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  <h1>Source code for dscript.utils</h1><div class="highlight"><pre>
<span></span><span class="kn">import</span> <span class="nn">torch</span>
<span class="kn">import</span> <span class="nn">torch.utils.data</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">pandas</span> <span class="k">as</span> <span class="nn">pd</span>
<span class="kn">import</span> <span class="nn">subprocess</span> <span class="k">as</span> <span class="nn">sp</span>
<span class="kn">import</span> <span class="nn">sys</span>
<span class="kn">import</span> <span class="nn">gzip</span> <span class="k">as</span> <span class="nn">gz</span>
<span class="kn">from</span> <span class="nn">datetime</span> <span class="kn">import</span> <span class="n">datetime</span>
<span class="kn">from</span> <span class="nn">.fasta</span> <span class="kn">import</span> <span class="n">parse</span>

<div class="viewcode-block" id="log"><a class="viewcode-back" href="../../api/index.html#dscript.utils.log">[docs]</a><span class="k">def</span> <span class="nf">log</span><span class="p">(</span><span class="n">msg</span><span class="p">,</span> <span class="n">file</span><span class="o">=</span><span class="n">sys</span><span class="o">.</span><span class="n">stderr</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Log datetime-stamped message to file</span>
<span class="sd">    </span>
<span class="sd">    :param msg: Message to log</span>
<span class="sd">    :param f: Writable file object to log message to</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">timestr</span> <span class="o">=</span> <span class="n">datetime</span><span class="o">.</span><span class="n">utcnow</span><span class="p">()</span><span class="o">.</span><span class="n">isoformat</span><span class="p">(</span><span class="n">sep</span><span class="o">=</span><span class="s1">&#39;-&#39;</span><span class="p">,</span> <span class="n">timespec</span><span class="o">=</span><span class="s1">&#39;milliseconds&#39;</span><span class="p">)</span>
    <span class="n">file</span><span class="o">.</span><span class="n">write</span><span class="p">(</span><span class="sa">f</span><span class="s2">&quot;[</span><span class="si">{</span><span class="n">timestr</span><span class="si">}</span><span class="s2">] </span><span class="si">{</span><span class="n">msg</span><span class="si">}</span><span class="se">\n</span><span class="s2">&quot;</span><span class="p">)</span>
    <span class="n">file</span><span class="o">.</span><span class="n">flush</span><span class="p">()</span></div>

<div class="viewcode-block" id="plot_PR_curve"><a class="viewcode-back" href="../../api/index.html#dscript.utils.plot_PR_curve">[docs]</a><span class="k">def</span> <span class="nf">plot_PR_curve</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">phat</span><span class="p">,</span> <span class="n">saveFile</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Plot precision-recall curve.</span>

<span class="sd">    :param y: Labels</span>
<span class="sd">    :type y: np.ndarray</span>
<span class="sd">    :param phat: Predicted probabilities</span>
<span class="sd">    :type phat: np.ndarray</span>
<span class="sd">    :param saveFile: File for plot of curve to be saved to</span>
<span class="sd">    :type saveFile: str</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
    <span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="kn">import</span> <span class="n">precision_recall_curve</span><span class="p">,</span> <span class="n">average_precision_score</span>

    <span class="n">aupr</span> <span class="o">=</span> <span class="n">average_precision_score</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">phat</span><span class="p">)</span>
    <span class="n">precision</span><span class="p">,</span> <span class="n">recall</span><span class="p">,</span> <span class="n">_</span> <span class="o">=</span> <span class="n">precision_recall_curve</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">phat</span><span class="p">)</span>

    <span class="n">plt</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">recall</span><span class="p">,</span> <span class="n">precision</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">&quot;b&quot;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> <span class="n">where</span><span class="o">=</span><span class="s2">&quot;post&quot;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">fill_between</span><span class="p">(</span><span class="n">recall</span><span class="p">,</span> <span class="n">precision</span><span class="p">,</span> <span class="n">step</span><span class="o">=</span><span class="s2">&quot;post&quot;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">&quot;b&quot;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">&quot;Recall&quot;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;Precision&quot;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">ylim</span><span class="p">([</span><span class="mf">0.0</span><span class="p">,</span> <span class="mf">1.05</span><span class="p">])</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">xlim</span><span class="p">([</span><span class="mf">0.0</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">])</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;Precision-Recall (AUPR: </span><span class="si">{:.3}</span><span class="s2">)&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">aupr</span><span class="p">))</span>
    <span class="k">if</span> <span class="n">saveFile</span><span class="p">:</span>
        <span class="n">plt</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">saveFile</span><span class="p">)</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span></div>


<div class="viewcode-block" id="plot_ROC_curve"><a class="viewcode-back" href="../../api/index.html#dscript.utils.plot_ROC_curve">[docs]</a><span class="k">def</span> <span class="nf">plot_ROC_curve</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">phat</span><span class="p">,</span> <span class="n">saveFile</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Plot receiver operating characteristic curve.</span>

