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  <h1>Source code for pyFTS.common.Transformations</h1><div class="highlight"><pre>
<span></span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd">Common data transformation used on pre and post processing of the FTS</span>
<span class="sd">&quot;&quot;&quot;</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">math</span>
<span class="kn">from</span> <span class="nn">pyFTS</span> <span class="k">import</span> <span class="o">*</span>


<div class="viewcode-block" id="Transformation"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Transformation">[docs]</a><span class="k">class</span> <span class="nc">Transformation</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Data transformation used on pre and post processing of the FTS</span>
<span class="sd">    &quot;&quot;&quot;</span>

    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">is_invertible</span> <span class="o">=</span> <span class="kc">True</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">minimal_length</span> <span class="o">=</span> <span class="mi">1</span>

<div class="viewcode-block" id="Transformation.apply"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Transformation.apply">[docs]</a>    <span class="k">def</span> <span class="nf">apply</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">param</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">        Apply the transformation on input data</span>

<span class="sd">        :param data: input data</span>
<span class="sd">        :param param:</span>
<span class="sd">        :param kwargs:</span>
<span class="sd">        :return: numpy array with transformed data</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="k">pass</span></div>

<div class="viewcode-block" id="Transformation.inverse"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Transformation.inverse">[docs]</a>    <span class="k">def</span> <span class="nf">inverse</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">param</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
        <span class="sd">&quot;&quot;&quot;</span>

<span class="sd">        :param data: transformed data</span>
<span class="sd">        :param param:</span>
<span class="sd">        :param kwargs:</span>
<span class="sd">        :return: numpy array with inverse transformed data</span>
<span class="sd">        &quot;&quot;&quot;</span>
        <span class="k">pass</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="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="vm">__class__</span><span class="o">.</span><span class="vm">__name__</span> <span class="o">+</span> <span class="s1">&#39;(&#39;</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">parameters</span><span class="p">)</span> <span class="o">+</span> <span class="s1">&#39;)&#39;</span></div>


<div class="viewcode-block" id="Differential"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Differential">[docs]</a><span class="k">class</span> <span class="nc">Differential</span><span class="p">(</span><span class="n">Transformation</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Differentiation data transform</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">lag</span><span class="p">):</span>
        <span class="nb">super</span><span class="p">(</span><span class="n">Differential</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="bp">self</span><span class="o">.</span><span class="n">lag</span> <span class="o">=</span> <span class="n">lag</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">minimal_length</span> <span class="o">=</span> <span class="mi">2</span>

    <span class="nd">@property</span>
    <span class="k">def</span> <span class="nf">parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">lag</span>

<div class="viewcode-block" id="Differential.apply"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Differential.apply">[docs]</a>    <span class="k">def</span> <span class="nf">apply</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">param</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
        <span class="k">if</span> <span class="n">param</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">lag</span> <span class="o">=</span> <span class="n">param</span>

        <span class="k">if</span> <span class="ow">not</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">np</span><span class="o">.</span><span class="n">generic</span><span class="p">)):</span>
            <span class="n">data</span> <span class="o">=</span> <span class="p">[</span><span class="n">data</span><span class="p">]</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="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">generic</span><span class="p">)):</span>
            <span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>

        <span class="n">n</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>
        <span class="n">diff</span> <span class="o">=</span> <span class="p">[</span><span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">-</span> <span class="n">data</span><span class="p">[</span><span class="n">t</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">lag</span><span class="p">]</span> <span class="k">for</span> <span class="n">t</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">lag</span><span class="p">,</span> <span class="n">n</span><span class="p">)]</span>
        <span class="k">for</span> <span class="n">t</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="bp">self</span><span class="o">.</span><span class="n">lag</span><span class="p">):</span> <span class="n">diff</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="mi">0</span><span class="p">)</span>
        <span class="k">return</span> <span class="n">diff</span></div>

