n">ret</span></div>
 
 <div class="viewcode-block" id="IntervalFTS.get_sequence_membership"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ifts.IntervalFTS.get_sequence_membership">[docs]</a>    <span class="k">def</span> <span class="nf">get_sequence_membership</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">fuzzySets</span><span class="p">):</span>
diff --git a/docs/build/html/_modules/pyFTS/models/incremental/IncrementalEnsemble.html b/docs/build/html/_modules/pyFTS/models/incremental/IncrementalEnsemble.html
index 2d34de9..30a7ccd 100644
--- a/docs/build/html/_modules/pyFTS/models/incremental/IncrementalEnsemble.html
+++ b/docs/build/html/_modules/pyFTS/models/incremental/IncrementalEnsemble.html
@@ -112,9 +112,14 @@
         <span class="bp">self</span><span class="o">.</span><span class="n">batch_size</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;batch_size&#39;</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
         <span class="sd">&quot;&quot;&quot;The batch interval between each retraining&quot;&quot;&quot;</span>
 
+        <span class="bp">self</span><span class="o">.</span><span class="n">num_models</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;num_models&#39;</span><span class="p">,</span> <span class="mi">5</span><span class="p">)</span>
+        <span class="sd">&quot;&quot;&quot;The number of models to hold in the ensemble&quot;&quot;&quot;</span>
+
+        <span class="bp">self</span><span class="o">.</span><span class="n">point_method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;point_method&#39;</span><span class="p">,</span> <span class="s1">&#39;exponential&#39;</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">uod_clip</span> <span class="o">=</span> <span class="kc">False</span>
-        <span class="c1">#self.max_lag = self.window_length + self.max_lag</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">window_length</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span>
 
 <div class="viewcode-block" id="IncrementalEnsembleFTS.train"><a class="viewcode-back" href="../../../../pyFTS.models.incremental.html#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.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>
 
@@ -123,16 +128,9 @@
         <span class="k">if</span> <span class="n">model</span><span class="o">.</span><span class="n">is_high_order</span><span class="p">:</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="n">partitioner</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">model</span><span class="o">.</span><span class="n">fit</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
-        <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">models</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</span><span class="p">:</span>
-            <span class="bp">self</span><span class="o">.</span><span class="n">models</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
-        <span class="bp">self</span><span class="o">.</span><span class="n">models</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">model</span><span class="p">)</span></div>
-
-    <span class="k">def</span> <span class="nf">_point_smoothing</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">forecasts</span><span class="p">):</span>
-        <span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">models</span><span class="p">)</span>
-
-        <span class="n">ret</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nansum</span><span class="p">([</span><span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="o">-</span><span class="p">(</span><span class="n">l</span><span class="o">-</span><span class="n">k</span><span class="p">))</span> <span class="o">*</span> <span class="n">forecasts</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">l</span><span class="p">)])</span>
-
-        <span class="k">return</span> <span class="n">ret</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">append_model</span><span class="p">(</span><span class="n">model</span><span class="p">)</span>
+        <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">models</span><span class="p">)</span> <span class="o">&gt;</span> <span class="bp">self</span><span class="o">.</span><span class="n">num_models</span><span class="p">:</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">models</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span></div>
 
 <div class="viewcode-block" id="IncrementalEnsembleFTS.forecast"><a class="viewcode-back" href="../../../../pyFTS.models.incremental.html#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.forecast">[docs]</a>    <span class="k">def</span> <span class="nf">forecast</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
         <span class="n">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
@@ -143,18 +141,21 @@
 
         <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">data_window</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">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">k2</span> <span class="o">=</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="k">if</span> <span class="n">k</span> <span class="o">&gt;=</span> <span class="bp">self</span><span class="o">.</span><span class="n">window_length</span><span class="p">:</span>
+            <span class="n">data_window</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">k2</span><span class="p">])</span>
+
+            <span class="k">if</span> <span class="n">k2</span> <span class="o">&gt;=</span> <span class="bp">self</span><span class="o">.</span><span class="n">window_length</span><span class="p">:</span>
                 <span class="n">data_window</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="mi">0</span><span class="p">)</span>
 
-            <span class="k">if</span> <span class="n">k</span> <span class="o">%</span> <span class="bp">self</span><span class="o">.</span><span class="n">batch_size</span> <span class="o">==</span> <span class="mi">0</span> <span class="ow">and</span> <span class="n">k</span> <span class="o">&gt;=</span> <span class="bp">self</span><span class="o">.</span><span class="n">window_length</span><span class="p">:</span>
+            <span class="k">if</span> <span class="n">k</span> <span class="o">%</span> <span class="bp">self</span><span class="o">.</span><span class="n">batch_size</span> <span class="o">==</span> <span class="mi">0</span> <span class="ow">and</span> <span class="n">k2</span> <span class="o">&gt;=</span> <span class="bp">self</span><span class="o">.</span><span class="n">window_length</span><span class="p">:</span>
                 <span class="bp">self</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="n">data_window</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</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">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_models_forecasts</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
-            <span class="n">point</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">_point_smoothing</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
-            <span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">point</span><span class="p">)</span>
+            <span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">models</span><span class="p">)</span> <span class="o">&gt;</span> <span class="mi">0</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">k2</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
+                <span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_models_forecasts</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
+                <span class="n">point</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">get_point</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
+                <span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">point</span><span class="p">)</span>
 
         <span class="k">return</span> <span class="n">ret</span></div></div>
 
diff --git a/docs/build/html/_modules/pyFTS/models/incremental/TimeVariant.html b/docs/build/html/_modules/pyFTS/models/incremental/TimeVariant.html
index 529e7d9..799339e 100644
--- a/docs/build/html/_modules/pyFTS/models/incremental/TimeVariant.html
+++ b/docs/build/html/_modules/pyFTS/models/incremental/TimeVariant.html
@@ -111,6 +111,7 @@
         <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">uod_clip</span> <span class="o">=</span> <span class="kc">False</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">window_length</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">order</span>
+        <span class="bp">self</span><span class="o">.</span><span class="n">is_wrapper</span> <span class="o">=</span> <span class="kc">True</span>
 