<span class="sd">    :param y: Labels</span>
<span class="sd">    :type y: np.ndarray</span>
<span class="sd">    :param phat: Predicted probabilities</span>
<span class="sd">    :type phat: np.ndarray</span>
<span class="sd">    :param saveFile: File for plot of curve to be saved to</span>
<span class="sd">    :type saveFile: str</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span>
    <span class="kn">from</span> <span class="nn">sklearn.metrics</span> <span class="kn">import</span> <span class="n">roc_curve</span><span class="p">,</span> <span class="n">roc_auc_score</span>

    <span class="n">auroc</span> <span class="o">=</span> <span class="n">roc_auc_score</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">phat</span><span class="p">)</span>

    <span class="n">fpr</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="n">roc_thresh</span> <span class="o">=</span> <span class="n">roc_curve</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="n">phat</span><span class="p">)</span>
    <span class="nb">print</span><span class="p">(</span><span class="s2">&quot;AUROC:&quot;</span><span class="p">,</span> <span class="n">auroc</span><span class="p">)</span>

    <span class="n">plt</span><span class="o">.</span><span class="n">step</span><span class="p">(</span><span class="n">fpr</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">&quot;b&quot;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> <span class="n">where</span><span class="o">=</span><span class="s2">&quot;post&quot;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">fill_between</span><span class="p">(</span><span class="n">fpr</span><span class="p">,</span> <span class="n">tpr</span><span class="p">,</span> <span class="n">step</span><span class="o">=</span><span class="s2">&quot;post&quot;</span><span class="p">,</span> <span class="n">alpha</span><span class="o">=</span><span class="mf">0.2</span><span class="p">,</span> <span class="n">color</span><span class="o">=</span><span class="s2">&quot;b&quot;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">xlabel</span><span class="p">(</span><span class="s2">&quot;FPR&quot;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">ylabel</span><span class="p">(</span><span class="s2">&quot;TPR&quot;</span><span class="p">)</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">ylim</span><span class="p">([</span><span class="mf">0.0</span><span class="p">,</span> <span class="mf">1.05</span><span class="p">])</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">xlim</span><span class="p">([</span><span class="mf">0.0</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">])</span>
    <span class="n">plt</span><span class="o">.</span><span class="n">title</span><span class="p">(</span><span class="s2">&quot;Receiver Operating Characteristic (AUROC: </span><span class="si">{:.3}</span><span class="s2">)&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">auroc</span><span class="p">))</span>
    <span class="k">if</span> <span class="n">saveFile</span><span class="p">:</span>
        <span class="n">plt</span><span class="o">.</span><span class="n">savefig</span><span class="p">(</span><span class="n">saveFile</span><span class="p">)</span>
    <span class="k">else</span><span class="p">:</span>
        <span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span></div>


<div class="viewcode-block" id="RBF"><a class="viewcode-back" href="../../api/index.html#dscript.utils.RBF">[docs]</a><span class="k">def</span> <span class="nf">RBF</span><span class="p">(</span><span class="n">D</span><span class="p">,</span> <span class="n">sigma</span><span class="o">=</span><span class="kc">None</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Convert distance matrix into similarity matrix using Radial Basis Function (RBF) Kernel.</span>

<span class="sd">    :math:`RBF(x,x&#39;) = \\exp{\\frac{-(x - x&#39;)^{2}}{2\\sigma^{2}}}`</span>

<span class="sd">    :param D: Distance matrix</span>
<span class="sd">    :type D: np.ndarray</span>
<span class="sd">    :param sigma: Bandwith of RBF Kernel [default: :math:`\\sqrt{\\text{max}(D)}`]</span>
<span class="sd">    :type sigma: float</span>
<span class="sd">    :return: Similarity matrix</span>
<span class="sd">    :rtype: np.ndarray</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">sigma</span> <span class="o">=</span> <span class="n">sigma</span> <span class="ow">or</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">max</span><span class="p">(</span><span class="n">D</span><span class="p">))</span>
    <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="o">-</span><span class="mi">1</span> <span class="o">*</span> <span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">square</span><span class="p">(</span><span class="n">D</span><span class="p">)</span> <span class="o">/</span> <span class="p">(</span><span class="mi">2</span> <span class="o">*</span> <span class="n">sigma</span> <span class="o">**</span> <span class="mi">2</span><span class="p">)))</span></div>


<div class="viewcode-block" id="gpu_mem"><a class="viewcode-back" href="../../api/index.html#dscript.utils.gpu_mem">[docs]</a><span class="k">def</span> <span class="nf">gpu_mem</span><span class="p">(</span><span class="n">device</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Get current memory usage for GPU.</span>

