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<section id="numpy-argmin">
<h1>numpy.argmin<a class="headerlink" href="#numpy-argmin" title="Link to this heading">#</a></h1>
<dl class="py function">
<dt class="sig sig-object py" id="numpy.argmin">
<span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">argmin</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">a</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">axis=None</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">keepdims=<no</span> <span class="pre">value></span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/fromnumeric.py#L1348-L1439"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.argmin" title="Link to this definition">#</a></dt>
<dd><p>Returns the indices of the minimum values along an axis.</p>
<dl class="field-list">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><dl>
<dt><strong>a</strong><span class="classifier">array_like</span></dt><dd><p>Input array.</p>
</dd>
<dt><strong>axis</strong><span class="classifier">int, optional</span></dt><dd><p>By default, the index is into the flattened array, otherwise
along the specified axis.</p>
</dd>
<dt><strong>out</strong><span class="classifier">array, optional</span></dt><dd><p>If provided, the result will be inserted into this array. It should
be of the appropriate shape and dtype.</p>
</dd>
<dt><strong>keepdims</strong><span class="classifier">bool, optional</span></dt><dd><p>If this is set to True, the axes which are reduced are left
in the result as dimensions with size one. With this option,
the result will broadcast correctly against the array.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 1.22.0.</span></p>
</div>
</dd>
</dl>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><dl class="simple">
<dt><strong>index_array</strong><span class="classifier">ndarray of ints</span></dt><dd><p>Array of indices into the array. It has the same shape as <em class="xref py py-obj">a.shape</em>
with the dimension along <em class="xref py py-obj">axis</em> removed. If <em class="xref py py-obj">keepdims</em> is set to True,
then the size of <em class="xref py py-obj">axis</em> will be 1 with the resulting array having same
shape as <em class="xref py py-obj">a.shape</em>.</p>
</dd>
</dl>
</dd>
</dl>
<div class="admonition seealso">
<p class="admonition-title">See also</p>
<dl class="simple">
<dt><a class="reference internal" href="numpy.ndarray.argmin.html#numpy.ndarray.argmin" title="numpy.ndarray.argmin"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ndarray.argmin</span></code></a>, <a class="reference internal" href="numpy.argmax.html#numpy.argmax" title="numpy.argmax"><code class="xref py py-obj docutils literal notranslate"><span class="pre">argmax</span></code></a></dt><dd></dd>
<dt><a class="reference internal" href="numpy.amin.html#numpy.amin" title="numpy.amin"><code class="xref py py-obj docutils literal notranslate"><span class="pre">amin</span></code></a></dt><dd><p>The minimum value along a given axis.</p>
</dd>
<dt><a class="reference internal" href="numpy.unravel_index.html#numpy.unravel_index" title="numpy.unravel_index"><code class="xref py py-obj docutils literal notranslate"><span class="pre">unravel_index</span></code></a></dt><dd><p>Convert a flat index into an index tuple.</p>
</dd>
<dt><a class="reference internal" href="numpy.take_along_axis.html#numpy.take_along_axis" title="numpy.take_along_axis"><code class="xref py py-obj docutils literal notranslate"><span class="pre">take_along_axis</span></code></a></dt><dd><p>Apply <code class="docutils literal notranslate"><span class="pre">np.expand_dims(index_array,</span> <span class="pre">axis)</span></code> from argmin to an array as if by calling min.</p>
</dd>
</dl>
</div>
<p class="rubric">Notes</p>
<p>In case of multiple occurrences of the minimum values, the indices
corresponding to the first occurrence are returned.</p>
<p class="rubric">Examples</p>
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<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">a</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">6</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">)</span> <span class="o">+</span> <span class="mi">10</span>
<span class="gp">>>> </span><span class="n">a</span>
<span class="go">array([[10, 11, 12],</span>
<span class="go"> [13, 14, 15]])</span>
<span class="gp">>>> </span><span class="n">np</span><span class="o">.</span><span class="n">argmin</span><span class="p">(</span><span class="n">a</span><span class="p">)</span>
<span class="go">0</span>
<span class="gp">>>> </span><span class="n">np</span><span class="o">.</span><span class="n">argmin</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">0</span><span class="p">)</span>