 <div class="viewcode-block" id="Retrainer.train"><a class="viewcode-back" href="../../../../pyFTS.models.incremental.html#pyFTS.models.incremental.TimeVariant.Retrainer.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">partitioner</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner_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="o">**</span><span class="bp">self</span><span class="o">.</span><span class="n">partitioner_params</span><span class="p">)</span>
diff --git a/docs/build/html/_modules/pyFTS/models/multivariate/flrg.html b/docs/build/html/_modules/pyFTS/models/multivariate/flrg.html
index 7767f05..0c8292c 100644
--- a/docs/build/html/_modules/pyFTS/models/multivariate/flrg.html
+++ b/docs/build/html/_modules/pyFTS/models/multivariate/flrg.html
@@ -96,7 +96,6 @@
                 <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="n">var</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
             <span class="bp">self</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="n">var</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">fset</span><span class="p">)</span></div>
 
-
 <div class="viewcode-block" id="FLRG.append_rhs"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.flrg.FLRG.append_rhs">[docs]</a>    <span class="k">def</span> <span class="nf">append_rhs</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">fset</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
         <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">add</span><span class="p">(</span><span class="n">fset</span><span class="p">)</span></div>
 
@@ -108,6 +107,18 @@
 
         <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmin</span><span class="p">(</span><span class="n">mvs</span><span class="p">)</span></div>
 
+<div class="viewcode-block" id="FLRG.get_lower"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.flrg.FLRG.get_lower">[docs]</a>    <span class="k">def</span> <span class="nf">get_lower</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
+        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">lower</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">lower</span> <span class="o">=</span> <span class="nb">min</span><span class="p">([</span><span class="n">sets</span><span class="p">[</span><span class="n">rhs</span><span class="p">]</span><span class="o">.</span><span class="n">lower</span> <span class="k">for</span> <span class="n">rhs</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">])</span>
+
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">lower</span></div>
+
+<div class="viewcode-block" id="FLRG.get_upper"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.flrg.FLRG.get_upper">[docs]</a>    <span class="k">def</span> <span class="nf">get_upper</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
+        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">upper</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">upper</span> <span class="o">=</span> <span class="nb">max</span><span class="p">([</span><span class="n">sets</span><span class="p">[</span><span class="n">rhs</span><span class="p">]</span><span class="o">.</span><span class="n">upper</span> <span class="k">for</span> <span class="n">rhs</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="p">])</span>
+
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">upper</span></div>
+
     <span class="k">def</span> <span class="nf">__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="p">:</span>
diff --git a/docs/build/html/_modules/pyFTS/models/multivariate/mvfts.html b/docs/build/html/_modules/pyFTS/models/multivariate/mvfts.html
index bb11981..4ed62a7 100644
--- a/docs/build/html/_modules/pyFTS/models/multivariate/mvfts.html
+++ b/docs/build/html/_modules/pyFTS/models/multivariate/mvfts.html
@@ -219,8 +219,9 @@
                         <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="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="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">mvs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_flrg</span><span class="o">.</span><span class="n">get_membership</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="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">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="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>
@@ -275,6 +276,49 @@
 
         <span class="k">return</span> <span class="n">ret</span></div>
 
+<div class="viewcode-block" id="MVFTS.forecast_interval"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.forecast_interval">[docs]</a>    <span class="k">def</span> <span class="nf">forecast_interval</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
+        <span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
+        <span class="n">ndata</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">apply_transformations</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
+        <span class="n">c</span> <span class="o">=</span> <span class="mi">0</span>
+        <span class="k">for</span> <span class="n">index</span><span class="p">,</span> <span class="n">row</span> <span class="ow">in</span> <span class="n">ndata</span><span class="o">.</span><span class="n">iterrows</span><span class="p">()</span> <span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">ndata</span><span class="p">,</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">)</span> <span class="k">else</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">ndata</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">row</span><span class="p">)</span>
+            <span class="n">flrs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrs</span><span class="p">(</span><span class="n">data_point</span><span class="p">)</span>
+            <span class="n">mvs</span> <span class="o">=</span> <span class="p">[]</span>
+            <span class="n">ups</span> <span class="o">=</span> <span class="p">[]</span>
+            <span class="n">los</span> <span class="o">=</span> <span class="p">[]</span>
+            <span class="k">for</span> <span class="n">flr</span> <span class="ow">in</span> <span class="n">flrs</span><span class="p">:</span>
+                <span class="n">flrg</span> <span class="o">=</span> <span class="n">mvflrg</span><span class="o">.</span><span class="n">FLRG</span><span class="p">(</span><span class="n">lhs</span><span class="o">=</span><span class="n">flr</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span>
+                <span class="k">if</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_key</span><span class="p">()</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span><span class="p">:</span>
+                    <span class="c1">#Naïve approach is applied when no rules were found</span>
+                    <span class="k">if</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="ow">in</span> <span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">:</span>
+                        <span class="n">fs</span> <span class="o">=</span> <span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">[</span><span class="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">fset</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">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">fs</span><span class="p">]</span>
+                        <span class="n">up</span> <span class="o">=</span> <span class="n">fset</span><span class="o">.</span><span class="n">upper</span>
+                        <span class="n">lo</span> <span class="o">=</span> <span class="n">fset</span><span class="o">.</span><span class="n">lower</span>
+                        <span class="n">mv</span> <span class="o">=</span> <span class="n">fset</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">data_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">name</span><span class="p">])</span>
+                        <span class="n">mvs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mv</span><span class="p">)</span>
+                        <span class="n">ups</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">up</span><span class="p">)</span>
+                        <span class="n">los</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">lo</span><span class="p">)</span>
+                    <span class="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="mf">0.</span><span class="p">)</span>
+                        <span class="n">ups</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">los</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">_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">mvs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_flrg</span><span class="o">.</span><span class="n">get_membership</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">ups</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_flrg</span><span class="o">.</span><span class="n">get_upper</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="n">los</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">_flrg</span><span class="o">.</span><span class="n">get_lower</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="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">up</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">mv</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">ups</span><span class="p">)</span><span class="o">.</span><span class="n">T</span><span class="p">)</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">nansum</span><span class="p">(</span><span class="n">mv</span><span class="p">)</span>
+            <span class="n">lo</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">mv</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">los</span><span class="p">)</span><span class="o">.</span><span class="n">T</span><span class="p">)</span> <span class="o">/</span> <span class="n">np</span><span class="o">.</span><span class="n">nansum</span><span class="p">(</span><span class="n">mv</span><span class="p">)</span>
+
+            <span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="n">lo</span><span class="p">,</span> <span class="n">up</span><span class="p">])</span>
+
+        <span class="n">ret</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">target_variable</span><span class="o">.</span><span class="n">apply_inverse_transformations</span><span class="p">(</span><span class="n">ret</span><span class="p">,</span>
+                                                           <span class="n">params</span><span class="o">=</span><span class="n">data</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">target_variable</span><span class="o">.</span><span class="n">data_label</span><span class="p">]</span><span class="o">.</span><span class="n">values</span><span class="p">)</span>
+        <span class="k">return</span> <span class="n">ret</span></div>
+
 
