<!doctype html>
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta http-equiv="X-UA-Compatible" content="IE=Edge" />
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" /><script type="text/javascript">
var _gaq = _gaq || [];
_gaq.push(['_setAccount', 'UA-55120145-3']);
_gaq.push(['_trackPageview']);
(function() {
var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true;
ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js';
var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s);
})();
</script>
<title>pyFTS.partitioners.partitioner — pyFTS 1.4 documentation</title>
<link rel="stylesheet" href="../../../_static/bizstyle.css" type="text/css" />
<link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
<script type="text/javascript" src="../../../_static/documentation_options.js"></script>
<script type="text/javascript" src="../../../_static/jquery.js"></script>
<script type="text/javascript" src="../../../_static/underscore.js"></script>
<script type="text/javascript" src="../../../_static/doctools.js"></script>
<script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.1/MathJax.js?config=TeX-AMS-MML_HTMLorMML"></script>
<script type="text/javascript" src="../../../_static/bizstyle.js"></script>
<link rel="index" title="Index" href="../../../genindex.html" />
<link rel="search" title="Search" href="../../../search.html" />
<meta name="viewport" content="width=device-width,initial-scale=1.0">
<!--[if lt IE 9]>
<script type="text/javascript" src="_static/css3-mediaqueries.js"></script>
<![endif]-->
</head><body>
<div class="related" role="navigation" aria-label="related navigation">
<h3>Navigation</h3>
<ul>
<li class="right" style="margin-right: 10px">
<a href="../../../genindex.html" title="General Index"
accesskey="I">index</a></li>
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.4 documentation</a> »</li>
<li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> »</li>
</ul>
</div>
<div class="sphinxsidebar" role="navigation" aria-label="main navigation">
<div class="sphinxsidebarwrapper">
<p class="logo"><a href="../../../index.html">
<img class="logo" src="../../../_static/logo_heading2.png" alt="Logo"/>
</a></p>
<div id="searchbox" style="display: none" role="search">
<h3>Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../../../search.html" method="get">
<input type="text" name="q" />
<input type="submit" value="Go" />
<input type="hidden" name="check_keywords" value="yes" />
<input type="hidden" name="area" value="default" />
</form>
</div>
</div>
<script type="text/javascript">$('#searchbox').show(0);</script>
</div>
</div>
<div class="document">
<div class="documentwrapper">
<div class="bodywrapper">
<div class="body" role="main">
<h1>Source code for pyFTS.partitioners.partitioner</h1><div class="highlight"><pre>
<span></span><span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="k">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">Membership</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">scipy.spatial</span> <span class="k">import</span> <span class="n">KDTree</span>
<span class="kn">import</span> <span class="nn">matplotlib.pylab</span> <span class="k">as</span> <span class="nn">plt</span>
<div class="viewcode-block" id="Partitioner"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner">[docs]</a><span class="k">class</span> <span class="nc">Partitioner</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Universe of Discourse partitioner. Split data on several fuzzy sets</span>
<span class="sd"> """</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Universe of Discourse partitioner scheme. Split data on several fuzzy sets</span>
<span class="sd"> """</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'name'</span><span class="p">,</span><span class="s2">""</span><span class="p">)</span>
<span class="sd">"""partitioner name"""</span>
<span class="bp">self</span><span class="o">.</span><span class="n">partitions</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'npart'</span><span class="p">,</span> <span class="mi">10</span><span class="p">)</span>
<span class="sd">"""The number of universe of discourse partitions, i.e., the number of fuzzy sets that will be created"""</span>
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">membership_function</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'func'</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">)</span>
<span class="sd">"""Fuzzy membership function (pyFTS.common.Membership)"""</span>
<span class="bp">self</span><span class="o">.</span><span class="n">setnames</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'names'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="sd">"""list of partitions names. If None is given the partitions will be auto named with prefix"""</span>
<span class="bp">self</span><span class="o">.</span><span class="n">prefix</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'prefix'</span><span class="p">,</span> <span class="s1">'A'</span><span class="p">)</span>
<span class="sd">"""prefix of auto generated partition names"""</span>
<span class="bp">self</span><span class="o">.</span><span class="n">transformation</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'transformation'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="sd">"""data transformation to be applied on data"""</span>
<span class="bp">self</span><span class="o">.</span><span class="n">indexer</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'indexer'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">variable</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'variable'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="sd">"""In a multivariate context, the variable that contains this partitioner"""</span>
<span class="bp">self</span><span class="o">.</span><span class="n">type</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'type'</span><span class="p">,</span> <span class="s1">'common'</span><span class="p">)</span>