<div class="viewcode-block" id="Differential.inverse"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Differential.inverse">[docs]</a>    <span class="k">def</span> <span class="nf">inverse</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">param</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</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="s2">&quot;type&quot;</span><span class="p">,</span><span class="s2">&quot;point&quot;</span><span class="p">)</span>
        <span class="n">steps_ahead</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;steps_ahead&quot;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</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="n">np</span><span class="o">.</span><span class="n">ndarray</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">generic</span><span class="p">)):</span>
            <span class="n">data</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">tolist</span><span class="p">()</span>

        <span class="k">if</span> <span class="ow">not</span> <span class="nb">isinstance</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="nb">list</span><span class="p">):</span>
            <span class="n">data</span> <span class="o">=</span> <span class="p">[</span><span class="n">data</span><span class="p">]</span>

        <span class="n">n</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>

<span class="c1">#        print(n)</span>
<span class="c1">#        print(len(param))</span>

        <span class="k">if</span> <span class="n">steps_ahead</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
            <span class="k">if</span> <span class="nb">type</span> <span class="o">==</span> <span class="s2">&quot;point&quot;</span><span class="p">:</span>
                <span class="n">inc</span> <span class="o">=</span> <span class="p">[</span><span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">+</span> <span class="n">param</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="k">for</span> <span class="n">t</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">n</span><span class="p">)]</span>
            <span class="k">elif</span> <span class="nb">type</span> <span class="o">==</span> <span class="s2">&quot;interval&quot;</span><span class="p">:</span>
                <span class="n">inc</span> <span class="o">=</span> <span class="p">[[</span><span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">param</span><span class="p">[</span><span class="n">t</span><span class="p">],</span> <span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">][</span><span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="n">param</span><span class="p">[</span><span class="n">t</span><span class="p">]]</span> <span class="k">for</span> <span class="n">t</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">n</span><span class="p">)]</span>
            <span class="k">elif</span> <span class="nb">type</span> <span class="o">==</span> <span class="s2">&quot;distribution&quot;</span><span class="p">:</span>
                <span class="k">for</span> <span class="n">t</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">n</span><span class="p">):</span>
                    <span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">]</span><span class="o">.</span><span class="n">differential_offset</span><span class="p">(</span><span class="n">param</span><span class="p">[</span><span class="n">t</span><span class="p">])</span>
                <span class="n">inc</span> <span class="o">=</span> <span class="n">data</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="k">if</span> <span class="nb">type</span> <span class="o">==</span> <span class="s2">&quot;point&quot;</span><span class="p">:</span>
                <span class="n">inc</span> <span class="o">=</span> <span class="p">[</span><span class="n">data</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">]]</span>
                <span class="k">for</span> <span class="n">t</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">1</span><span class="p">,</span> <span class="n">steps_ahead</span><span class="p">):</span>
                    <span class="n">inc</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">t</span><span class="p">]</span> <span class="o">+</span> <span class="n">inc</span><span class="p">[</span><span class="n">t</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
            <span class="k">elif</span> <span class="nb">type</span> <span class="o">==</span> <span class="s2">&quot;interval&quot;</span><span class="p">:</span>
                <span class="n">inc</span> <span class="o">=</span> <span class="p">[[</span><span class="n">data</span><span class="p">[</span><span class="mi">0</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">data</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="o">+</span> <span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">]]]</span>
                <span class="k">for</span> <span class="n">t</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">1</span><span class="p">,</span> <span class="n">steps_ahead</span><span class="p">):</span>
                    <span class="n">inc</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">t</span><span class="p">][</span><span class="mi">0</span><span class="p">]</span> <span class="o">+</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmean</span><span class="p">(</span><span class="n">inc</span><span class="p">[</span><span class="n">t</span><span class="o">-</span><span class="mi">1</span><span class="p">]),</span> <span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">][</span><span class="mi">1</span><span class="p">]</span> <span class="o">+</span> <span class="n">np</span><span class="o">.</span><span class="n">nanmean</span><span class="p">(</span><span class="n">inc</span><span class="p">[</span><span class="n">t</span><span class="o">-</span><span class="mi">1</span><span class="p">])])</span>
            <span class="k">elif</span> <span class="nb">type</span> <span class="o">==</span> <span class="s2">&quot;distribution&quot;</span><span class="p">:</span>
                <span class="n">data</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span><span class="o">.</span><span class="n">differential_offset</span><span class="p">(</span><span class="n">param</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>
                <span class="k">for</span> <span class="n">t</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">1</span><span class="p">,</span> <span class="n">steps_ahead</span><span class="p">):</span>
                    <span class="n">ex</span> <span class="o">=</span> <span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="o">-</span><span class="mi">1</span><span class="p">]</span><span class="o">.</span><span class="n">expected_value</span><span class="p">()</span>
                    <span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">]</span><span class="o">.</span><span class="n">differential_offset</span><span class="p">(</span><span class="n">ex</span><span class="p">)</span>
                <span class="n">inc</span> <span class="o">=</span> <span class="n">data</span>

