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<h1>Source code for quapy.data.reader</h1><div class="highlight"><pre>
<span></span><span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">scipy.sparse</span> <span class="kn">import</span> <span class="n">dok_matrix</span>
<span class="kn">from</span> <span class="nn">tqdm</span> <span class="kn">import</span> <span class="n">tqdm</span>
<div class="viewcode-block" id="from_text">
<a class="viewcode-back" href="../../../quapy.data.html#quapy.data.reader.from_text">[docs]</a>
<span class="k">def</span> <span class="nf">from_text</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s1">&#39;utf-8&#39;</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">class2int</span><span class="o">=</span><span class="kc">True</span><span class="p">):</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Reads a labelled colletion of documents.</span>
<span class="sd"> File fomart &lt;0 or 1&gt;\t&lt;document&gt;\n</span>
<span class="sd"> :param path: path to the labelled collection</span>
<span class="sd"> :param encoding: the text encoding used to open the file</span>
<span class="sd"> :param verbose: if &gt;0 (default) shows some progress information in standard output</span>
<span class="sd"> :return: a list of sentences, and a list of labels</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">all_sentences</span><span class="p">,</span> <span class="n">all_labels</span> <span class="o">=</span> <span class="p">[],</span> <span class="p">[]</span>
<span class="k">if</span> <span class="n">verbose</span><span class="o">&gt;</span><span class="mi">0</span><span class="p">:</span>
<span class="n">file</span> <span class="o">=</span> <span class="n">tqdm</span><span class="p">(</span><span class="nb">open</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="s1">&#39;rt&#39;</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="n">encoding</span><span class="p">)</span><span class="o">.</span><span class="n">readlines</span><span class="p">(),</span> <span class="sa">f</span><span class="s1">&#39;loading </span><span class="si">{</span><span class="n">path</span><span class="si">}</span><span class="s1">&#39;</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">file</span> <span class="o">=</span> <span class="nb">open</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="s1">&#39;rt&#39;</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="n">encoding</span><span class="p">)</span><span class="o">.</span><span class="n">readlines</span><span class="p">()</span>
<span class="k">for</span> <span class="n">line</span> <span class="ow">in</span> <span class="n">file</span><span class="p">:</span>
<span class="n">line</span> <span class="o">=</span> <span class="n">line</span><span class="o">.</span><span class="n">strip</span><span class="p">()</span>
<span class="k">if</span> <span class="n">line</span><span class="p">:</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">label</span><span class="p">,</span> <span class="n">sentence</span> <span class="o">=</span> <span class="n">line</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;</span><span class="se">\t</span><span class="s1">&#39;</span><span class="p">)</span>
<span class="n">sentence</span> <span class="o">=</span> <span class="n">sentence</span><span class="o">.</span><span class="n">strip</span><span class="p">()</span>
<span class="k">if</span> <span class="n">class2int</span><span class="p">:</span>
<span class="n">label</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">label</span><span class="p">)</span>
<span class="k">if</span> <span class="n">sentence</span><span class="p">:</span>
<span class="n">all_sentences</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">sentence</span><span class="p">)</span>
<span class="n">all_labels</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">label</span><span class="p">)</span>
<span class="k">except</span> <span class="ne">ValueError</span><span class="p">:</span>
<span class="nb">print</span><span class="p">(</span><span class="sa">f</span><span class="s1">&#39;format error in </span><span class="si">{</span><span class="n">line</span><span class="si">}</span><span class="s1">&#39;</span><span class="p">)</span>
<span class="k">return</span> <span class="n">all_sentences</span><span class="p">,</span> <span class="n">all_labels</span></div>
<div class="viewcode-block" id="from_sparse">
<a class="viewcode-back" href="../../../quapy.data.html#quapy.data.reader.from_sparse">[docs]</a>
<span class="k">def</span> <span class="nf">from_sparse</span><span class="p">(</span><span class="n">path</span><span class="p">):</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Reads a labelled collection of real-valued instances expressed in sparse format</span>
<span class="sd"> File format &lt;-1 or 0 or 1&gt;[\s col(int):val(float)]\n</span>
<span class="sd"> :param path: path to the labelled collection</span>
<span class="sd"> :return: a `csr_matrix` containing the instances (rows), and a ndarray containing the labels</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="k">def</span> <span class="nf">split_col_val</span><span class="p">(</span><span class="n">col_val</span><span class="p">):</span>
<span class="n">col</span><span class="p">,</span> <span class="n">val</span> <span class="o">=</span> <span class="n">col_val</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;:&#39;</span><span class="p">)</span>
<span class="n">col</span><span class="p">,</span> <span class="n">val</span> <span class="o">=</span> <span class="nb">int</span><span class="p">(</span><span class="n">col</span><span class="p">)</span> <span class="o">-</span> <span class="mi">1</span><span class="p">,</span> <span class="nb">float</span><span class="p">(</span><span class="n">val</span><span class="p">)</span>
