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<h1>Source code for pyFTS.models.ifts</h1><div class="highlight"><pre>
<span></span><span class="ch">#!/usr/bin/python</span>
<span class="c1"># -*- coding: utf8 -*-</span>
<span class="sd">"""</span>
<span class="sd">High Order Interval Fuzzy Time Series</span>
<span class="sd">SILVA, Petrônio CL; SADAEI, Hossein Javedani; GUIMARÃES, Frederico Gadelha. Interval Forecasting with Fuzzy Time Series.</span>
<span class="sd">In: Computational Intelligence (SSCI), 2016 IEEE Symposium Series on. IEEE, 2016. p. 1-8.</span>
<span class="sd">"""</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">FuzzySet</span><span class="p">,</span> <span class="n">FLR</span><span class="p">,</span> <span class="n">fts</span><span class="p">,</span> <span class="n">tree</span>
<span class="kn">from</span> <span class="nn">pyFTS.models</span> <span class="kn">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>
<span class="sd">"""</span>
<span class="sd"> High Order Interval Fuzzy Time Series</span>
<span class="sd"> """</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">IntervalFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">"IFTS"</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Interval FTS"</span>
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">"Silva, P.; Guimarães, F.; Sadaei, H. (2016)"</span>
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">has_point_forecasting</span> <span class="o">=</span> <span class="kc">False</span>
<span class="bp">self</span><span class="o">.</span><span class="n">has_interval_forecasting</span> <span class="o">=</span> <span class="kc">True</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">min_order</span> <span class="o">=</span> <span class="mi">1</span>
<div class="viewcode-block" id="IntervalFTS.get_upper"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ifts.IntervalFTS.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">flrg</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">nan</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">></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_upper</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">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">upper</span>
<span class="k">return</span> <span class="n">ret</span></div>
<div class="viewcode-block" id="IntervalFTS.get_lower"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ifts.IntervalFTS.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">flrg</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">nan</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">></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">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">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>
<span class="n">mb</span> <span class="o">=</span> <span class="p">[</span><span class="n">fuzzySets</span><span class="p">[</span><span class="n">k</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">k</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="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">))]</span>
<span class="k">return</span> <span class="n">mb</span></div>
<div class="viewcode-block" id="IntervalFTS.forecast_interval"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ifts.IntervalFTS.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">ndata</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">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
<span class="k">if</span> <span class="n">l</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="k">return</span> <span class="n">ndata</span>
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="n">l</span><span class="o">+</span><span class="mi">1</span><span class="p">):</span>
<span class="n">sample</span> <span class="o">=</span> <span class="n">ndata</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
<span class="n">flrgs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrg</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
<span class="n">up</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">lo</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">affected_flrgs_memberships</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">flrg</span> <span class="ow">in</span> <span class="n">flrgs</span><span class="p">:</span>
<span class="k">if</span> <span class="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">></span> <span class="mi">0</span><span class="p">:</span>
<span class="n">mv</span> <span class="o">=</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_membership</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
<span class="n">up</span><span class="o">.</span><span class="n">append</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">get_upper</span><span class="p">(</span><span class="n">flrg</span><span class="p">))</span>
<span class="n">lo</span><span class="o">.</span><span class="n">append</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">get_lower</span><span class="p">(</span><span class="n">flrg</span><span class="p">))</span>
<span class="n">affected_flrgs_memberships</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="c1"># gerar o intervalo</span>
<span class="n">norm</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">affected_flrgs_memberships</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">nansum</span><span class="p">(</span><span class="n">lo</span><span class="p">)</span> <span class="o">/</span> <span class="n">norm</span>
<span class="n">up_</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">up</span><span class="p">)</span> <span class="o">/</span> <span class="n">norm</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="k">return</span> <span class="n">ret</span></div>
<div class="viewcode-block" id="IntervalFTS.forecast_ahead_interval"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ifts.IntervalFTS.forecast_ahead_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead_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="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="n">start</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'start_at'</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
<span class="n">ret</span> <span class="o">=</span> <span class="p">[[</span><span class="n">x</span><span class="p">,</span> <span class="n">x</span><span class="p">]</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">data</span><span class="p">[</span><span class="n">start</span><span class="p">:</span><span class="n">start</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="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="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">+</span> <span class="n">steps</span><span class="p">):</span>
<span class="n">interval_lower</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">clip_uod</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">forecast_interval</span><span class="p">([</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">ret</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="mi">0</span><span class="p">])</span>
<span class="n">interval_upper</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">clip_uod</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">forecast_interval</span><span class="p">([</span><span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">ret</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="mi">0</span><span class="p">])</span>
<span class="n">interval</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">nanmin</span><span class="p">(</span><span class="n">interval_lower</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmax</span><span class="p">(</span><span class="n">interval_upper</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">interval</span><span class="p">)</span>
<span class="k">return</span> <span class="n">ret</span><span class="p">[</span><span class="o">-</span><span class="n">steps</span><span class="p">:]</span></div></div>
<div class="viewcode-block" id="WeightedIntervalFTS"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ifts.WeightedIntervalFTS">[docs]</a><span class="k">class</span> <span class="nc">WeightedIntervalFTS</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">"""</span>
<span class="sd"> Weighted High Order Interval Fuzzy Time Series</span>
<span class="sd"> """</span>
