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<section id="numpy-absolute">
<h1>numpy.absolute<a class="headerlink" href="#numpy-absolute" title="Link to this heading">#</a></h1>
<dl class="py data">
<dt class="sig sig-object py" id="numpy.absolute">
<span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">absolute</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">/</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">out=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">where=True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">casting='same_kind'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">order='K'</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">dtype=None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">subok=True</span></span></em><span class="optional">[</span>, <em class="sig-param"><span class="n"><span class="pre">signature</span></span></em><span class="optional">]</span><span class="sig-paren">)</span><em class="property"><span class="w"> </span><span class="p"><span class="pre">=</span></span><span class="w"> </span><span class="pre"><ufunc</span> <span class="pre">'absolute'></span></em><a class="headerlink" href="#numpy.absolute" title="Link to this definition">#</a></dt>
<dd><p>Calculate the absolute value element-wise.</p>
<p><code class="docutils literal notranslate"><span class="pre">np.abs</span></code> is a shorthand for this function.</p>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><dl class="simple">
<dt><strong>x</strong><span class="classifier">array_like</span></dt><dd><p>Input array.</p>
</dd>
<dt><strong>out</strong><span class="classifier">ndarray, None, or tuple of ndarray and None, optional</span></dt><dd><p>A location into which the result is stored. If provided, it must have
a shape that the inputs broadcast to. If not provided or None,
a freshly-allocated array is returned. A tuple (possible only as a
keyword argument) must have length equal to the number of outputs.</p>
</dd>
<dt><strong>where</strong><span class="classifier">array_like, optional</span></dt><dd><p>This condition is broadcast over the input. At locations where the
condition is True, the <em class="xref py py-obj">out</em> array will be set to the ufunc result.
Elsewhere, the <em class="xref py py-obj">out</em> array will retain its original value.
Note that if an uninitialized <em class="xref py py-obj">out</em> array is created via the default
<code class="docutils literal notranslate"><span class="pre">out=None</span></code>, locations within it where the condition is False will
remain uninitialized.</p>
</dd>
<dt><strong>**kwargs</strong></dt><dd><p>For other keyword-only arguments, see the
<a class="reference internal" href="../ufuncs.html#ufuncs-kwargs"><span class="std std-ref">ufunc docs</span></a>.</p>
</dd>
</dl>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><dl class="simple">
<dt><strong>absolute</strong><span class="classifier">ndarray</span></dt><dd><p>An ndarray containing the absolute value of
each element in <em class="xref py py-obj">x</em>. For complex input, <code class="docutils literal notranslate"><span class="pre">a</span> <span class="pre">+</span> <span class="pre">ib</span></code>, the
absolute value is <span class="math notranslate nohighlight">\(\sqrt{ a^2 + b^2 }\)</span>.
This is a scalar if <em class="xref py py-obj">x</em> is a scalar.</p>
</dd>
</dl>
</dd>
</dl>
<p class="rubric">Examples</p>
<div class="try_examples_outer_container docutils container" id="e647a931-acc8-487c-9240-55cc8c240373">
<div class="try_examples_button_container"><button class="try_examples_button" onclick="window.tryExamplesShowIframe('e647a931-acc8-487c-9240-55cc8c240373','0cc77fa5-b6d4-420e-9027-0f3b093c5578','00760f8f-7b94-40c7-b299-ded31d6d25b7','../../lite/tree/../notebooks/index.html?path=ffde3e01_d623_4fe0_b07f_e95796e5beb1.ipynb','None')">Try it in your browser!</button></div><div class="try_examples_content docutils container">
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
<span class="gp">>>> </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="o">-</span><span class="mf">1.2</span><span class="p">,</span> <span class="mf">1.2</span><span class="p">])</span>
<span class="gp">>>> </span><span class="n">np</span><span class="o">.</span><span class="n">absolute</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="go">array([ 1.2, 1.2])</span>
<span class="gp">>>> </span><span class="n">np</span><span class="o">.</span><span class="n">absolute</span><span class="p">(</span><span class="mf">1.2</span> <span class="o">+</span> <span class="mi">1</span><span class="n">j</span><span class="p">)</span>
<span class="go">1.5620499351813308</span>
</pre></div>
</div>
<p>Plot the function over <code class="docutils literal notranslate"><span class="pre">[-10,</span> <span class="pre">10]</span></code>:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span><span class="w"> </span><span class="nn">matplotlib.pyplot</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">plt</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">linspace</span><span class="p">(</span><span class="n">start</span><span class="o">=-</span><span class="mi">10</span><span class="p">,</span> <span class="n">stop</span><span class="o">=</span><span class="mi">10</span><span class="p">,</span> <span class="n">num</span><span class="o">=</span><span class="mi">101</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">plt</span><span class="o">.</span><span class="n">plot</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">absolute</span><span class="p">(</span><span class="n">x</span><span class="p">))</span>
<span class="gp">>>> </span><span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>
</div>
<figure class="align-default">
<img alt="../../_images/numpy-absolute-1_00_00.png" class="plot-directive" src="../../_images/numpy-absolute-1_00_00.png" />
</figure>
<p>Plot the function over the complex plane:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">xx</span> <span class="o">=</span> <span class="n">x</span> <span class="o">+</span> <span class="mi">1</span><span class="n">j</span> <span class="o">*</span> <span class="n">x</span><span class="p">[:,</span> <span class="n">np</span><span class="o">.</span><span class="n">newaxis</span><span class="p">]</span>
<span class="gp">>>> </span><span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">xx</span><span class="p">),</span> <span class="n">extent</span><span class="o">=</span><span class="p">[</span><span class="o">-</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">,</span> <span class="o">-</span><span class="mi">10</span><span class="p">,</span> <span class="mi">10</span><span class="p">],</span> <span class="n">cmap</span><span class="o">=</span><span class="s1">'gray'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">plt</span><span class="o">.</span><span class="n">show</span><span class="p">()</span>
</pre></div>
</div>
<figure class="align-default">
<img alt="../../_images/numpy-absolute-1_01_00.png" class="plot-directive" src="../../_images/numpy-absolute-1_01_00.png" />
</figure>
<p>The <a class="reference external" href="https://docs.python.org/3/library/functions.html#abs" title="(in Python v3.13)"><code class="xref py py-obj docutils literal notranslate"><span class="pre">abs</span></code></a> function can be used as a shorthand for <code class="docutils literal notranslate"><span class="pre">np.absolute</span></code> on
ndarrays.</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">x</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="o">-</span><span class="mf">1.2</span><span class="p">,</span> <span class="mf">1.2</span><span class="p">])</span>
<span class="gp">>>> </span><span class="nb">abs</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="go">array([1.2, 1.2])</span>
</pre></div>
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