<span class="go">array([0, 0, 0])</span>
<span class="gp">>>> </span><span class="n">np</span><span class="o">.</span><span class="n">argmin</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="go">array([0, 0])</span>
</pre></div>
</div>
<p>Indices of the minimum elements of a N-dimensional array:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">ind</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">unravel_index</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">argmin</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="kc">None</span><span class="p">),</span> <span class="n">a</span><span class="o">.</span><span class="n">shape</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">ind</span>
<span class="go">(0, 0)</span>
<span class="gp">>>> </span><span class="n">a</span><span class="p">[</span><span class="n">ind</span><span class="p">]</span>
<span class="go">10</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">b</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">6</span><span class="p">)</span> <span class="o">+</span> <span class="mi">10</span>
<span class="gp">>>> </span><span class="n">b</span><span class="p">[</span><span class="mi">4</span><span class="p">]</span> <span class="o">=</span> <span class="mi">10</span>
<span class="gp">>>> </span><span class="n">b</span>
<span class="go">array([10, 11, 12, 13, 10, 15])</span>
<span class="gp">>>> </span><span class="n">np</span><span class="o">.</span><span class="n">argmin</span><span class="p">(</span><span class="n">b</span><span class="p">)</span> <span class="c1"># Only the first occurrence is returned.</span>
<span class="go">0</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">array</span><span class="p">([[</span><span class="mi">4</span><span class="p">,</span><span class="mi">2</span><span class="p">,</span><span class="mi">3</span><span class="p">],</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span><span class="mi">0</span><span class="p">,</span><span class="mi">3</span><span class="p">]])</span>
<span class="gp">>>> </span><span class="n">index_array</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">argmin</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">axis</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span>
<span class="gp">>>> </span><span class="c1"># Same as np.amin(x, axis=-1, keepdims=True)</span>
<span class="gp">>>> </span><span class="n">np</span><span class="o">.</span><span class="n">take_along_axis</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">expand_dims</span><span class="p">(</span><span class="n">index_array</span><span class="p">,</span> <span class="n">axis</span><span class="o">=-</span><span class="mi">1</span><span class="p">),</span> <span class="n">axis</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span>
<span class="go">array([[2],</span>
<span class="go"> [0]])</span>
<span class="gp">>>> </span><span class="c1"># Same as np.amax(x, axis=-1)</span>
<span class="gp">>>> </span><span class="n">np</span><span class="o">.</span><span class="n">take_along_axis</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">expand_dims</span><span class="p">(</span><span class="n">index_array</span><span class="p">,</span> <span class="n">axis</span><span class="o">=-</span><span class="mi">1</span><span class="p">),</span>
<span class="gp">... </span> <span class="n">axis</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span><span class="o">.</span><span class="n">squeeze</span><span class="p">(</span><span class="n">axis</span><span class="o">=-</span><span class="mi">1</span><span class="p">)</span>
<span class="go">array([2, 0])</span>
</pre></div>
</div>
<p>Setting <em class="xref py py-obj">keepdims</em> to <em class="xref py py-obj">True</em>,</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">arange</span><span class="p">(</span><span class="mi">24</span><span class="p">)</span><span class="o">.</span><span class="n">reshape</span><span class="p">((</span><span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="mi">4</span><span class="p">))</span>
<span class="gp">>>> </span><span class="n">res</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">argmin</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">axis</span><span class="o">=</span><span class="mi">1</span><span class="p">,</span> <span class="n">keepdims</span><span class="o">=</span><span class="kc">True</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">res</span><span class="o">.</span><span class="n">shape</span>
<span class="go">(2, 1, 4)</span>
</pre></div>
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