 <div class="viewcode-block" id="MVFTS.clone_parameters"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.clone_parameters">[docs]</a>    <span class="k">def</span> <span class="nf">clone_parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">model</span><span class="p">):</span>
         <span class="nb">super</span><span class="p">(</span><span class="n">MVFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="n">clone_parameters</span><span class="p">(</span><span class="n">model</span><span class="p">)</span>
diff --git a/docs/build/html/_modules/pyFTS/models/multivariate/wmvfts.html b/docs/build/html/_modules/pyFTS/models/multivariate/wmvfts.html
index 753ea68..8c28d39 100644
--- a/docs/build/html/_modules/pyFTS/models/multivariate/wmvfts.html
+++ b/docs/build/html/_modules/pyFTS/models/multivariate/wmvfts.html
@@ -107,8 +107,23 @@
         <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">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">midpoint</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="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="bp">self</span><span class="o">.</span><span class="n">midpoint</span> <span class="o">=</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>
+
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">midpoint</span></div>
+
+<div class="viewcode-block" id="WeightedFLRG.get_lower"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_lower">[docs]</a>    <span class="k">def</span> <span class="nf">get_lower</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
+        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">lower</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="n">lw</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">s</span><span class="p">]</span><span class="o">.</span><span class="n">lower</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()])</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">lower</span> <span class="o">=</span> <span class="n">lw</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>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">lower</span></div>
+
+<div class="viewcode-block" id="WeightedFLRG.get_upper"><a class="viewcode-back" href="../../../../pyFTS.models.multivariate.html#pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_upper">[docs]</a>    <span class="k">def</span> <span class="nf">get_upper</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">sets</span><span class="p">):</span>
+        <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">upper</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
+            <span class="n">up</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">s</span><span class="p">]</span><span class="o">.</span><span class="n">upper</span> <span class="k">for</span> <span class="n">s</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">RHS</span><span class="o">.</span><span class="n">keys</span><span class="p">()])</span>
+            <span class="bp">self</span><span class="o">.</span><span class="n">upper</span> <span class="o">=</span> <span class="n">up</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>
+        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">upper</span></div>
 
 
     <span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
diff --git a/docs/build/html/genindex.html b/docs/build/html/genindex.html
index 4470ab1..9cb0b93 100644
--- a/docs/build/html/genindex.html
+++ b/docs/build/html/genindex.html
@@ -354,8 +354,6 @@
         <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.hyperparam.html#pyFTS.hyperparam.GridSearch.cluster_method">cluster_method() (in module pyFTS.hyperparam.GridSearch)</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>
@@ -445,8 +443,6 @@
       <li><a href="pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.density">density() (pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution method)</a>
 </li>
       <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>
@@ -480,12 +476,10 @@
 </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><a href="pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.expected_value">expected_value() (pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution method)</a>
 </li>
   </ul></td>
   <td style="width: 33%; vertical-align: top;"><ul>
-      <li><a href="pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.expected_value">expected_value() (pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution method)</a>
-</li>
       <li><a href="pyFTS.partitioners.html#pyFTS.partitioners.parallel_util.explore_partitioners">explore_partitioners() (in module pyFTS.partitioners.parallel_util)</a>
 
       <ul>
@@ -666,6 +660,8 @@
         <li><a href="pyFTS.models.ensemble.html#pyFTS.models.ensemble.ensemble.EnsembleFTS.forecast_interval">(pyFTS.models.ensemble.ensemble.EnsembleFTS method)</a>
 </li>
         <li><a href="pyFTS.models.html#pyFTS.models.ifts.IntervalFTS.forecast_interval">(pyFTS.models.ifts.IntervalFTS method)</a>
+</li>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.mvfts.MVFTS.forecast_interval">(pyFTS.models.multivariate.mvfts.MVFTS method)</a>
 </li>
         <li><a href="pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS.forecast_interval">(pyFTS.models.nonstationary.cvfts.ConditionalVarianceFTS method)</a>
 </li>
@@ -971,7 +967,13 @@
       <li><a href="pyFTS.common.html#pyFTS.common.flrg.FLRG.get_lower">get_lower() (pyFTS.common.flrg.FLRG method)</a>
 
       <ul>
+        <li><a href="pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFLRG.get_lower">(pyFTS.models.hofts.WeightedHighOrderFLRG method)</a>
+</li>
         <li><a href="pyFTS.models.html#pyFTS.models.ifts.IntervalFTS.get_lower">(pyFTS.models.ifts.IntervalFTS method)</a>
+</li>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.flrg.FLRG.get_lower">(pyFTS.models.multivariate.flrg.FLRG method)</a>
+</li>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_lower">(pyFTS.models.multivariate.wmvfts.WeightedFLRG method)</a>
 </li>
         <li><a href="pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.common.FuzzySet.get_lower">(pyFTS.models.nonstationary.common.FuzzySet method)</a>
 </li>
@@ -1065,7 +1067,13 @@
       <li><a href="pyFTS.common.html#pyFTS.common.flrg.FLRG.get_upper">get_upper() (pyFTS.common.flrg.FLRG method)</a>
 