<span class="sd">"""The type of fuzzy sets that are generated by this partitioner"""</span>
<span class="bp">self</span><span class="o">.</span><span class="n">extractor</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">'extractor'</span><span class="p">,</span> <span class="k">lambda</span> <span class="n">x</span><span class="p">:</span> <span class="n">x</span><span class="p">)</span>
<span class="sd">"""Anonymous function used to extract a single primitive type from an object instance"""</span>
<span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span> <span class="o">=</span> <span class="kc">None</span>
<span class="sd">"""A ordered list of the fuzzy sets names, sorted by their middle point"""</span>
<span class="bp">self</span><span class="o">.</span><span class="n">kdtree</span> <span class="o">=</span> <span class="kc">None</span>
<span class="sd">"""A spatial index to help in fuzzyfication"""</span>
<span class="k">if</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'preprocess'</span><span class="p">,</span><span class="kc">True</span><span class="p">):</span>
<span class="n">data</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'data'</span><span class="p">,[</span><span class="kc">None</span><span class="p">])</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">ndata</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_data</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">ndata</span> <span class="o">=</span> <span class="n">data</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">transformation</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">ndata</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">transformation</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">ndata</span> <span class="o">=</span> <span class="n">data</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">ndata</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">indexer</span><span class="o">.</span><span class="n">get_data</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
<span class="n">_min</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmin</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
<span class="k">if</span> <span class="n">_min</span> <span class="o">==</span> <span class="o">-</span><span class="n">np</span><span class="o">.</span><span class="n">inf</span><span class="p">:</span>
<span class="n">ndata</span><span class="p">[</span><span class="n">ndata</span> <span class="o">==</span> <span class="o">-</span><span class="n">np</span><span class="o">.</span><span class="n">inf</span><span class="p">]</span> <span class="o">=</span> <span class="mi">0</span>
<span class="n">_min</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmin</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">min</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">_min</span> <span class="o">*</span> <span class="mf">1.1</span> <span class="k">if</span> <span class="n">_min</span> <span class="o"><</span> <span class="mi">0</span> <span class="k">else</span> <span class="n">_min</span> <span class="o">*</span> <span class="mf">0.9</span><span class="p">)</span>
<span class="n">_max</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmax</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">max</span> <span class="o">=</span> <span class="nb">float</span><span class="p">(</span><span class="n">_max</span> <span class="o">*</span> <span class="mf">1.1</span> <span class="k">if</span> <span class="n">_max</span> <span class="o">></span> <span class="mi">0</span> <span class="k">else</span> <span class="n">_max</span> <span class="o">*</span> <span class="mf">0.9</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">build</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span> <span class="ow">is</span> <span class="kc">None</span> <span class="ow">and</span> <span class="bp">self</span><span class="o">.</span><span class="n">setnames</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">setnames</span><span class="p">[:</span><span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)]</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span> <span class="o">=</span> <span class="n">FuzzySet</span><span class="o">.</span><span class="n">set_ordered</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
<span class="k">del</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
<div class="viewcode-block" id="Partitioner.build"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner.build">[docs]</a> <span class="k">def</span> <span class="nf">build</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Perform the partitioning of the Universe of Discourse</span>
<span class="sd"> :param data: training data</span>
<span class="sd"> :return: </span>
<span class="sd"> """</span>
<span class="k">pass</span></div>
<div class="viewcode-block" id="Partitioner.get_name"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner.get_name">[docs]</a> <span class="k">def</span> <span class="nf">get_name</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">counter</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Find the name of the fuzzy set given its counter id.</span>
<span class="sd"> :param counter: The number of the fuzzy set</span>
<span class="sd"> :return: String</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">prefix</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">counter</span><span class="p">)</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">setnames</span> <span class="ow">is</span> <span class="kc">None</span> <span class="k">else</span> <span class="bp">self</span><span class="o">.</span><span class="n">setnames</span><span class="p">[</span><span class="n">counter</span><span class="p">]</span></div>