<span class="k">def</span> <span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="nb">super</span><span class="p">(</span><span class="n">WeightedIntervalFTS</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="o">**</span><span class="n">kwargs</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">shortname</span> <span class="o">=</span> <span class="s2">"WIFTS"</span>
<span class="bp">self</span><span class="o">.</span><span class="n">name</span> <span class="o">=</span> <span class="s2">"Weighted Interval FTS"</span>
<span class="bp">self</span><span class="o">.</span><span class="n">detail</span> <span class="o">=</span> <span class="s2">"Silva, P.; Guimarães, F.; Sadaei, H. (2016)"</span>
<span class="bp">self</span><span class="o">.</span><span class="n">flrgs</span> <span class="o">=</span> <span class="p">{}</span>
<span class="bp">self</span><span class="o">.</span><span class="n">has_point_forecasting</span> <span class="o">=</span> <span class="kc">False</span>
<span class="bp">self</span><span class="o">.</span><span class="n">has_interval_forecasting</span> <span class="o">=</span> <span class="kc">True</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">min_order</span> <span class="o">=</span> <span class="mi">1</span>
<div class="viewcode-block" id="WeightedIntervalFTS.get_upper"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ifts.WeightedIntervalFTS.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">flrg</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">nan</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">></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_upper</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">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">upper</span>
<span class="k">return</span> <span class="n">ret</span></div>
<div class="viewcode-block" id="WeightedIntervalFTS.get_lower"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ifts.WeightedIntervalFTS.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">flrg</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">nan</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">flrg</span><span class="o">.</span><span class="n">LHS</span><span class="p">)</span> <span class="o">></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">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">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="WeightedIntervalFTS.get_sequence_membership"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ifts.WeightedIntervalFTS.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>
<span class="n">mb</span> <span class="o">=</span> <span class="p">[</span><span class="n">fuzzySets</span><span class="p">[</span><span class="n">k</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">k</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="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">))]</span>
<span class="k">return</span> <span class="n">mb</span></div>
<div class="viewcode-block" id="WeightedIntervalFTS.forecast_interval"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ifts.WeightedIntervalFTS.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">ndata</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">l</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">ndata</span><span class="p">)</span>
<span class="k">if</span> <span class="n">l</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="k">return</span> <span class="n">ndata</span>
<span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">,</span> <span class="n">l</span><span class="o">+</span><span class="mi">1</span><span class="p">):</span>
<span class="n">sample</span> <span class="o">=</span> <span class="n">ndata</span><span class="p">[</span><span class="n">k</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">max_lag</span><span class="p">:</span> <span class="n">k</span><span class="p">]</span>
<span class="n">flrgs</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">generate_lhs_flrg</span><span class="p">(</span><span class="n">sample</span><span class="p">)</span>
<span class="n">up</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">lo</span> <span class="o">=</span> <span class="p">[]</span>
<span class="n">affected_flrgs_memberships</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">flrg</span> <span class="ow">in</span> <span class="n">flrgs</span><span class="p">:</span>
<span class="k">if</span> <span class="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">></span> <span class="mi">0</span><span class="p">:</span>
<span class="n">mv</span> <span class="o">=</span> <span class="n">flrg</span><span class="o">.</span><span class="n">get_membership</span><span class="p">(</span><span class="n">sample</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">partitioner</span><span class="o">.</span><span class="n">sets</span><span class="p">)</span>
<span class="n">up</span><span class="o">.</span><span class="n">append</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">get_upper</span><span class="p">(</span><span class="n">flrg</span><span class="p">))</span>
<span class="n">lo</span><span class="o">.</span><span class="n">append</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">get_lower</span><span class="p">(</span><span class="n">flrg</span><span class="p">))</span>
<span class="n">affected_flrgs_memberships</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="c1"># gerar o intervalo</span>
<span class="n">norm</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">affected_flrgs_memberships</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">nansum</span><span class="p">(</span><span class="n">lo</span><span class="p">)</span> <span class="o">/</span> <span class="n">norm</span>
<span class="n">up_</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">up</span><span class="p">)</span> <span class="o">/</span> <span class="n">norm</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="k">return</span> <span class="n">ret</span></div>
<div class="viewcode-block" id="WeightedIntervalFTS.forecast_ahead_interval"><a class="viewcode-back" href="../../../pyFTS.models.html#pyFTS.models.ifts.WeightedIntervalFTS.forecast_ahead_interval">[docs]</a> <span class="k">def</span> <span class="nf">forecast_ahead_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="n">steps</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="n">start</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">'start_at'</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span>
<span class="n">ret</span> <span class="o">=</span> <span class="p">[[</span><span class="n">x</span><span class="p">,</span> <span class="n">x</span><span class="p">]</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">data</span><span class="p">[</span><span class="n">start</span><span class="p">:</span><span class="n">start</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="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="bp">self</span><span class="o">.</span><span class="n">max_lag</span> <span class="o">+</span> <span class="n">steps</span><span class="p">):</span>
<span class="n">interval_lower</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">clip_uod</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">forecast_interval</span><span class="p">([</span><span class="n">x</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">ret</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="mi">0</span><span class="p">])</span>
<span class="n">interval_upper</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">clip_uod</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">forecast_interval</span><span class="p">([</span><span class="n">x</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">ret</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="mi">0</span><span class="p">])</span>
<span class="n">interval</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">nanmin</span><span class="p">(</span><span class="n">interval_lower</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmax</span><span class="p">(</span><span class="n">interval_upper</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">interval</span><span class="p">)</span>
<span class="k">return</span> <span class="n">ret</span><span class="p">[</span><span class="o">-</span><span class="n">steps</span><span class="p">:]</span></div></div>
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