       <ul>
+        <li><a href="pyFTS.models.html#pyFTS.models.hofts.WeightedHighOrderFLRG.get_upper">(pyFTS.models.hofts.WeightedHighOrderFLRG method)</a>
+</li>
         <li><a href="pyFTS.models.html#pyFTS.models.ifts.IntervalFTS.get_upper">(pyFTS.models.ifts.IntervalFTS method)</a>
+</li>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.flrg.FLRG.get_upper">(pyFTS.models.multivariate.flrg.FLRG method)</a>
+</li>
+        <li><a href="pyFTS.models.multivariate.html#pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_upper">(pyFTS.models.multivariate.wmvfts.WeightedFLRG method)</a>
 </li>
         <li><a href="pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.common.FuzzySet.get_upper">(pyFTS.models.nonstationary.common.FuzzySet method)</a>
 </li>
@@ -1359,6 +1367,8 @@
       <li><a href="pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.flrg.NonStationaryFLRG">NonStationaryFLRG (class in pyFTS.models.nonstationary.flrg)</a>
 </li>
       <li><a href="pyFTS.models.nonstationary.html#pyFTS.models.nonstationary.nsfts.NonStationaryFTS">NonStationaryFTS (class in pyFTS.models.nonstationary.nsfts)</a>
+</li>
+      <li><a href="pyFTS.models.incremental.html#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.num_models">num_models (pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS attribute)</a>
 </li>
   </ul></td>
 </tr></table>
@@ -1470,7 +1480,7 @@
         <li><a href="pyFTS.probabilistic.html#pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution.plot">(pyFTS.probabilistic.ProbabilityDistribution.ProbabilityDistribution method)</a>
 </li>
       </ul></li>
-      <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.plot_compared_intervals_ahead">plot_compared_intervals_ahead() (in module pyFTS.benchmarks.benchmarks)</a>
+      <li><a href="pyFTS.common.html#pyFTS.common.Util.plot_compared_intervals_ahead">plot_compared_intervals_ahead() (in module pyFTS.common.Util)</a>
 </li>
       <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.plot_compared_series">plot_compared_series() (in module pyFTS.benchmarks.benchmarks)</a>
 </li>
@@ -1482,17 +1492,17 @@
 </li>
       <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.Util.plot_dataframe_probabilistic">plot_dataframe_probabilistic() (in module pyFTS.benchmarks.Util)</a>
 </li>
-      <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.plot_density_rectange">plot_density_rectange() (in module pyFTS.benchmarks.benchmarks)</a>
+      <li><a href="pyFTS.common.html#pyFTS.common.Util.plot_density_rectange">plot_density_rectange() (in module pyFTS.common.Util)</a>
 </li>
-      <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.plot_distribution">plot_distribution() (in module pyFTS.benchmarks.benchmarks)</a>
+      <li><a href="pyFTS.common.html#pyFTS.common.Util.plot_distribution">plot_distribution() (in module pyFTS.common.Util)</a>
 </li>
-      <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.plot_interval">plot_interval() (in module pyFTS.benchmarks.benchmarks)</a>
+      <li><a href="pyFTS.common.html#pyFTS.common.Util.plot_interval">plot_interval() (in module pyFTS.common.Util)</a>
 </li>
       <li><a href="pyFTS.partitioners.html#pyFTS.partitioners.Util.plot_partitioners">plot_partitioners() (in module pyFTS.partitioners.Util)</a>
 </li>
       <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.plot_point">plot_point() (in module pyFTS.benchmarks.benchmarks)</a>
 </li>
-      <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.plot_probability_distributions">plot_probability_distributions() (in module pyFTS.benchmarks.benchmarks)</a>
+      <li><a href="pyFTS.common.html#pyFTS.common.Util.plot_probability_distributions">plot_probability_distributions() (in module pyFTS.common.Util)</a>
 </li>
       <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.ResidualAnalysis.plot_residuals">plot_residuals() (in module pyFTS.benchmarks.ResidualAnalysis)</a>
 </li>
@@ -1559,8 +1569,6 @@
       <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.Util.process_common_data">process_common_data() (in module pyFTS.benchmarks.Util)</a>
 </li>
       <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.process_interval_jobs">process_interval_jobs() (in module pyFTS.benchmarks.benchmarks)</a>
-</li>
-      <li><a href="pyFTS.hyperparam.html#pyFTS.hyperparam.GridSearch.process_jobs">process_jobs() (in module pyFTS.hyperparam.GridSearch)</a>
 </li>
       <li><a href="pyFTS.benchmarks.html#pyFTS.benchmarks.benchmarks.process_point_jobs">process_point_jobs() (in module pyFTS.benchmarks.benchmarks)</a>
 </li>
@@ -1667,8 +1675,6 @@
       <li><a href="pyFTS.distributed.html#module-pyFTS.distributed.spark">pyFTS.distributed.spark (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>
diff --git a/docs/build/html/objects.inv b/docs/build/html/objects.inv
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diff --git a/docs/build/html/py-modindex.html b/docs/build/html/py-modindex.html
index d76a9c0..3e7aa3e 100644
--- a/docs/build/html/py-modindex.html
+++ b/docs/build/html/py-modindex.html
@@ -325,11 +325,6 @@
        <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;
diff --git a/docs/build/html/pyFTS.benchmarks.html b/docs/build/html/pyFTS.benchmarks.html
index 2060b42..24409c8 100644
--- a/docs/build/html/pyFTS.benchmarks.html
+++ b/docs/build/html/pyFTS.benchmarks.html
@@ -189,38 +189,6 @@
 <code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">plotCompared</code><span class="sig-paren">(</span><em>original</em>, <em>forecasts</em>, <em>labels</em>, <em>title</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#plotCompared"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.plotCompared" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
-<dl class="function">
-<dt id="pyFTS.benchmarks.benchmarks.plot_compared_intervals_ahead">
-<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">plot_compared_intervals_ahead</code><span class="sig-paren">(</span><em>original, models, colors, distributions, time_from, time_to, intervals=True, save=False, file=None, tam=[20, 5], resolution=None, cmap='Blues', linewidth=1.5</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#plot_compared_intervals_ahead"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.plot_compared_intervals_ahead" title="Permalink to this definition">¶</a></dt>
-<dd><p>Plot the forecasts of several one step ahead models, by point or by interval</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>original</strong> – Original time series data (list)</li>
-<li><strong>models</strong> – List of models to compare</li>
-<li><strong>colors</strong> – List of models colors</li>
-<li><strong>distributions</strong> – True to plot a distribution</li>
-<li><strong>time_from</strong> – index of data poit to start the ahead forecasting</li>
-<li><strong>time_to</strong> – number of steps ahead to forecast</li>
-<li><strong>interpol</strong> – Fill space between distribution plots</li>
-<li><strong>save</strong> – Save the picture on file</li>
-<li><strong>file</strong> – Filename to save the picture</li>
-<li><strong>tam</strong> – Size of the picture</li>
-<li><strong>resolution</strong> – </li>
-<li><strong>cmap</strong> – Color map to be used on distribution plot</li>
-<li><strong>option</strong> – Distribution type to be passed for models</li>
-</ul>
-</td>
-</tr>
-<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
-</td>
-</tr>
-</tbody>
-</table>
-</dd></dl>
-
 <dl class="function">
 <dt id="pyFTS.benchmarks.benchmarks.plot_compared_series">
 <code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">plot_compared_series</code><span class="sig-paren">(</span><em>original, models, colors, typeonlegend=False, save=False, file=None, tam=[20, 5], points=True, intervals=True, linewidth=1.5</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#plot_compared_series"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.plot_compared_series" title="Permalink to this definition">¶</a></dt>
@@ -250,32 +218,11 @@
 </table>
 </dd></dl>
 
