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<section id="numpy-ascontiguousarray">
<h1>numpy.ascontiguousarray<a class="headerlink" href="#numpy-ascontiguousarray" title="Link to this heading">#</a></h1>
<dl class="py function">
<dt class="sig sig-object py" id="numpy.ascontiguousarray">
<span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">ascontiguousarray</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">dtype</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">like</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#numpy.ascontiguousarray" title="Link to this definition">#</a></dt>
<dd><p>Return a contiguous array (ndim >= 1) in memory (C order).</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>dtype</strong><span class="classifier">str or dtype object, optional</span></dt><dd><p>Data-type of returned array.</p>
</dd>
<dt><strong>like</strong><span class="classifier">array_like, optional</span></dt><dd><p>Reference object to allow the creation of arrays which are not
NumPy arrays. If an array-like passed in as <code class="docutils literal notranslate"><span class="pre">like</span></code> supports
the <code class="docutils literal notranslate"><span class="pre">__array_function__</span></code> protocol, the result will be defined
by it. In this case, it ensures the creation of an array object
compatible with that passed in via this argument.</p>
<div class="versionadded">
<p><span class="versionmodified added">New in version 1.20.0.</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>out</strong><span class="classifier">ndarray</span></dt><dd><p>Contiguous array of same shape and content as <em class="xref py py-obj">a</em>, with type <a class="reference internal" href="numpy.dtype.html#numpy.dtype" title="numpy.dtype"><code class="xref py py-obj docutils literal notranslate"><span class="pre">dtype</span></code></a>
if specified.</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.asfortranarray.html#numpy.asfortranarray" title="numpy.asfortranarray"><code class="xref py py-obj docutils literal notranslate"><span class="pre">asfortranarray</span></code></a></dt><dd><p>Convert input to an ndarray with column-major memory order.</p>
</dd>
<dt><a class="reference internal" href="numpy.require.html#numpy.require" title="numpy.require"><code class="xref py py-obj docutils literal notranslate"><span class="pre">require</span></code></a></dt><dd><p>Return an ndarray that satisfies requirements.</p>
</dd>
<dt><a class="reference internal" href="numpy.ndarray.flags.html#numpy.ndarray.flags" title="numpy.ndarray.flags"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ndarray.flags</span></code></a></dt><dd><p>Information about the memory layout of the array.</p>
</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="try_examples_outer_container docutils container" id="5bc99f33-ad8b-4187-8ede-a097642bd374">
<div class="try_examples_button_container"><button class="try_examples_button" onclick="window.tryExamplesShowIframe('5bc99f33-ad8b-4187-8ede-a097642bd374','3b3dc3c9-1310-48c4-a7a9-efccad7959bd','63510a4d-8767-4b7d-9d74-5e4d21398c02','../../lite/tree/../notebooks/index.html?path=787d72fd_b393_400d_a353_23f536944c07.ipynb','None')">Try it in your browser!</button></div><div class="try_examples_content docutils container">
<p>Starting with a Fortran-contiguous array:</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">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">ones</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="n">order</span><span class="o">=</span><span class="s1">'F'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">x</span><span class="o">.</span><span class="n">flags</span><span class="p">[</span><span class="s1">'F_CONTIGUOUS'</span><span class="p">]</span>
<span class="go">True</span>
</pre></div>
</div>
<p>Calling <code class="docutils literal notranslate"><span class="pre">ascontiguousarray</span></code> makes a C-contiguous copy:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ascontiguousarray</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">y</span><span class="o">.</span><span class="n">flags</span><span class="p">[</span><span class="s1">'C_CONTIGUOUS'</span><span class="p">]</span>
<span class="go">True</span>
<span class="gp">>>> </span><span class="n">np</span><span class="o">.</span><span class="n">may_share_memory</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">)</span>
<span class="go">False</span>
</pre></div>
</div>
<p>Now, starting with a C-contiguous array:</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">ones</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="n">order</span><span class="o">=</span><span class="s1">'C'</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">x</span><span class="o">.</span><span class="n">flags</span><span class="p">[</span><span class="s1">'C_CONTIGUOUS'</span><span class="p">]</span>
<span class="go">True</span>
</pre></div>
</div>
<p>Then, calling <code class="docutils literal notranslate"><span class="pre">ascontiguousarray</span></code> returns the same object:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">y</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">ascontiguousarray</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">x</span> <span class="ow">is</span> <span class="n">y</span>
<span class="go">True</span>
</pre></div>
</div>
<p>Note: This function returns an array with at least one-dimension (1-d)
so it will not preserve 0-d arrays.</p>
</div>
</div>
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