        <span class="k">if</span> <span class="n">n</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
            <span class="k">return</span> <span class="n">inc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="k">return</span> <span class="n">inc</span></div></div>


<div class="viewcode-block" id="Scale"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Scale">[docs]</a><span class="k">class</span> <span class="nc">Scale</span><span class="p">(</span><span class="n">Transformation</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Scale data inside a interval [min, max]</span>

<span class="sd">    </span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="nb">min</span><span class="o">=</span><span class="mi">0</span><span class="p">,</span> <span class="nb">max</span><span class="o">=</span><span class="mi">1</span><span class="p">):</span>
        <span class="nb">super</span><span class="p">(</span><span class="n">Scale</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="bp">self</span><span class="o">.</span><span class="n">data_max</span> <span class="o">=</span> <span class="kc">None</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">data_min</span> <span class="o">=</span> <span class="kc">None</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">transf_max</span> <span class="o">=</span> <span class="nb">max</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">transf_min</span> <span class="o">=</span> <span class="nb">min</span>

    <span class="nd">@property</span>
    <span class="k">def</span> <span class="nf">parameters</span><span class="p">(</span><span class="bp">self</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">transf_max</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">transf_min</span><span class="p">]</span>

<div class="viewcode-block" id="Scale.apply"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Scale.apply">[docs]</a>    <span class="k">def</span> <span class="nf">apply</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">param</span><span class="o">=</span><span class="kc">None</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="bp">self</span><span class="o">.</span><span class="n">data_max</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">data_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">data</span><span class="p">)</span>
            <span class="bp">self</span><span class="o">.</span><span class="n">data_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">data</span><span class="p">)</span>
        <span class="n">data_range</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">data_max</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">data_min</span>
        <span class="n">transf_range</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">transf_max</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">transf_min</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="nb">list</span><span class="p">):</span>
            <span class="n">tmp</span> <span class="o">=</span> <span class="p">[(</span><span class="n">k</span> <span class="o">+</span> <span class="p">(</span><span class="o">-</span><span class="mi">1</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">data_min</span><span class="p">))</span> <span class="o">/</span> <span class="n">data_range</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">data</span><span class="p">]</span>
            <span class="n">tmp2</span> <span class="o">=</span> <span class="p">[</span> <span class="p">(</span><span class="n">k</span> <span class="o">*</span> <span class="n">transf_range</span><span class="p">)</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">transf_min</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">tmp</span><span class="p">]</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="n">tmp</span> <span class="o">=</span> <span class="p">(</span><span class="n">data</span> <span class="o">+</span> <span class="p">(</span><span class="o">-</span><span class="mi">1</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">data_min</span><span class="p">))</span> <span class="o">/</span> <span class="n">data_range</span>
            <span class="n">tmp2</span> <span class="o">=</span> <span class="p">(</span><span class="n">tmp</span> <span class="o">*</span> <span class="n">transf_range</span><span class="p">)</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">transf_min</span>

        <span class="k">return</span>  <span class="n">tmp2</span></div>

<div class="viewcode-block" id="Scale.inverse"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Scale.inverse">[docs]</a>    <span class="k">def</span> <span class="nf">inverse</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">param</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
        <span class="n">data_range</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">data_max</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">data_min</span>
        <span class="n">transf_range</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">transf_max</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">transf_min</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="nb">list</span><span class="p">):</span>
            <span class="n">tmp2</span> <span class="o">=</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">transf_min</span><span class="p">)</span> <span class="o">/</span> <span class="n">transf_range</span>   <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">data</span><span class="p">]</span>
            <span class="n">tmp</span> <span class="o">=</span> <span class="p">[(</span><span class="n">k</span> <span class="o">*</span> <span class="n">data_range</span><span class="p">)</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">data_min</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">tmp2</span><span class="p">]</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="n">tmp2</span> <span class="o">=</span> <span class="p">(</span><span class="n">data</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">transf_min</span><span class="p">)</span> <span class="o">/</span> <span class="n">transf_range</span>
            <span class="n">tmp</span> <span class="o">=</span> <span class="p">(</span><span class="n">tmp2</span> <span class="o">*</span> <span class="n">data_range</span><span class="p">)</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">data_min</span>
        <span class="k">return</span> <span class="n">tmp</span></div></div>


<div class="viewcode-block" id="AdaptiveExpectation"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.AdaptiveExpectation">[docs]</a><span class="k">class</span> <span class="nc">AdaptiveExpectation</span><span class="p">(</span><span class="n">Transformation</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Adaptive Expectation post processing</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">parameters</span><span class="p">):</span>
        <span class="nb">super</span><span class="p">(</span><span class="n">AdaptiveExpectation</span><span class="p">,</span> <span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="n">parameters</span><span class="p">)</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">h</span> <span class="o">=</span> <span class="n">parameters</span>

    <span class="nd">@property</span>
    <span class="k">def</span> <span class="nf">parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">parameters</span>

<div class="viewcode-block" id="AdaptiveExpectation.apply"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.AdaptiveExpectation.apply">[docs]</a>    <span class="k">def</span> <span class="nf">apply</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">param</span><span class="o">=</span><span class="kc">None</span><span class="p">,</span><span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
        <span class="k">return</span> <span class="n">data</span></div>

<div class="viewcode-block" id="AdaptiveExpectation.inverse"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.AdaptiveExpectation.inverse">[docs]</a>    <span class="k">def</span> <span class="nf">inverse</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">param</span><span class="p">,</span><span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
        <span class="n">n</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">data</span><span class="p">)</span>

        <span class="n">inc</span> <span class="o">=</span> <span class="p">[</span><span class="n">param</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">+</span> <span class="bp">self</span><span class="o">.</span><span class="n">h</span><span class="o">*</span><span class="p">(</span><span class="n">data</span><span class="p">[</span><span class="n">t</span><span class="p">]</span> <span class="o">-</span> <span class="n">param</span><span class="p">[</span><span class="n">t</span><span class="p">])</span> <span class="k">for</span> <span class="n">t</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">n</span><span class="p">)]</span>

        <span class="k">if</span> <span class="n">n</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
            <span class="k">return</span> <span class="n">inc</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="k">return</span> <span class="n">inc</span></div></div>


<div class="viewcode-block" id="BoxCox"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.BoxCox">[docs]</a><span class="k">class</span> <span class="nc">BoxCox</span><span class="p">(</span><span class="n">Transformation</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Box-Cox power transformation</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">plambda</span><span class="p">):</span>
        <span class="nb">super</span><span class="p">(</span><span class="n">BoxCox</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="bp">self</span><span class="o">.</span><span class="n">plambda</span> <span class="o">=</span> <span class="n">plambda</span>

    <span class="nd">@property</span>
    <span class="k">def</span> <span class="nf">parameters</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">plambda</span>

<div class="viewcode-block" id="BoxCox.apply"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.BoxCox.apply">[docs]</a>    <span class="k">def</span> <span class="nf">apply</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">param</span><span class="o">=</span><span class="kc">None</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="bp">self</span><span class="o">.</span><span class="n">plambda</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span>
            <span class="n">modified</span> <span class="o">=</span> <span class="p">[(</span><span class="n">dat</span> <span class="o">**</span> <span class="bp">self</span><span class="o">.</span><span class="n">plambda</span> <span class="o">-</span> <span class="mi">1</span><span class="p">)</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">plambda</span> <span class="k">for</span> <span class="n">dat</span> <span class="ow">in</span> <span class="n">data</span><span class="p">]</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="n">modified</span> <span class="o">=</span> <span class="p">[</span><span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">dat</span><span class="p">)</span> <span class="k">for</span> <span class="n">dat</span> <span class="ow">in</span> <span class="n">data</span><span class="p">]</span>
        <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">modified</span><span class="p">)</span></div>

<div class="viewcode-block" id="BoxCox.inverse"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.BoxCox.inverse">[docs]</a>    <span class="k">def</span> <span class="nf">inverse</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">param</span><span class="o">=</span><span class="kc">None</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="bp">self</span><span class="o">.</span><span class="n">plambda</span> <span class="o">!=</span> <span class="mi">0</span><span class="p">:</span>
            <span class="n">modified</span> <span class="o">=</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="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">dat</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">plambda</span> <span class="o">+</span> <span class="mi">1</span><span class="p">)</span> <span class="p">)</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">plambda</span> <span class="k">for</span> <span class="n">dat</span> <span class="ow">in</span> <span class="n">data</span><span class="p">]</span>
        <span class="k">else</span><span class="p">:</span>
            <span class="n">modified</span> <span class="o">=</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="n">dat</span><span class="p">)</span> <span class="k">for</span> <span class="n">dat</span> <span class="ow">in</span> <span class="n">data</span><span class="p">]</span>
        <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">modified</span><span class="p">)</span></div></div>


<div class="viewcode-block" id="Z"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.Z">[docs]</a><span class="k">def</span> <span class="nf">Z</span><span class="p">(</span><span class="n">original</span><span class="p">):</span>
    <span class="n">mu</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">mean</span><span class="p">(</span><span class="n">original</span><span class="p">)</span>
    <span class="n">sigma</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">std</span><span class="p">(</span><span class="n">original</span><span class="p">)</span>
    <span class="n">z</span> <span class="o">=</span> <span class="p">[(</span><span class="n">k</span> <span class="o">-</span> <span class="n">mu</span><span class="p">)</span><span class="o">/</span><span class="n">sigma</span> <span class="k">for</span> <span class="n">k</span> <span class="ow">in</span> <span class="n">original</span><span class="p">]</span>
    <span class="k">return</span> <span class="n">z</span></div>


<span class="c1"># retrieved from Sadaei and Lee (2014) - Multilayer Stock ForecastingModel Using Fuzzy Time Series</span>
<div class="viewcode-block" id="roi"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.roi">[docs]</a><span class="k">def</span> <span class="nf">roi</span><span class="p">(</span><span class="n">original</span><span class="p">):</span>
    <span class="n">n</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">original</span><span class="p">)</span>
    <span class="n">roi</span> <span class="o">=</span> <span class="p">[]</span>
    <span class="k">for</span> <span class="n">t</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">n</span><span class="o">-</span><span class="mi">1</span><span class="p">):</span>
        <span class="n">roi</span><span class="o">.</span><span class="n">append</span><span class="p">(</span> <span class="p">(</span><span class="n">original</span><span class="p">[</span><span class="n">t</span><span class="o">+</span><span class="mi">1</span><span class="p">]</span> <span class="o">-</span> <span class="n">original</span><span class="p">[</span><span class="n">t</span><span class="p">])</span><span class="o">/</span><span class="n">original</span><span class="p">[</span><span class="n">t</span><span class="p">]</span>  <span class="p">)</span>
    <span class="k">return</span> <span class="n">roi</span></div>

<div class="viewcode-block" id="smoothing"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.smoothing">[docs]</a><span class="k">def</span> <span class="nf">smoothing</span><span class="p">(</span><span class="n">original</span><span class="p">,</span> <span class="n">lags</span><span class="p">):</span>
    <span class="k">pass</span></div>

<div class="viewcode-block" id="aggregate"><a class="viewcode-back" href="../../../pyFTS.common.html#pyFTS.common.Transformations.aggregate">[docs]</a><span class="k">def</span> <span class="nf">aggregate</span><span class="p">(</span><span class="n">original</span><span class="p">,</span> <span class="n">operation</span><span class="p">):</span>
    <span class="k">pass</span></div>
</pre></div>

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