-<dl class="function">
-<dt id="pyFTS.benchmarks.benchmarks.plot_density_rectange">
-<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">plot_density_rectange</code><span class="sig-paren">(</span><em>ax</em>, <em>cmap</em>, <em>density</em>, <em>fig</em>, <em>resolution</em>, <em>time_from</em>, <em>time_to</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#plot_density_rectange"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.plot_density_rectange" title="Permalink to this definition">¶</a></dt>
-<dd><p>Auxiliar function to plot_compared_intervals_ahead</p>
-</dd></dl>
-
-<dl class="function">
-<dt id="pyFTS.benchmarks.benchmarks.plot_distribution">
-<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">plot_distribution</code><span class="sig-paren">(</span><em>ax</em>, <em>cmap</em>, <em>probabilitydist</em>, <em>fig</em>, <em>time_from</em>, <em>reference_data=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#plot_distribution"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.plot_distribution" title="Permalink to this definition">¶</a></dt>
-<dd></dd></dl>
-
-<dl class="function">
-<dt id="pyFTS.benchmarks.benchmarks.plot_interval">
-<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">plot_interval</code><span class="sig-paren">(</span><em>axis</em>, <em>intervals</em>, <em>order</em>, <em>label</em>, <em>color='red'</em>, <em>typeonlegend=False</em>, <em>ls='-'</em>, <em>linewidth=1</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#plot_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.plot_interval" title="Permalink to this definition">¶</a></dt>
-<dd></dd></dl>
-
 <dl class="function">
 <dt id="pyFTS.benchmarks.benchmarks.plot_point">
 <code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">plot_point</code><span class="sig-paren">(</span><em>axis</em>, <em>points</em>, <em>order</em>, <em>label</em>, <em>color='red'</em>, <em>ls='-'</em>, <em>linewidth=1</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#plot_point"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.plot_point" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
-<dl class="function">
-<dt id="pyFTS.benchmarks.benchmarks.plot_probability_distributions">
-<code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">plot_probability_distributions</code><span class="sig-paren">(</span><em>pmfs, lcolors, tam=[15, 7]</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#plot_probability_distributions"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.plot_probability_distributions" title="Permalink to this definition">¶</a></dt>
-<dd></dd></dl>
-
 <dl class="function">
 <dt id="pyFTS.benchmarks.benchmarks.print_distribution_statistics">
 <code class="descclassname">pyFTS.benchmarks.benchmarks.</code><code class="descname">print_distribution_statistics</code><span class="sig-paren">(</span><em>original</em>, <em>models</em>, <em>steps</em>, <em>resolution</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/benchmarks/benchmarks.html#print_distribution_statistics"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.benchmarks.benchmarks.print_distribution_statistics" title="Permalink to this definition">¶</a></dt>
diff --git a/docs/build/html/pyFTS.common.html b/docs/build/html/pyFTS.common.html
index 9f29b92..175ff3b 100644
--- a/docs/build/html/pyFTS.common.html
+++ b/docs/build/html/pyFTS.common.html
@@ -1253,10 +1253,124 @@ bisect but with a simpler API and support for key functions.</p>
 </table>
 </dd></dl>
 