<span class="k">return</span> <span class="n">col</span><span class="p">,</span> <span class="n">val</span>
<span class="n">all_documents</span><span class="p">,</span> <span class="n">all_labels</span> <span class="o">=</span> <span class="p">[],</span> <span class="p">[]</span>
<span class="n">max_col</span> <span class="o">=</span> <span class="mi">0</span>
<span class="k">for</span> <span class="n">line</span> <span class="ow">in</span> <span class="n">tqdm</span><span class="p">(</span><span class="nb">open</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="s1">&#39;rt&#39;</span><span class="p">)</span><span class="o">.</span><span class="n">readlines</span><span class="p">(),</span> <span class="sa">f</span><span class="s1">&#39;loading </span><span class="si">{</span><span class="n">path</span><span class="si">}</span><span class="s1">&#39;</span><span class="p">):</span>
<span class="n">parts</span> <span class="o">=</span> <span class="n">line</span><span class="o">.</span><span class="n">strip</span><span class="p">()</span><span class="o">.</span><span class="n">split</span><span class="p">()</span>
<span class="k">if</span> <span class="n">parts</span><span class="p">:</span>
<span class="n">all_labels</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">int</span><span class="p">(</span><span class="n">parts</span><span class="p">[</span><span class="mi">0</span><span class="p">]))</span>
<span class="n">cols</span><span class="p">,</span> <span class="n">vals</span> <span class="o">=</span> <span class="nb">zip</span><span class="p">(</span><span class="o">*</span><span class="p">[</span><span class="n">split_col_val</span><span class="p">(</span><span class="n">col_val</span><span class="p">)</span> <span class="k">for</span> <span class="n">col_val</span> <span class="ow">in</span> <span class="n">parts</span><span class="p">[</span><span class="mi">1</span><span class="p">:]])</span>
<span class="n">cols</span><span class="p">,</span> <span class="n">vals</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">cols</span><span class="p">),</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">vals</span><span class="p">)</span>
<span class="n">max_col</span> <span class="o">=</span> <span class="nb">max</span><span class="p">(</span><span class="n">max_col</span><span class="p">,</span> <span class="n">cols</span><span class="o">.</span><span class="n">max</span><span class="p">())</span>
<span class="n">all_documents</span><span class="o">.</span><span class="n">append</span><span class="p">((</span><span class="n">cols</span><span class="p">,</span> <span class="n">vals</span><span class="p">))</span>
<span class="n">n_docs</span> <span class="o">=</span> <span class="nb">len</span><span class="p">(</span><span class="n">all_labels</span><span class="p">)</span>
<span class="n">X</span> <span class="o">=</span> <span class="n">dok_matrix</span><span class="p">((</span><span class="n">n_docs</span><span class="p">,</span> <span class="n">max_col</span> <span class="o">+</span> <span class="mi">1</span><span class="p">),</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">float</span><span class="p">)</span>
<span class="k">for</span> <span class="n">i</span><span class="p">,</span> <span class="p">(</span><span class="n">cols</span><span class="p">,</span> <span class="n">vals</span><span class="p">)</span> <span class="ow">in</span> <span class="n">tqdm</span><span class="p">(</span><span class="nb">enumerate</span><span class="p">(</span><span class="n">all_documents</span><span class="p">),</span> <span class="n">total</span><span class="o">=</span><span class="nb">len</span><span class="p">(</span><span class="n">all_documents</span><span class="p">),</span>
<span class="n">desc</span><span class="o">=</span><span class="sa">f</span><span class="s1">&#39;\-- filling matrix of shape </span><span class="si">{</span><span class="n">X</span><span class="o">.</span><span class="n">shape</span><span class="si">}</span><span class="s1">&#39;</span><span class="p">):</span>
<span class="n">X</span><span class="p">[</span><span class="n">i</span><span class="p">,</span> <span class="n">cols</span><span class="p">]</span> <span class="o">=</span> <span class="n">vals</span>
<span class="n">X</span> <span class="o">=</span> <span class="n">X</span><span class="o">.</span><span class="n">tocsr</span><span class="p">()</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">all_labels</span><span class="p">)</span> <span class="o">+</span> <span class="mi">1</span>
<span class="k">return</span> <span class="n">X</span><span class="p">,</span> <span class="n">y</span></div>
<div class="viewcode-block" id="from_csv">
<a class="viewcode-back" href="../../../quapy.data.html#quapy.data.reader.from_csv">[docs]</a>
<span class="k">def</span> <span class="nf">from_csv</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="s1">&#39;utf-8&#39;</span><span class="p">):</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Reads a csv file in which columns are separated by &#39;,&#39;.</span>
<span class="sd"> File format &lt;label&gt;,&lt;feat1&gt;,&lt;feat2&gt;,...,&lt;featn&gt;\n</span>
<span class="sd"> :param path: path to the csv file</span>
<span class="sd"> :param encoding: the text encoding used to open the file</span>
