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<!DOCTYPE html>
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<section id="numpy-broadcast-to">
<h1>numpy.broadcast_to<a class="headerlink" href="#numpy-broadcast-to" title="Link to this heading">#</a></h1>
<dl class="py function">
<dt class="sig sig-object py" id="numpy.broadcast_to">
<span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">broadcast_to</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">array</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">shape</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">subok</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">False</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/lib/_stride_tricks_impl.py#L367-L410"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.broadcast_to" title="Link to this definition">#</a></dt>
<dd><p>Broadcast an array to a new shape.</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>array</strong><span class="classifier">array_like</span></dt><dd><p>The array to broadcast.</p>
</dd>
<dt><strong>shape</strong><span class="classifier">tuple or int</span></dt><dd><p>The shape of the desired array. A single integer <code class="docutils literal notranslate"><span class="pre">i</span></code> is interpreted
as <code class="docutils literal notranslate"><span class="pre">(i,)</span></code>.</p>
</dd>
<dt><strong>subok</strong><span class="classifier">bool, optional</span></dt><dd><p>If True, then sub-classes will be passed-through, otherwise
the returned array will be forced to be a base-class array (default).</p>
</dd>
</dl>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><dl class="simple">
<dt><strong>broadcast</strong><span class="classifier">array</span></dt><dd><p>A readonly view on the original array with the given shape. It is
typically not contiguous. Furthermore, more than one element of a
broadcasted array may refer to a single memory location.</p>
</dd>
</dl>
</dd>
<dt class="field-odd">Raises<span class="colon">:</span></dt>
<dd class="field-odd"><dl class="simple">
<dt>ValueError</dt><dd><p>If the array is not compatible with the new shape according to NumPy’s
broadcasting rules.</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.broadcast.html#numpy.broadcast" title="numpy.broadcast"><code class="xref py py-obj docutils literal notranslate"><span class="pre">broadcast</span></code></a></dt><dd></dd>
<dt><a class="reference internal" href="numpy.broadcast_arrays.html#numpy.broadcast_arrays" title="numpy.broadcast_arrays"><code class="xref py py-obj docutils literal notranslate"><span class="pre">broadcast_arrays</span></code></a></dt><dd></dd>
<dt><a class="reference internal" href="numpy.broadcast_shapes.html#numpy.broadcast_shapes" title="numpy.broadcast_shapes"><code class="xref py py-obj docutils literal notranslate"><span class="pre">broadcast_shapes</span></code></a></dt><dd></dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="try_examples_outer_container docutils container" id="4c7c78fb-5d93-426b-8c8f-c790a2bb26eb">
<div class="try_examples_button_container"><button class="try_examples_button" onclick="window.tryExamplesShowIframe('4c7c78fb-5d93-426b-8c8f-c790a2bb26eb','b3e48f5d-742b-4053-b2b9-d0636c809177','9ca94d22-68ca-4068-a38e-7b55861fa3b1','../../lite/tree/../notebooks/index.html?path=c1613b97_b512_4c0b_bf0e_c78e7960dddf.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="mi">1</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="gp">>>> </span><span class="n">np</span><span class="o">.</span><span class="n">broadcast_to</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">3</span><span class="p">))</span>
<span class="go">array([[1, 2, 3],</span>
<span class="go"> [1, 2, 3],</span>
<span class="go"> [1, 2, 3]])</span>
</pre></div>
</div>
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