+<dl class="function">
+<dt id="pyFTS.common.Util.plot_compared_intervals_ahead">
+<code class="descclassname">pyFTS.common.Util.</code><code class="descname">plot_compared_intervals_ahead</code><span class="sig-paren">(</span><em>original, models, colors, distributions, time_from, time_to, intervals=True, save=False, file=None, tam=[20, 5], resolution=None, cmap='Blues', linewidth=1.5</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/Util.html#plot_compared_intervals_ahead"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.common.Util.plot_compared_intervals_ahead" title="Permalink to this definition">¶</a></dt>
+<dd><p>Plot the forecasts of several one step ahead models, by point or by interval</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>original</strong> – Original time series data (list)</li>
+<li><strong>models</strong> – List of models to compare</li>
+<li><strong>colors</strong> – List of models colors</li>
+<li><strong>distributions</strong> – True to plot a distribution</li>
+<li><strong>time_from</strong> – index of data poit to start the ahead forecasting</li>
+<li><strong>time_to</strong> – number of steps ahead to forecast</li>
+<li><strong>interpol</strong> – Fill space between distribution plots</li>
+<li><strong>save</strong> – Save the picture on file</li>
+<li><strong>file</strong> – Filename to save the picture</li>
+<li><strong>tam</strong> – Size of the picture</li>
+<li><strong>resolution</strong> – </li>
+<li><strong>cmap</strong> – Color map to be used on distribution plot</li>
+<li><strong>option</strong> – Distribution type to be passed for models</li>
+</ul>
+</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
+</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="function">
+<dt id="pyFTS.common.Util.plot_density_rectange">
+<code class="descclassname">pyFTS.common.Util.</code><code class="descname">plot_density_rectange</code><span class="sig-paren">(</span><em>ax</em>, <em>cmap</em>, <em>density</em>, <em>fig</em>, <em>resolution</em>, <em>time_from</em>, <em>time_to</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/Util.html#plot_density_rectange"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.common.Util.plot_density_rectange" title="Permalink to this definition">¶</a></dt>
+<dd><p>Auxiliar function to plot_compared_intervals_ahead</p>
+</dd></dl>
+
+<dl class="function">
+<dt id="pyFTS.common.Util.plot_distribution">
+<code class="descclassname">pyFTS.common.Util.</code><code class="descname">plot_distribution</code><span class="sig-paren">(</span><em>ax</em>, <em>cmap</em>, <em>probabilitydist</em>, <em>fig</em>, <em>time_from</em>, <em>reference_data=None</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/Util.html#plot_distribution"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.common.Util.plot_distribution" title="Permalink to this definition">¶</a></dt>
+<dd><p>Plot forecasted ProbabilityDistribution objects on a matplotlib axis</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>ax</strong> – matplotlib axis</li>
+<li><strong>cmap</strong> – matplotlib colormap name</li>
+<li><strong>probabilitydist</strong> – list of ProbabilityDistribution objects</li>
+<li><strong>fig</strong> – matplotlib figure</li>
+<li><strong>time_from</strong> – starting time (on x axis) to begin the plots</li>
+<li><strong>reference_data</strong> – </li>
+</ul>
+</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
+</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="function">
+<dt id="pyFTS.common.Util.plot_interval">
+<code class="descclassname">pyFTS.common.Util.</code><code class="descname">plot_interval</code><span class="sig-paren">(</span><em>axis</em>, <em>intervals</em>, <em>order</em>, <em>label</em>, <em>color='red'</em>, <em>typeonlegend=False</em>, <em>ls='-'</em>, <em>linewidth=1</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/Util.html#plot_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.common.Util.plot_interval" title="Permalink to this definition">¶</a></dt>
+<dd><p>Plot forecasted intervals on matplotlib</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>axis</strong> – matplotlib axis</li>
+<li><strong>intervals</strong> – list of forecasted intervals</li>
+<li><strong>order</strong> – order of the model that create the forecasts</li>
+<li><strong>label</strong> – figure label</li>
+<li><strong>color</strong> – matplotlib color name</li>
+<li><strong>typeonlegend</strong> – </li>
+<li><strong>ls</strong> – matplotlib line style</li>
+<li><strong>linewidth</strong> – matplotlib width</li>
+</ul>
+</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
+</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
+<dl class="function">
+<dt id="pyFTS.common.Util.plot_probability_distributions">
+<code class="descclassname">pyFTS.common.Util.</code><code class="descname">plot_probability_distributions</code><span class="sig-paren">(</span><em>pmfs, lcolors, tam=[15, 7]</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/Util.html#plot_probability_distributions"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.common.Util.plot_probability_distributions" title="Permalink to this definition">¶</a></dt>
+<dd></dd></dl>
+
 <dl class="function">
 <dt id="pyFTS.common.Util.plot_rules">
 <code class="descclassname">pyFTS.common.Util.</code><code class="descname">plot_rules</code><span class="sig-paren">(</span><em>model, size=[5, 5], axis=None, rules_by_axis=None, columns=1</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/common/Util.html#plot_rules"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.common.Util.plot_rules" title="Permalink to this definition">¶</a></dt>
-<dd></dd></dl>
+<dd><p>Plot the FLRG rules of a FTS model on a matplotlib axis</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>model</strong> – FTS model</li>
+<li><strong>size</strong> – figure size</li>
+<li><strong>axis</strong> – matplotlib axis</li>
+<li><strong>rules_by_axis</strong> – number of rules plotted by column</li>
+<li><strong>columns</strong> – number of columns</li>
+</ul>
+</td>
+</tr>
+<tr class="field-even field"><th class="field-name">Returns:</th><td class="field-body"><p class="first last"></p>
+</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
 