<span class="sd"> :return: a np.ndarray for the labels and a ndarray (float) for the covariates</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">X</span><span class="p">,</span> <span class="n">y</span> <span class="o">=</span> <span class="p">[],</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">instance</span> <span class="ow">in</span> <span class="n">tqdm</span><span class="p">(</span><span class="nb">open</span><span class="p">(</span><span class="n">path</span><span class="p">,</span> <span class="s1">&#39;rt&#39;</span><span class="p">,</span> <span class="n">encoding</span><span class="o">=</span><span class="n">encoding</span><span class="p">)</span><span class="o">.</span><span class="n">readlines</span><span class="p">(),</span> <span class="n">desc</span><span class="o">=</span><span class="sa">f</span><span class="s1">&#39;reading </span><span class="si">{</span><span class="n">path</span><span class="si">}</span><span class="s1">&#39;</span><span class="p">):</span>
<span class="n">yi</span><span class="p">,</span> <span class="o">*</span><span class="n">xi</span> <span class="o">=</span> <span class="n">instance</span><span class="o">.</span><span class="n">strip</span><span class="p">()</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">&#39;,&#39;</span><span class="p">)</span>
<span class="n">X</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="nb">list</span><span class="p">(</span><span class="nb">map</span><span class="p">(</span><span class="nb">float</span><span class="p">,</span><span class="n">xi</span><span class="p">)))</span>
<span class="n">y</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">yi</span><span class="p">)</span>
<span class="n">X</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">X</span><span class="p">)</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">y</span><span class="p">)</span>
<span class="k">return</span> <span class="n">X</span><span class="p">,</span> <span class="n">y</span></div>
<div class="viewcode-block" id="reindex_labels">
<a class="viewcode-back" href="../../../quapy.data.html#quapy.data.reader.reindex_labels">[docs]</a>
<span class="k">def</span> <span class="nf">reindex_labels</span><span class="p">(</span><span class="n">y</span><span class="p">):</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Re-indexes a list of labels as a list of indexes, and returns the classnames corresponding to the indexes.</span>
<span class="sd"> E.g.:</span>
<span class="sd"> &gt;&gt;&gt; reindex_labels([&#39;B&#39;, &#39;B&#39;, &#39;A&#39;, &#39;C&#39;])</span>
<span class="sd"> &gt;&gt;&gt; (array([1, 1, 0, 2]), array([&#39;A&#39;, &#39;B&#39;, &#39;C&#39;], dtype=&#39;&lt;U1&#39;))</span>
<span class="sd"> :param y: the list or array of original labels</span>
<span class="sd"> :return: a ndarray (int) of class indexes, and a ndarray of classnames corresponding to the indexes.</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">y</span><span class="p">)</span>
<span class="n">classnames</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="nb">sorted</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">unique</span><span class="p">(</span><span class="n">y</span><span class="p">)))</span>
<span class="n">label2index</span> <span class="o">=</span> <span class="p">{</span><span class="n">label</span><span class="p">:</span> <span class="n">index</span> <span class="k">for</span> <span class="n">index</span><span class="p">,</span> <span class="n">label</span> <span class="ow">in</span> <span class="nb">enumerate</span><span class="p">(</span><span class="n">classnames</span><span class="p">)}</span>
<span class="n">indexed</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">empty</span><span class="p">(</span><span class="n">y</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">int</span><span class="p">)</span>
<span class="k">for</span> <span class="n">label</span> <span class="ow">in</span> <span class="n">classnames</span><span class="p">:</span>
<span class="n">indexed</span><span class="p">[</span><span class="n">y</span><span class="o">==</span><span class="n">label</span><span class="p">]</span> <span class="o">=</span> <span class="n">label2index</span><span class="p">[</span><span class="n">label</span><span class="p">]</span>
<span class="k">return</span> <span class="n">indexed</span><span class="p">,</span> <span class="n">classnames</span></div>
<div class="viewcode-block" id="binarize">
<a class="viewcode-back" href="../../../quapy.data.html#quapy.data.reader.binarize">[docs]</a>
<span class="k">def</span> <span class="nf">binarize</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">pos_class</span><span class="p">):</span>
<span class="w"> </span><span class="sd">&quot;&quot;&quot;</span>
<span class="sd"> Binarizes a categorical array-like collection of labels towards the positive class `pos_class`. E.g.,:</span>
<span class="sd"> &gt;&gt;&gt; binarize([1, 2, 3, 1, 1, 0], pos_class=2)</span>
<span class="sd"> &gt;&gt;&gt; array([0, 1, 0, 0, 0, 0])</span>
<span class="sd"> :param y: array-like of labels</span>
<span class="sd"> :param pos_class: integer, the positive class</span>
<span class="sd"> :return: a binary np.ndarray, in which values 1 corresponds to positions in whcih `y` had `pos_class` labels, and</span>
<span class="sd"> 0 otherwise</span>
<span class="sd"> &quot;&quot;&quot;</span>
<span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">asarray</span><span class="p">(</span><span class="n">y</span><span class="p">)</span>
<span class="n">ybin</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">zeros</span><span class="p">(</span><span class="n">y</span><span class="o">.</span><span class="n">shape</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="nb">int</span><span class="p">)</span>
<span class="n">ybin</span><span class="p">[</span><span class="n">y</span> <span class="o">==</span> <span class="n">pos_class</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1</span>
<span class="k">return</span> <span class="n">ybin</span></div>
</pre></div>
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