<div class="viewcode-block" id="Partitioner.lower_set"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner.lower_set">[docs]</a> <span class="k">def</span> <span class="nf">lower_set</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Return the fuzzy set on lower bound of the universe of discourse.</span>
<span class="sd"> :return: Fuzzy Set</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span></div>
<div class="viewcode-block" id="Partitioner.upper_set"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner.upper_set">[docs]</a> <span class="k">def</span> <span class="nf">upper_set</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Return the fuzzy set on upper bound of the universe of discourse.</span>
<span class="sd"> :return: Fuzzy Set</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="o">-</span><span class="mi">1</span><span class="p">]]</span></div>
<div class="viewcode-block" id="Partitioner.build_index"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner.build_index">[docs]</a> <span class="k">def</span> <span class="nf">build_index</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="n">points</span> <span class="o">=</span> <span class="p">[]</span>
<span class="c1">#self.index = {}</span>
<span class="k">for</span> <span class="n">ct</span><span class="p">,</span> <span class="n">key</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">):</span>
<span class="n">fset</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span>
<span class="n">points</span><span class="o">.</span><span class="n">append</span><span class="p">([</span><span class="n">fset</span><span class="o">.</span><span class="n">lower</span><span class="p">,</span> <span class="n">fset</span><span class="o">.</span><span class="n">centroid</span><span class="p">,</span> <span class="n">fset</span><span class="o">.</span><span class="n">upper</span><span class="p">])</span>
<span class="c1">#self.index[ct] = fset.name</span>
<span class="kn">import</span> <span class="nn">sys</span>
<span class="n">sys</span><span class="o">.</span><span class="n">setrecursionlimit</span><span class="p">(</span><span class="mi">100000</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">kdtree</span> <span class="o">=</span> <span class="n">KDTree</span><span class="p">(</span><span class="n">points</span><span class="p">)</span>
<span class="n">sys</span><span class="o">.</span><span class="n">setrecursionlimit</span><span class="p">(</span><span class="mi">1000</span><span class="p">)</span></div>
<div class="viewcode-block" id="Partitioner.fuzzyfy"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner.fuzzyfy">[docs]</a> <span class="k">def</span> <span class="nf">fuzzyfy</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Fuzzyfy the input data according to this partitioner fuzzy sets.</span>
<span class="sd"> :param data: input value to be fuzzyfied</span>
<span class="sd"> :keyword alpha_cut: the minimal membership value to be considered on fuzzyfication (only for mode='sets')</span>
<span class="sd"> :keyword method: the fuzzyfication method (fuzzy: all fuzzy memberships, maximum: only the maximum membership)</span>
<span class="sd"> :keyword mode: the fuzzyfication mode (sets: return the fuzzy sets names, vector: return a vector with the membership</span>
<span class="sd"> values for all fuzzy sets, both: return a list with tuples (fuzzy set, membership value) )</span>
<span class="sd"> :returns a list with the fuzzyfied values, depending on the mode</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="p">(</span><span class="nb">list</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">)):</span>
<span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">inst</span> <span class="ow">in</span> <span class="n">data</span><span class="p">:</span>
<span class="n">mv</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">fuzzyfy</span><span class="p">(</span><span class="n">inst</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="n">ret</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">mv</span><span class="p">)</span>
<span class="k">return</span> <span class="n">ret</span>
<span class="n">alpha_cut</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'alpha_cut'</span><span class="p">,</span> <span class="mf">0.</span><span class="p">)</span>
<span class="n">mode</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">'mode'</span><span class="p">,</span> <span class="s1">'sets'</span><span class="p">)</span>
<span class="n">method</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'method'</span><span class="p">,</span> <span class="s1">'fuzzy'</span><span class="p">)</span>
<span class="n">nearest</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">search</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="nb">type</span><span class="o">=</span><span class="s1">'index'</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">zeros</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">partitions</span><span class="p">)</span>
<span class="k">for</span> <span class="n">ix</span> <span class="ow">in</span> <span class="n">nearest</span><span class="p">:</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
<span class="n">mv</span><span class="p">[</span><span class="n">ix</span><span class="p">]</span> <span class="o">=</span> <span class="n">tmp</span> <span class="k">if</span> <span class="n">tmp</span> <span class="o">>=</span> <span class="n">alpha_cut</span> <span class="k">else</span> <span class="mf">0.</span>
<span class="n">ix</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">mv</span> <span class="o">></span> <span class="mf">0.</span><span class="p">))</span>
<span class="k">if</span> <span class="n">ix</span><span class="o">.</span><span class="n">size</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
<span class="n">mv</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">check_bounds</span><span class="p">(</span><span class="n">data</span><span class="p">)]</span> <span class="o">=</span> <span class="mf">1.</span>
<span class="k">if</span> <span class="n">method</span> <span class="o">==</span> <span class="s1">'fuzzy'</span> <span class="ow">and</span> <span class="n">mode</span> <span class="o">==</span> <span class="s1">'vector'</span><span class="p">:</span>
<span class="k">return</span> <span class="n">mv</span>
<span class="k">elif</span> <span class="n">method</span> <span class="o">==</span> <span class="s1">'fuzzy'</span> <span class="ow">and</span> <span class="n">mode</span> <span class="o">==</span> <span class="s1">'sets'</span><span class="p">:</span>
<span class="n">ix</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">mv</span> <span class="o">></span> <span class="mf">0.</span><span class="p">))</span>
<span class="n">sets</span> <span class="o">=</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">i</span><span class="p">]</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">ix</span><span class="p">]</span>
<span class="k">return</span> <span class="n">sets</span>
<span class="k">elif</span> <span class="n">method</span> <span class="o">==</span> <span class="s1">'maximum'</span> <span class="ow">and</span> <span class="n">mode</span> <span class="o">==</span> <span class="s1">'sets'</span><span class="p">:</span>
<span class="n">mx</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">mv</span><span class="p">)</span>
<span class="n">ix</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">mv</span> <span class="o">==</span> <span class="n">mx</span><span class="p">))</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">ix</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span>
<span class="k">elif</span> <span class="n">mode</span> <span class="o">==</span> <span class="s1">'both'</span><span class="p">:</span>
<span class="n">ix</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ravel</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">argwhere</span><span class="p">(</span><span class="n">mv</span> <span class="o">></span> <span class="mf">0.</span><span class="p">))</span>
<span class="n">sets</span> <span class="o">=</span> <span class="p">[(</span><span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="n">mv</span><span class="p">[</span><span class="n">i</span><span class="p">])</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">ix</span><span class="p">]</span>
<span class="k">return</span> <span class="n">sets</span></div>
<div class="viewcode-block" id="Partitioner.check_bounds"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner.check_bounds">[docs]</a> <span class="k">def</span> <span class="nf">check_bounds</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">):</span>
<span class="sd">'''</span>
<span class="sd"> Check if the input data is outside the known Universe of Discourse and, if it is, round it to the closest</span>
<span class="sd"> fuzzy set.</span>
<span class="sd"> :param data: input data to be verified</span>
<span class="sd"> :return: the index of the closest fuzzy set when data is outside de universe of discourse or None if</span>
<span class="sd"> the data is inside the UoD.</span>
<span class="sd"> '''</span>
<span class="k">if</span> <span class="n">data</span> <span class="o"><</span> <span class="bp">self</span><span class="o">.</span><span class="n">min</span><span class="p">:</span>
<span class="k">return</span> <span class="mi">0</span>
<span class="k">elif</span> <span class="n">data</span> <span class="o">></span> <span class="bp">self</span><span class="o">.</span><span class="n">max</span><span class="p">:</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitions</span><span class="o">-</span><span class="mi">1</span></div>
<div class="viewcode-block" id="Partitioner.search"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner.search">[docs]</a> <span class="k">def</span> <span class="nf">search</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">'''</span>
<span class="sd"> Perform a search for the nearest fuzzy sets of the point 'data'. This function were designed to work with several</span>
<span class="sd"> overlapped fuzzy sets.</span>
<span class="sd"> :param data: the value to search for the nearest fuzzy sets</span>
<span class="sd"> :param type: the return type: 'index' for the fuzzy set indexes or 'name' for fuzzy set names.</span>
<span class="sd"> :param results: the number of nearest fuzzy sets to return</span>
<span class="sd"> :return: a list with the nearest fuzzy sets</span>
<span class="sd"> '''</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">kdtree</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">build_index</span><span class="p">()</span>
<span class="nb">type</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'type'</span><span class="p">,</span><span class="s1">'index'</span><span class="p">)</span>
<span class="n">results</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">'results'</span><span class="p">,</span> <span class="mi">3</span><span class="p">)</span>
<span class="n">_</span><span class="p">,</span> <span class="n">ix</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">kdtree</span><span class="o">.</span><span class="n">query</span><span class="p">([</span><span class="n">data</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">data</span><span class="p">],</span> <span class="n">results</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">type</span> <span class="o">==</span> <span class="s1">'name'</span><span class="p">:</span>
<span class="k">return</span> <span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">k</span><span class="p">]</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">ix</span><span class="p">)]</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">ix</span><span class="p">)</span></div>
<div class="viewcode-block" id="Partitioner.plot"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner.plot">[docs]</a> <span class="k">def</span> <span class="nf">plot</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ax</span><span class="p">,</span> <span class="n">rounding</span><span class="o">=</span><span class="mi">0</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Plot the partitioning using the Matplotlib axis ax</span>
<span class="sd"> :param ax: Matplotlib axis</span>
<span class="sd"> """</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_title</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_ylim</span><span class="p">([</span><span class="mi">0</span><span class="p">,</span> <span class="mf">1.1</span><span class="p">])</span>
<span class="n">ax</span><span class="o">.</span><span class="n">set_xlim</span><span class="p">([</span><span class="bp">self</span><span class="o">.</span><span class="n">min</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">max</span><span class="p">])</span>
<span class="n">ticks</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">x</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
<span class="n">s</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span>
<span class="k">if</span> <span class="n">s</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="s1">'common'</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">plot_set</span><span class="p">(</span><span class="n">ax</span><span class="p">,</span> <span class="n">s</span><span class="p">)</span>
<span class="k">elif</span> <span class="n">s</span><span class="o">.</span><span class="n">type</span> <span class="o">==</span> <span class="s1">'composite'</span><span class="p">:</span>
<span class="k">for</span> <span class="n">ss</span> <span class="ow">in</span> <span class="n">s</span><span class="o">.</span><span class="n">sets</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">plot_set</span><span class="p">(</span><span class="n">ax</span><span class="p">,</span> <span class="n">ss</span><span class="p">)</span>
<span class="n">ticks</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="nb">round</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">centroid</span><span class="p">,</span><span class="n">rounding</span><span class="p">))</span><span class="o">+</span><span class="s1">'</span><span class="se">\n</span><span class="s1">'</span><span class="o">+</span><span class="n">s</span><span class="o">.</span><span class="n">name</span><span class="p">)</span>
<span class="n">x</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">centroid</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">xaxis</span><span class="o">.</span><span class="n">set_ticklabels</span><span class="p">(</span><span class="n">ticks</span><span class="p">)</span>
<span class="n">ax</span><span class="o">.</span><span class="n">xaxis</span><span class="o">.</span><span class="n">set_ticks</span><span class="p">(</span><span class="n">x</span><span class="p">)</span></div>
<div class="viewcode-block" id="Partitioner.plot_set"><a class="viewcode-back" href="../../../pyFTS.partitioners.html#pyFTS.partitioners.partitioner.Partitioner.plot_set">[docs]</a> <span class="k">def</span> <span class="nf">plot_set</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">ax</span><span class="p">,</span> <span class="n">s</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Plot an isolate fuzzy set on Matplotlib axis</span>
<span class="sd"> :param ax: Matplotlib axis</span>
<span class="sd"> :param s: Fuzzy Set</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="n">s</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trimf</span><span class="p">:</span>
<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="n">s</span><span class="o">.</span><span class="n">parameters</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">s</span><span class="o">.</span><span class="n">parameters</span><span class="p">[</span><span class="mi">1</span><span class="p">],</span> <span class="n">s</span><span class="o">.</span><span class="n">parameters</span><span class="p">[</span><span class="mi">2</span><span class="p">]],</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="n">s</span><span class="o">.</span><span class="n">alpha</span><span class="p">,</span> <span class="mi">0</span><span class="p">])</span>
<span class="k">elif</span> <span class="n">s</span><span class="o">.</span><span class="n">mf</span> <span class="ow">in</span> <span class="p">(</span><span class="n">Membership</span><span class="o">.</span><span class="n">gaussmf</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">bellmf</span><span class="p">,</span> <span class="n">Membership</span><span class="o">.</span><span class="n">sigmf</span><span class="p">):</span>
<span class="n">tmpx</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">lower</span><span class="p">,</span> <span class="n">s</span><span class="o">.</span><span class="n">upper</span><span class="p">,</span> <span class="mi">100</span><span class="p">)</span>
<span class="n">tmpy</span> <span class="o">=</span> <span class="p">[</span><span class="n">s</span><span class="o">.</span><span class="n">membership</span><span class="p">(</span><span class="n">kk</span><span class="p">)</span> <span class="k">for</span> <span class="n">kk</span> <span class="ow">in</span> <span class="n">tmpx</span><span class="p">]</span>
<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">tmpx</span><span class="p">,</span> <span class="n">tmpy</span><span class="p">)</span>
<span class="k">elif</span> <span class="n">s</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">trapmf</span><span class="p">:</span>
<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">s</span><span class="o">.</span><span class="n">parameters</span><span class="p">,</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="n">s</span><span class="o">.</span><span class="n">alpha</span><span class="p">,</span> <span class="n">s</span><span class="o">.</span><span class="n">alpha</span><span class="p">,</span> <span class="mi">0</span><span class="p">])</span>
<span class="k">elif</span> <span class="n">s</span><span class="o">.</span><span class="n">mf</span> <span class="o">==</span> <span class="n">Membership</span><span class="o">.</span><span class="n">singleton</span><span class="p">:</span>
<span class="n">ax</span><span class="o">.</span><span class="n">plot</span><span class="p">([</span><span class="n">s</span><span class="o">.</span><span class="n">parameters</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span><span class="n">s</span><span class="o">.</span><span class="n">parameters</span><span class="p">[</span><span class="mi">0</span><span class="p">]],</span> <span class="p">[</span><span class="mi">0</span><span class="p">,</span> <span class="n">s</span><span class="o">.</span><span class="n">alpha</span><span class="p">])</span></div>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Return a string representation of the partitioner, the list of fuzzy sets and their parameters</span>
<span class="sd"> :return:</span>
<span class="sd"> """</span>
<span class="n">tmp</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">+</span> <span class="s2">":</span><span class="se">\n</span><span class="s2">"</span>
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="o">.</span><span class="n">keys</span><span class="p">():</span>
<span class="n">tmp</span> <span class="o">+=</span> <span class="nb">str</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">])</span><span class="o">+</span> <span class="s2">"</span><span class="se">\n</span><span class="s2">"</span>
<span class="k">return</span> <span class="n">tmp</span>
<span class="k">def</span> <span class="nf">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Return the number of partitions</span>
<span class="sd"> :return: number of partitions</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitions</span>
<span class="k">def</span> <span class="nf">__getitem__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">item</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Return a fuzzy set by its order or its name.</span>
<span class="sd"> :param item: If item is an integer then it represents the fuzzy set index (order), if it was a string then</span>
<span class="sd"> it represents the fuzzy set name.</span>
<span class="sd"> :return: the fuzzy set</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">item</span><span class="p">,</span> <span class="p">(</span><span class="nb">int</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">int</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">int8</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">int16</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">int32</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">int64</span><span class="p">)):</span>
<span class="k">if</span> <span class="n">item</span> <span class="o"><</span> <span class="mi">0</span> <span class="ow">or</span> <span class="n">item</span> <span class="o">>=</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitions</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"The fuzzy set index must be between 0 and </span><span class="si">{}</span><span class="s2">."</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">partitions</span><span class="p">))</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">[</span><span class="n">item</span><span class="p">]]</span>
<span class="k">elif</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">item</span><span class="p">,</span> <span class="nb">str</span><span class="p">):</span>
<span class="k">if</span> <span class="n">item</span> <span class="ow">not</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"The fuzzy set with name </span><span class="si">{}</span><span class="s2"> does not exist."</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">item</span><span class="p">))</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">item</span><span class="p">]</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"The parameter 'item' must be an integer or a string and the value informed was </span><span class="si">{}</span><span class="s2"> of type </span><span class="si">{}</span><span class="s2">!"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">item</span><span class="p">,</span> <span class="nb">type</span><span class="p">(</span><span class="n">item</span><span class="p">)))</span>
<span class="k">def</span> <span class="nf">__iter__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Iterate over the fuzzy sets, ordered by its midpoints.</span>
<span class="sd"> :return: An iterator over the fuzzy sets.</span>
<span class="sd"> """</span>
<span class="k">for</span> <span class="n">key</span> <span class="ow">in</span> <span class="bp">self</span><span class="o">.</span><span class="n">ordered_sets</span><span class="p">:</span>
<span class="k">yield</span> <span class="bp">self</span><span class="o">.</span><span class="n">sets</span><span class="p">[</span><span class="n">key</span><span class="p">]</span></div>
</pre></div>
</div>
</div>
</div>
<div class="clearer"></div>
</div>
<div class="related" role="navigation" aria-label="related navigation">
<h3>Navigation</h3>
<ul>
<li class="right" style="margin-right: 10px">
<a href="../../../genindex.html" title="General Index"
>index</a></li>
<li class="right" >
<a href="../../../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li class="nav-item nav-item-0"><a href="../../../index.html">pyFTS 1.4 documentation</a> »</li>
<li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> »</li>
</ul>
</div>
<div class="footer" role="contentinfo">
© Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
Created using <a href="http://sphinx-doc.org/">Sphinx</a> 1.7.2.
</div>
</body>
</html>