 <dl class="function">
 <dt id="pyFTS.common.Util.show_and_save_image">
diff --git a/docs/build/html/pyFTS.html b/docs/build/html/pyFTS.html
index 162aee5..b91ec3c 100644
--- a/docs/build/html/pyFTS.html
+++ b/docs/build/html/pyFTS.html
@@ -176,7 +176,7 @@
 <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>
+<li class="toctree-l2"><a class="reference internal" href="pyFTS.hyperparam.html#pyfts-hyperparam-gridsearch-module">pyFTS.hyperparam.GridSearch module</a></li>
 <li class="toctree-l2"><a class="reference internal" href="pyFTS.hyperparam.html#pyfts-hyperparam-evolutionary-module">pyFTS.hyperparam.Evolutionary module</a></li>
 </ul>
 </li>
diff --git a/docs/build/html/pyFTS.hyperparam.html b/docs/build/html/pyFTS.hyperparam.html
index 2867cbb..31ff724 100644
--- a/docs/build/html/pyFTS.hyperparam.html
+++ b/docs/build/html/pyFTS.hyperparam.html
@@ -66,7 +66,7 @@
 <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>
+<li><a class="reference internal" href="#pyfts-hyperparam-gridsearch-module">pyFTS.hyperparam.GridSearch module</a></li>
 <li><a class="reference internal" href="#pyfts-hyperparam-evolutionary-module">pyFTS.hyperparam.Evolutionary module</a></li>
 </ul>
 </li>
@@ -183,28 +183,8 @@ Value: the measure value</p>
 </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.cluster_method">
-<code class="descclassname">pyFTS.hyperparam.GridSearch.</code><code class="descname">cluster_method</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#cluster_method"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.hyperparam.GridSearch.cluster_method" title="Permalink to this definition">¶</a></dt>
-<dd></dd></dl>
-
-<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.process_jobs">
-<code class="descclassname">pyFTS.hyperparam.GridSearch.</code><code class="descname">process_jobs</code><span class="sig-paren">(</span><em>jobs</em>, <em>datasetname</em>, <em>conn</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/hyperparam/GridSearch.html#process_jobs"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.hyperparam.GridSearch.process_jobs" title="Permalink to this definition">¶</a></dt>
-<dd></dd></dl>
-
+<div class="section" id="pyfts-hyperparam-gridsearch-module">
+<h2>pyFTS.hyperparam.GridSearch module<a class="headerlink" href="#pyfts-hyperparam-gridsearch-module" title="Permalink to this headline">¶</a></h2>
 </div>
 <div class="section" id="pyfts-hyperparam-evolutionary-module">
 <h2>pyFTS.hyperparam.Evolutionary module<a class="headerlink" href="#pyfts-hyperparam-evolutionary-module" title="Permalink to this headline">¶</a></h2>
diff --git a/docs/build/html/pyFTS.models.ensemble.html b/docs/build/html/pyFTS.models.ensemble.html
index 9abd414..8f0ebac 100644
--- a/docs/build/html/pyFTS.models.ensemble.html
+++ b/docs/build/html/pyFTS.models.ensemble.html
@@ -319,7 +319,7 @@ XIII Brazilian Congress on Computational Intelligence, 2017. Rio de Janeiro, Bra
 <dl class="attribute">
 <dt id="pyFTS.models.ensemble.ensemble.EnsembleFTS.point_method">
 <code class="descname">point_method</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.models.ensemble.ensemble.EnsembleFTS.point_method" title="Permalink to this definition">¶</a></dt>
-<dd><p>The method used to mix the several model’s forecasts into a unique point forecast. Options: mean, median, quantile</p>
+<dd><p>The method used to mix the several model’s forecasts into a unique point forecast. Options: mean, median, quantile, exponential</p>
 </dd></dl>
 
 <dl class="method">
diff --git a/docs/build/html/pyFTS.models.html b/docs/build/html/pyFTS.models.html
index ec67bc3..c0df496 100644
--- a/docs/build/html/pyFTS.models.html
+++ b/docs/build/html/pyFTS.models.html
@@ -528,6 +528,22 @@ using Fuzzy Time Series. 2017 IEEE International Conference on Fuzzy Systems. DO
 <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_lower">
+<code class="descname">get_lower</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_lower"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFLRG.get_lower" title="Permalink to this definition">¶</a></dt>
+<dd><p>Returns the lower bound 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">lower bound value</td>
+</tr>
+</tbody>
+</table>
+</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>
@@ -544,6 +560,22 @@ using Fuzzy Time Series. 2017 IEEE International Conference on Fuzzy Systems. DO
 </table>
 </dd></dl>
 
+<dl class="method">
+<dt id="pyFTS.models.hofts.WeightedHighOrderFLRG.get_upper">
+<code class="descname">get_upper</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_upper"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.hofts.WeightedHighOrderFLRG.get_upper" title="Permalink to this definition">¶</a></dt>
+<dd><p>Returns the upper bound 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">upper bound 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>
@@ -628,7 +660,7 @@ In: Computational Intelligence (SSCI), 2016 IEEE Symposium Series on. IEEE, 2016
 <dl class="class">
 <dt id="pyFTS.models.ifts.IntervalFTS">
 <em class="property">class </em><code class="descclassname">pyFTS.models.ifts.</code><code class="descname">IntervalFTS</code><span class="sig-paren">(</span><em>**kwargs</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/ifts.html#IntervalFTS"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.ifts.IntervalFTS" 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>
+<dd><p>Bases: <a class="reference internal" href="#pyFTS.models.hofts.WeightedHighOrderFTS" title="pyFTS.models.hofts.WeightedHighOrderFTS"><code class="xref py py-class docutils literal notranslate"><span class="pre">pyFTS.models.hofts.WeightedHighOrderFTS</span></code></a></p>
 <p>High Order Interval Fuzzy Time Series</p>
 <dl class="method">
 <dt id="pyFTS.models.ifts.IntervalFTS.forecast_interval">
diff --git a/docs/build/html/pyFTS.models.incremental.html b/docs/build/html/pyFTS.models.incremental.html
index 442b491..b937e0c 100644
--- a/docs/build/html/pyFTS.models.incremental.html
+++ b/docs/build/html/pyFTS.models.incremental.html
@@ -265,6 +265,12 @@
 <dd><p>The FTS method specific parameters</p>
 </dd></dl>
 
+<dl class="attribute">
+<dt id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.num_models">
+<code class="descname">num_models</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.num_models" title="Permalink to this definition">¶</a></dt>
+<dd><p>The number of models to hold in the ensemble</p>
+</dd></dl>
+
 <dl class="attribute">
 <dt id="pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.partitioner_method">
 <code class="descname">partitioner_method</code><em class="property"> = None</em><a class="headerlink" href="#pyFTS.models.incremental.IncrementalEnsemble.IncrementalEnsembleFTS.partitioner_method" title="Permalink to this definition">¶</a></dt>
diff --git a/docs/build/html/pyFTS.models.multivariate.html b/docs/build/html/pyFTS.models.multivariate.html
index 58ebfdd..7e3e818 100644
--- a/docs/build/html/pyFTS.models.multivariate.html
+++ b/docs/build/html/pyFTS.models.multivariate.html
@@ -294,6 +294,22 @@ transformations and partitioners.</p>
 <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/flrg.html#FLRG.append_rhs"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.flrg.FLRG.append_rhs" title="Permalink to this definition">¶</a></dt>
 <dd></dd></dl>
 