<span class="sd">    :param device: GPU device number</span>
<span class="sd">    :type device: int</span>
<span class="sd">    :return: memory used, memory total</span>
<span class="sd">    :rtype: int, int</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">result</span> <span class="o">=</span> <span class="n">sp</span><span class="o">.</span><span class="n">check_output</span><span class="p">(</span>
        <span class="p">[</span>
            <span class="s2">&quot;nvidia-smi&quot;</span><span class="p">,</span>
            <span class="s2">&quot;--query-gpu=memory.used,memory.total&quot;</span><span class="p">,</span>
            <span class="s2">&quot;--format=csv,nounits,noheader&quot;</span><span class="p">,</span>
            <span class="s2">&quot;--id=</span><span class="si">{}</span><span class="s2">&quot;</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="n">device</span><span class="p">),</span>
        <span class="p">],</span>
        <span class="n">encoding</span><span class="o">=</span><span class="s2">&quot;utf-8&quot;</span><span class="p">,</span>
    <span class="p">)</span>
    <span class="n">gpu_memory</span> <span class="o">=</span> <span class="p">[</span><span class="nb">int</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">result</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="s2">&quot;,&quot;</span><span class="p">)]</span>
    <span class="k">return</span> <span class="n">gpu_memory</span><span class="p">[</span><span class="mi">0</span><span class="p">],</span> <span class="n">gpu_memory</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span></div>


<div class="viewcode-block" id="PairedDataset"><a class="viewcode-back" href="../../api/index.html#dscript.utils.PairedDataset">[docs]</a><span class="k">class</span> <span class="nc">PairedDataset</span><span class="p">(</span><span class="n">torch</span><span class="o">.</span><span class="n">utils</span><span class="o">.</span><span class="n">data</span><span class="o">.</span><span class="n">Dataset</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Dataset to be used by the PyTorch data loader for pairs of sequences and their labels.</span>

<span class="sd">    :param X0: List of first item in the pair</span>
<span class="sd">    :param X1: List of second item in the pair</span>
<span class="sd">    :param Y: List of labels</span>
<span class="sd">    &quot;&quot;&quot;</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="n">X0</span><span class="p">,</span> <span class="n">X1</span><span class="p">,</span> <span class="n">Y</span><span class="p">):</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">X0</span> <span class="o">=</span> <span class="n">X0</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">X1</span> <span class="o">=</span> <span class="n">X1</span>
        <span class="bp">self</span><span class="o">.</span><span class="n">Y</span> <span class="o">=</span> <span class="n">Y</span>
        <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">X0</span><span class="p">)</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">X1</span><span class="p">),</span> <span class="s2">&quot;X0: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">X0</span><span class="p">))</span> <span class="o">+</span> <span class="s2">&quot; X1: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">X1</span><span class="p">))</span> <span class="o">+</span> <span class="s2">&quot; Y: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">Y</span><span class="p">))</span>
        <span class="k">assert</span> <span class="nb">len</span><span class="p">(</span><span class="n">X0</span><span class="p">)</span> <span class="o">==</span> <span class="nb">len</span><span class="p">(</span><span class="n">Y</span><span class="p">),</span> <span class="s2">&quot;X0: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">X0</span><span class="p">))</span> <span class="o">+</span> <span class="s2">&quot; X1: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">X1</span><span class="p">))</span> <span class="o">+</span> <span class="s2">&quot; Y: &quot;</span> <span class="o">+</span> <span class="nb">str</span><span class="p">(</span><span class="nb">len</span><span class="p">(</span><span class="n">Y</span><span class="p">))</span>

    <span class="k">def</span> <span class="fm">__len__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
        <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">X0</span><span class="p">)</span>

    <span class="k">def</span> <span class="fm">__getitem__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">i</span><span class="p">):</span>
        <span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">X0</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">X1</span><span class="p">[</span><span class="n">i</span><span class="p">],</span> <span class="bp">self</span><span class="o">.</span><span class="n">Y</span><span class="p">[</span><span class="n">i</span><span class="p">]</span></div>


<div class="viewcode-block" id="collate_paired_sequences"><a class="viewcode-back" href="../../api/index.html#dscript.utils.collate_paired_sequences">[docs]</a><span class="k">def</span> <span class="nf">collate_paired_sequences</span><span class="p">(</span><span class="n">args</span><span class="p">):</span>
    <span class="sd">&quot;&quot;&quot;</span>
<span class="sd">    Collate function for PyTorch data loader.</span>
<span class="sd">    &quot;&quot;&quot;</span>
    <span class="n">x0</span> <span class="o">=</span> <span class="p">[</span><span class="n">a</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="k">for</span> <span class="n">a</span> <span class="ow">in</span> <span class="n">args</span><span class="p">]</span>
    <span class="n">x1</span> <span class="o">=</span> <span class="p">[</span><span class="n">a</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span> <span class="k">for</span> <span class="n">a</span> <span class="ow">in</span> <span class="n">args</span><span class="p">]</span>
    <span class="n">y</span> <span class="o">=</span> <span class="p">[</span><span class="n">a</span><span class="p">[</span><span class="mi">2</span><span class="p">]</span> <span class="k">for</span> <span class="n">a</span> <span class="ow">in</span> <span class="n">args</span><span class="p">]</span>
    <span class="k">return</span> <span class="n">x0</span><span class="p">,</span> <span class="n">x1</span><span class="p">,</span> <span class="n">torch</span><span class="o">.</span><span class="n">stack</span><span class="p">(</span><span class="n">y</span><span class="p">,</span> <span class="mi">0</span><span class="p">)</span></div>
</pre></div>

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