<!doctype html>

<html>
  <head>
    <meta charset="utf-8" />
    <meta name="viewport" content="width=device-width, initial-scale=1.0"><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.distributed.dispy &#8212; pyFTS 1.6 documentation</title>
    <link rel="stylesheet" href="../../../_static/bizstyle.css" type="text/css" />
    <link rel="stylesheet" href="../../../_static/pygments.css" type="text/css" />
    
    <script id="documentation_options" data-url_root="../../../" src="../../../_static/documentation_options.js"></script>
    <script src="../../../_static/jquery.js"></script>
    <script src="../../../_static/underscore.js"></script>
    <script src="../../../_static/doctools.js"></script>
    <script src="../../../_static/language_data.js"></script>
    <script 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 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 1.6 documentation</a> &#187;</li>
          <li class="nav-item nav-item-1"><a href="../../index.html" accesskey="U">Module code</a> &#187;</li>
        <li class="nav-item nav-item-this"><a href="">pyFTS.distributed.dispy</a></li> 
      </ul>
    </div>  

    <div class="document">
      <div class="documentwrapper">
        <div class="bodywrapper">
          <div class="body" role="main">
            
  <h1>Source code for pyFTS.distributed.dispy</h1><div class="highlight"><pre>
<span></span><span class="kn">import</span> <span class="nn">dispy</span> <span class="k">as</span> <span class="nn">dispy</span><span class="o">,</span> <span class="nn">dispy.httpd</span><span class="o">,</span> <span class="nn">logging</span>
<span class="kn">from</span> <span class="nn">pyFTS.common</span> <span class="kn">import</span> <span class="n">Util</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>


<div class="viewcode-block" id="start_dispy_cluster"><a class="viewcode-back" href="../../../pyFTS.distributed.html#pyFTS.distributed.dispy.start_dispy_cluster">[docs]</a><span class="k">def</span> <span class="nf">start_dispy_cluster</span><span class="p">(</span><span class="n">method</span><span class="p">,</span> <span class="n">nodes</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Start a new Dispy cluster on &#39;nodes&#39; to execute the method &#39;method&#39;</span>

<span class="sd">    :param method: function to be executed on each cluster node</span>
<span class="sd">    :param nodes: list of node names or IP&#39;s.</span>
<span class="sd">    :return: the dispy cluster instance and the http_server for monitoring</span>
<span class="sd">    &quot;&quot;&quot;</span>

    <span class="n">cluster</span> <span class="o">=</span> <span class="n">dispy</span><span class="o">.</span><span class="n">JobCluster</span><span class="p">(</span><span class="n">method</span><span class="p">,</span> <span class="n">nodes</span><span class="o">=</span><span class="n">nodes</span><span class="p">,</span> <span class="n">loglevel</span><span class="o">=</span><span class="n">logging</span><span class="o">.</span><span class="n">DEBUG</span><span class="p">,</span> <span class="n">ping_interval</span><span class="o">=</span><span class="mi">1000</span><span class="p">)</span>

    <span class="n">http_server</span> <span class="o">=</span> <span class="n">dispy</span><span class="o">.</span><span class="n">httpd</span><span class="o">.</span><span class="n">DispyHTTPServer</span><span class="p">(</span><span class="n">cluster</span><span class="p">)</span>

    <span class="k">return</span> <span class="n">cluster</span><span class="p">,</span> <span class="n">http_server</span></div>


<div class="viewcode-block" id="stop_dispy_cluster"><a class="viewcode-back" href="../../../pyFTS.distributed.html#pyFTS.distributed.dispy.stop_dispy_cluster">[docs]</a><span class="k">def</span> <span class="nf">stop_dispy_cluster</span><span class="p">(</span><span class="n">cluster</span><span class="p">,</span> <span class="n">http_server</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Stop a dispy cluster and http_server</span>

<span class="sd">    :param cluster:</span>
<span class="sd">    :param http_server:</span>
<span class="sd">    :return:</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="c1">#cluster.wait()  # wait for all jobs to finish</span>

    <span class="n">cluster</span><span class="o">.</span><span class="n">print_status</span><span class="p">()</span>

    <span class="n">http_server</span><span class="o">.</span><span class="n">shutdown</span><span class="p">()</span>  <span class="c1"># this waits until browser gets all updates</span>
    <span class="n">cluster</span><span class="o">.</span><span class="n">close</span><span class="p">()</span></div>


<div class="viewcode-block" id="get_number_of_cpus"><a class="viewcode-back" href="../../../pyFTS.distributed.html#pyFTS.distributed.dispy.get_number_of_cpus">[docs]</a><span class="k">def</span> <span class="nf">get_number_of_cpus</span><span class="p">(</span><span class="n">cluster</span><span class="p">):</span>
    <span class="n">cpus</span> <span class="o">=</span> <span class="mi">0</span>
    <span class="k">for</span> <span class="n">dispy_node</span> <span class="ow">in</span> <span class="n">cluster</span><span class="o">.</span><span class="n">status</span><span class="p">()</span><span class="o">.</span><span class="n">nodes</span><span class="p">:</span>
        <span class="n">cpus</span> <span class="o">+=</span> <span class="n">dispy_node</span><span class="o">.</span><span class="n">cpus</span>

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


<div class="viewcode-block" id="simple_model_train"><a class="viewcode-back" href="../../../pyFTS.distributed.html#pyFTS.distributed.dispy.simple_model_train">[docs]</a><span class="k">def</span> <span class="nf">simple_model_train</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">parameters</span><span class="p">):</span>
    <span class="kn">import</span> <span class="nn">time</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Cluster function that receives a FTS instance &#39;model&#39; and train using the &#39;data&#39; and &#39;parameters&#39;</span>

<span class="sd">    :param model: a FTS instance</span>
<span class="sd">    :param data: training dataset</span>
<span class="sd">    :param parameters: parameters for the training process</span>
<span class="sd">    :return: the trained model</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">_start</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
    <span class="n">model</span><span class="o">.</span><span class="n">train</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">parameters</span><span class="p">)</span>
    <span class="n">_end</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
    <span class="n">model</span><span class="o">.</span><span class="vm">__dict__</span><span class="p">[</span><span class="s1">&#39;training_time&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="n">_end</span> <span class="o">-</span> <span class="n">_start</span>
    <span class="k">return</span> <span class="n">model</span></div>


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

    <span class="n">batch_save</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;batch_save&#39;</span><span class="p">,</span> <span class="kc">False</span><span class="p">)</span>  <span class="c1"># save model between batches</span>

    <span class="n">batch_save_interval</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;batch_save_interval&#39;</span><span class="p">,</span> <span class="mi">1</span><span class="p">)</span>

    <span class="n">file_path</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="s1">&#39;file_path&#39;</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>

    <span class="n">cluster</span><span class="p">,</span> <span class="n">http_server</span> <span class="o">=</span> <span class="n">start_dispy_cluster</span><span class="p">(</span><span class="n">train_method</span><span class="p">,</span> <span class="n">nodes</span><span class="p">)</span>

    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;[{0: %H:%M:%S}] Distrituted Train Started with </span><span class="si">{1}</span><span class="s2"> CPU&#39;s&quot;</span>
          <span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">(),</span> <span class="n">get_number_of_cpus</span><span class="p">(</span><span class="n">cluster</span><span class="p">)))</span>

    <span class="n">jobs</span> <span class="o">=</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">batch_size</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">n</span> <span class="o">/</span> <span class="n">num_batches</span><span class="p">)</span>
    <span class="n">bcount</span> <span class="o">=</span> <span class="mi">1</span>
    <span class="k">for</span> <span class="n">ct</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">):</span>
        <span class="k">if</span> <span class="n">model</span><span class="o">.</span><span class="n">is_multivariate</span><span class="p">:</span>
            <span class="n">ndata</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">ct</span> <span class="o">-</span> <span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">:</span><span class="n">ct</span> <span class="o">+</span> <span class="n">batch_size</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="p">[</span><span class="n">ct</span> <span class="o">-</span> <span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">:</span> <span class="n">ct</span> <span class="o">+</span> <span class="n">batch_size</span><span class="p">]</span>

        <span class="n">tmp_model</span> <span class="o">=</span> <span class="n">fts_method</span><span class="p">()</span>

        <span class="n">tmp_model</span><span class="o">.</span><span class="n">clone_parameters</span><span class="p">(</span><span class="n">model</span><span class="p">)</span>

        <span class="n">job</span> <span class="o">=</span> <span class="n">cluster</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">tmp_model</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="n">train_parameters</span><span class="p">)</span>
        <span class="n">job</span><span class="o">.</span><span class="n">id</span> <span class="o">=</span> <span class="n">bcount</span>  <span class="c1"># associate an ID to identify jobs (if needed later)</span>
        <span class="n">jobs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">job</span><span class="p">)</span>

        <span class="n">bcount</span> <span class="o">+=</span> <span class="mi">1</span>

    <span class="k">for</span> <span class="n">job</span> <span class="ow">in</span> <span class="n">jobs</span><span class="p">:</span>
        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;[{0: %H:%M:%S}] Processing batch &quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">())</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">job</span><span class="o">.</span><span class="n">id</span><span class="p">))</span>
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">job</span><span class="p">()</span>
        <span class="k">if</span> <span class="n">job</span><span class="o">.</span><span class="n">status</span> <span class="o">==</span> <span class="n">dispy</span><span class="o">.</span><span class="n">DispyJob</span><span class="o">.</span><span class="n">Finished</span> <span class="ow">and</span> <span class="n">tmp</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
            <span class="n">model</span><span class="o">.</span><span class="n">merge</span><span class="p">(</span><span class="n">tmp</span><span class="p">)</span>
            <span class="k">if</span> <span class="s1">&#39;training_time&#39;</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">model</span><span class="o">.</span><span class="vm">__dict__</span><span class="p">:</span>
                <span class="n">model</span><span class="o">.</span><span class="vm">__dict__</span><span class="p">[</span><span class="s1">&#39;training_time&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
            <span class="n">model</span><span class="o">.</span><span class="vm">__dict__</span><span class="p">[</span><span class="s1">&#39;training_time&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="o">.</span><span class="vm">__dict__</span><span class="p">[</span><span class="s1">&#39;training_time&#39;</span><span class="p">])</span>

            <span class="k">if</span> <span class="n">batch_save</span> <span class="ow">and</span> <span class="p">(</span><span class="n">job</span><span class="o">.</span><span class="n">id</span> <span class="o">%</span> <span class="n">batch_save_interval</span><span class="p">)</span> <span class="o">==</span> <span class="mi">0</span><span class="p">:</span>
                <span class="n">Util</span><span class="o">.</span><span class="n">persist_obj</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">file_path</span><span class="p">)</span>

        <span class="k">else</span><span class="p">:</span>
            <span class="nb">print</span><span class="p">(</span><span class="n">job</span><span class="o">.</span><span class="n">exception</span><span class="p">)</span>
            <span class="nb">print</span><span class="p">(</span><span class="n">job</span><span class="o">.</span><span class="n">stdout</span><span class="p">)</span>

        <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;[{0: %H:%M:%S}] Finished batch &quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">())</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="n">job</span><span class="o">.</span><span class="n">id</span><span class="p">))</span>

    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;[{0: %H:%M:%S}] Distrituted Train Finished&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">datetime</span><span class="o">.</span><span class="n">datetime</span><span class="o">.</span><span class="n">now</span><span class="p">()))</span>

    <span class="n">stop_dispy_cluster</span><span class="p">(</span><span class="n">cluster</span><span class="p">,</span> <span class="n">http_server</span><span class="p">)</span>

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


<div class="viewcode-block" id="simple_model_predict"><a class="viewcode-back" href="../../../pyFTS.distributed.html#pyFTS.distributed.dispy.simple_model_predict">[docs]</a><span class="k">def</span> <span class="nf">simple_model_predict</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">parameters</span><span class="p">):</span>
    <span class="kn">import</span> <span class="nn">time</span>
    <span class="n">_start</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
    <span class="n">forecasts</span> <span class="o">=</span> <span class="n">model</span><span class="o">.</span><span class="n">predict</span><span class="p">(</span><span class="n">data</span><span class="p">,</span> <span class="o">**</span><span class="n">parameters</span><span class="p">)</span>
    <span class="n">_stop</span> <span class="o">=</span> <span class="n">time</span><span class="o">.</span><span class="n">time</span><span class="p">()</span>
    <span class="k">return</span> <span class="n">forecasts</span><span class="p">,</span> <span class="n">_stop</span> <span class="o">-</span> <span class="n">_start</span></div>


<div class="viewcode-block" id="distributed_predict"><a class="viewcode-back" href="../../../pyFTS.distributed.html#pyFTS.distributed.dispy.distributed_predict">[docs]</a><span class="k">def</span> <span class="nf">distributed_predict</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">parameters</span><span class="p">,</span> <span class="n">nodes</span><span class="p">,</span> <span class="n">data</span><span class="p">,</span> <span class="n">num_batches</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
    <span class="kn">import</span> <span class="nn">dispy</span><span class="o">,</span> <span class="nn">dispy.httpd</span>

    <span class="n">cluster</span><span class="p">,</span> <span class="n">http_server</span> <span class="o">=</span> <span class="n">start_dispy_cluster</span><span class="p">(</span><span class="n">simple_model_predict</span><span class="p">,</span> <span class="n">nodes</span><span class="p">)</span>

    <span class="n">jobs</span> <span class="o">=</span> <span class="p">[]</span>
    <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">batch_size</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">n</span> <span class="o">/</span> <span class="n">num_batches</span><span class="p">)</span>
    <span class="n">bcount</span> <span class="o">=</span> <span class="mi">1</span>
    <span class="k">for</span> <span class="n">ct</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">,</span> <span class="n">n</span><span class="p">,</span> <span class="n">batch_size</span><span class="p">):</span>
        <span class="k">if</span> <span class="n">model</span><span class="o">.</span><span class="n">is_multivariate</span><span class="p">:</span>
            <span class="n">ndata</span> <span class="o">=</span> <span class="n">data</span><span class="o">.</span><span class="n">iloc</span><span class="p">[</span><span class="n">ct</span> <span class="o">-</span> <span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">:</span><span class="n">ct</span> <span class="o">+</span> <span class="n">batch_size</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="p">[</span><span class="n">ct</span> <span class="o">-</span> <span class="n">model</span><span class="o">.</span><span class="n">order</span><span class="p">:</span> <span class="n">ct</span> <span class="o">+</span> <span class="n">batch_size</span><span class="p">]</span>

        <span class="n">job</span> <span class="o">=</span> <span class="n">cluster</span><span class="o">.</span><span class="n">submit</span><span class="p">(</span><span class="n">model</span><span class="p">,</span> <span class="n">ndata</span><span class="p">,</span> <span class="n">parameters</span><span class="p">)</span>
        <span class="n">job</span><span class="o">.</span><span class="n">id</span> <span class="o">=</span> <span class="n">bcount</span>  <span class="c1"># associate an ID to identify jobs (if needed later)</span>
        <span class="n">jobs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">job</span><span class="p">)</span>

        <span class="n">bcount</span> <span class="o">+=</span> <span class="mi">1</span>

    <span class="n">ret</span> <span class="o">=</span> <span class="p">[]</span>

    <span class="k">for</span> <span class="n">job</span> <span class="ow">in</span> <span class="n">jobs</span><span class="p">:</span>
        <span class="n">tmp</span> <span class="o">=</span> <span class="n">job</span><span class="p">()</span>
        <span class="k">if</span> <span class="n">job</span><span class="o">.</span><span class="n">status</span> <span class="o">==</span> <span class="n">dispy</span><span class="o">.</span><span class="n">DispyJob</span><span class="o">.</span><span class="n">Finished</span> <span class="ow">and</span> <span class="n">tmp</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">:</span>
            <span class="k">if</span> <span class="n">job</span><span class="o">.</span><span class="n">id</span> <span class="o">&lt;</span> <span class="n">batch_size</span><span class="p">:</span>
                <span class="n">ret</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="mi">0</span><span class="p">][:</span><span class="o">-</span><span class="mi">1</span><span class="p">])</span>
            <span class="k">else</span><span class="p">:</span>
                <span class="n">ret</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span>

            <span class="k">if</span> <span class="s1">&#39;forecasting_time&#39;</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">model</span><span class="o">.</span><span class="vm">__dict__</span><span class="p">:</span>
                <span class="n">model</span><span class="o">.</span><span class="vm">__dict__</span><span class="p">[</span><span class="s1">&#39;forecasting_time&#39;</span><span class="p">]</span> <span class="o">=</span> <span class="p">[]</span>
            <span class="n">model</span><span class="o">.</span><span class="vm">__dict__</span><span class="p">[</span><span class="s1">&#39;forecasting_time&#39;</span><span class="p">]</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">tmp</span><span class="p">[</span><span class="mi">1</span><span class="p">])</span>

        <span class="k">else</span><span class="p">:</span>
            <span class="nb">print</span><span class="p">(</span><span class="n">job</span><span class="o">.</span><span class="n">exception</span><span class="p">)</span>
            <span class="nb">print</span><span class="p">(</span><span class="n">job</span><span class="o">.</span><span class="n">stdout</span><span class="p">)</span>

    <span class="n">stop_dispy_cluster</span><span class="p">(</span><span class="n">cluster</span><span class="p">,</span> <span class="n">http_server</span><span class="p">)</span>

    <span class="k">return</span> <span class="n">ret</span></div>
</pre></div>

            <div class="clearer"></div>
          </div>
        </div>
      </div>
      <div class="sphinxsidebar" role="navigation" aria-label="main navigation">
        <div class="sphinxsidebarwrapper">
<div id="searchbox" style="display: none" role="search">
  <h3 id="searchlabel">Quick search</h3>
    <div class="searchformwrapper">
    <form class="search" action="../../../search.html" method="get">
      <input type="text" name="q" aria-labelledby="searchlabel" />
      <input type="submit" value="Go" />
    </form>
    </div>
</div>
<script>$('#searchbox').show(0);</script>
        </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 1.6 documentation</a> &#187;</li>
          <li class="nav-item nav-item-1"><a href="../../index.html" >Module code</a> &#187;</li>
        <li class="nav-item nav-item-this"><a href="">pyFTS.distributed.dispy</a></li> 
      </ul>
    </div>
    <div class="footer" role="contentinfo">
        &#169; Copyright 2018, Machine Intelligence and Data Science Laboratory - UFMG - Brazil.
      Created using <a href="https://www.sphinx-doc.org/">Sphinx</a> 3.1.2.
    </div>
  </body>
</html>