+<dl class="method">
+<dt id="pyFTS.models.multivariate.flrg.FLRG.get_lower">
+<code class="descname">get_lower</code><span class="sig-paren">(</span><em>sets</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/flrg.html#FLRG.get_lower"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.flrg.FLRG.get_lower" title="Permalink to this definition">¶</a></dt>
+<dd><p>Returns the lower bound 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">lower bound value</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
 <dl class="method">
 <dt id="pyFTS.models.multivariate.flrg.FLRG.get_membership">
 <code class="descname">get_membership</code><span class="sig-paren">(</span><em>data</em>, <em>variables</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/flrg.html#FLRG.get_membership"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.flrg.FLRG.get_membership" title="Permalink to this definition">¶</a></dt>
@@ -315,6 +331,22 @@ transformations and partitioners.</p>
 </table>
 </dd></dl>
 
+<dl class="method">
+<dt id="pyFTS.models.multivariate.flrg.FLRG.get_upper">
+<code class="descname">get_upper</code><span class="sig-paren">(</span><em>sets</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/flrg.html#FLRG.get_upper"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.flrg.FLRG.get_upper" title="Permalink to this definition">¶</a></dt>
+<dd><p>Returns the upper bound 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">upper bound value</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
 <dl class="method">
 <dt id="pyFTS.models.multivariate.flrg.FLRG.set_lhs">
 <code class="descname">set_lhs</code><span class="sig-paren">(</span><em>var</em>, <em>fset</em><span class="sig-paren">)</span><a class="reference internal" href="_modules/pyFTS/models/multivariate/flrg.html#FLRG.set_lhs"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.flrg.FLRG.set_lhs" title="Permalink to this definition">¶</a></dt>
@@ -426,6 +458,27 @@ transformations and partitioners.</p>
 </table>
 </dd></dl>
 
+<dl class="method">
+<dt id="pyFTS.models.multivariate.mvfts.MVFTS.forecast_interval">
+<code class="descname">forecast_interval</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_interval"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.mvfts.MVFTS.forecast_interval" title="Permalink to this definition">¶</a></dt>
+<dd><p>Interval forecast one step 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>kwargs</strong> – model specific parameters</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 prediction intervals</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>
@@ -487,6 +540,22 @@ transformations and partitioners.</p>
 <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.wmvfts.WeightedFLRG.get_lower">
+<code class="descname">get_lower</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_lower"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_lower" title="Permalink to this definition">¶</a></dt>
+<dd><p>Returns the lower bound 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">lower bound value</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
 <dl class="method">
 <dt id="pyFTS.models.multivariate.wmvfts.WeightedFLRG.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/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>
@@ -503,6 +572,22 @@ transformations and partitioners.</p>
 </table>
 </dd></dl>
 
+<dl class="method">
+<dt id="pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_upper">
+<code class="descname">get_upper</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_upper"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyFTS.models.multivariate.wmvfts.WeightedFLRG.get_upper" title="Permalink to this definition">¶</a></dt>
+<dd><p>Returns the upper bound 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">upper bound value</td>
+</tr>
+</tbody>
+</table>
+</dd></dl>
+
 <dl class="method">
 <dt id="pyFTS.models.multivariate.wmvfts.WeightedFLRG.weights">
 <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>
diff --git a/docs/build/html/searchindex.js b/docs/build/html/searchindex.js
index 71738b6..dbc2952 100644
--- a/docs/build/html/searchindex.js
+++ b/docs/build/html/searchindex.js
@@ -1 +1 @@
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\ No newline at end of file
diff --git a/pyFTS/common/Util.py b/pyFTS/common/Util.py
index 12524d0..842764f 100644
--- a/pyFTS/common/Util.py
+++ b/pyFTS/common/Util.py
@@ -12,6 +12,8 @@ from pyFTS.probabilistic import ProbabilityDistribution
 from pyFTS.common import Transformations
 
 
+
+
 def plot_compared_intervals_ahead(original, models, colors, distributions, time_from, time_to, intervals = True,
                                save=False, file=None, tam=[20, 5], resolution=None,
                                cmap='Blues', linewidth=1.5):
@@ -124,6 +126,17 @@ def plot_probability_distributions(pmfs, lcolors, tam=[15, 7]):
     ax.legend(handles0, labels0)
 
 def plot_distribution(ax, cmap, probabilitydist, fig, time_from, reference_data=None):
+    '''
+    Plot forecasted ProbabilityDistribution objects on a matplotlib axis
+
+    :param ax: matplotlib axis
+    :param cmap: matplotlib colormap name
+    :param probabilitydist: list of ProbabilityDistribution objects
+    :param fig: matplotlib figure
+    :param time_from: starting time (on x axis) to begin the plots
+    :param reference_data:
+    :return:
+    '''
     from matplotlib.patches import Rectangle
     from matplotlib.collections import PatchCollection
     patches = []
@@ -149,6 +162,19 @@ def plot_distribution(ax, cmap, probabilitydist, fig, time_from, reference_data=
 
 
 def plot_interval(axis, intervals, order, label, color='red', typeonlegend=False, ls='-', linewidth=1):
+    '''
+    Plot forecasted intervals on matplotlib
+
+    :param axis: matplotlib axis
+    :param intervals: list of forecasted intervals
+    :param order: order of the model that create the forecasts
+    :param label: figure label
+    :param color: matplotlib color name
+    :param typeonlegend:
+    :param ls: matplotlib line style
+    :param linewidth: matplotlib width
+    :return:
+    '''
     lower = [kk[0] for kk in intervals]
     upper = [kk[1] for kk in intervals]
     mi = min(lower) * 0.95
@@ -163,6 +189,16 @@ def plot_interval(axis, intervals, order, label, color='red', typeonlegend=False
 
 
 def plot_rules(model, size=[5, 5], axis=None, rules_by_axis=None, columns=1):
+    '''
+    Plot the FLRG rules of a FTS model on a matplotlib axis
+
+    :param model: FTS model
+    :param size: figure size
+    :param axis: matplotlib axis
+    :param rules_by_axis: number of rules plotted by column
+    :param columns: number of columns
+    :return:
+    '''
     if axis is None and rules_by_axis is None:
         rows = 1
     elif axis is None and rules_by_axis is not None: